1 Start of project

5 Learning the basics

13 Reaching out and increasing awareness

31 Analysis and research/survey results

Contents

The project Bridging the gap between seasonal climate forecasts (SCFs) anddecisionmakers in agriculture funded by the Australian Centre for International AgriculturalResearch (ACIAR) is a four-year collaborative undertaking that started in March 2005. Itskey objective is to identify and close the gap between the potential and practical applicationof SCFs to agricultural systems and policies in the Philippines and Australia. The projectinvolves research staff from the Philippine Atmospheric, Geophysical and AstronomicalServices Administration (PAGASA), Philippine Institute for Development Studies (PIDS),Leyte State University (LSU), South Australian Research and Development Institute(SARDI), Charles Sturt University (CSU), and New South Wales Department of PrimaryIndustries (NSW-DPI).

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The Government of the Philippines, through the Philippine Council for Agriculture, Forestry and Natural

Resources Research and Development (PCARRD), and the Australian Government, through the

Australian Centre for International Agricultural Research (ACIAR), signed a Memorandum of Subsidiary

Arrangement in October 2004 for the undertaking of a four-year project titled Bridging the gap between seasonal

climate forecasts and decisionmakers in agriculture. The project will aim to look into and close the gap between

the potential value of seasonal climate forecasts (SCFs), particularly those looking at the El Niño Southern Oscillation

(ENSO) phenomenon, and their actual use and application in the risk-management decisions of farmers at the

farm level and policymakers at the macro level. Implementing institutions for the Philippines are the Philippine

Atmospheric, Geophysical and Astronomical Services Administration (PAGASA), the Philippine Institute for

Development Studies (PIDS) and the Leyte State University (LSU) while for Australia, the key institutions involved

are the South Australian Research and Development Institute (SARDI), New South Wales Department of Primary

Industries (NSW/DPI), and University of Sydney.

In order to raise awareness of the project, a project launch will be held on July 27, 2005 at the Dusit Hotel

Nikko, Makati City. The launch primarily aims to introduce to the public—especially to the major stakeholders of

the results of the project—the thrusts and direction of the project, its objectives, the various research and case

studies to be undertaken, the various activities and expected outputs, and the institutions/individuals involved.

The launch will also include presentations of the issues (both in the Philippines and in Australia) that the project

intends to effectively address. This activity will be attended by the project team members, members of the Philippine

Project Steering Committee, various government and private agencies/institutions affected or concerned with

the results, members of media, Australian embassy and ACIAR representatives, members of the academe,

representatives from nongovernment organizations and farmers groups, and regular participants of PAGASA’s

Quarterly Climate Outlook Forum.

A question-and-answer portion for both members of the media and other stakeholders will follow the various

presentations regarding the project in order to entertain further questions about the project and elicit comments

and possible feedback on some of its aspects. (SCF Project Updates June 2005)

SCF project launch

SCF FolioA compilation of information and research materials

on seasonal climate forecast (SCF)

2 SCF Folio

About the project...

BackgroundAgriculture in the Philippines and eastern Australia is

greatly affected by the El Niño Southern Oscillation

(ENSO). Climate in these two countries has higher

season-to-season variability relative to other regions at

the same latitude and level of annual rainfall. Such

variability has significant effects on farm incomes. In

Australia, it accounts for around 40 percent of the

variation in its agricultural income. Similar

consequences are also seen in the Philippines. Climate

variability leaves rainfed agricultural producers exposed

to high levels of risk when making decisions about the

choice of outputs and inputs. It can also lead to

conservative practices that, while reducing the negative

effects of climatic extremes, may however come at the

expense of reduced agricultural incomes and higher

resource degradation. Because of all these, a strategic

mitigation of climatic risk that is so endemic to rainfed

agriculture would clearly be of significant value to

farmers.

Areas affected by ENSO suffer from increased

variability, but one compensation is that improvements

in the understanding of ENSO now provide a degree

of predictability about climate fluctuations. Climate

forecasts offer information on climatic conditions in the

coming season and are sometimes presented in the

form of a probability of receiving ‘above median’ or

‘below median’ rainfall. They offer skillful albeit

uncertain information about climatic conditions in

periods of 3–12 months ahead.

In Australia, the Bureau of Meteorology provides

three monthly seasonal climate outlooks based on the

Southern Oscillation Index (SOI) and sea surface

temperature (SST) anomalies. Although about 45

percent of Australian farmers claim to take seasonal

climate forecasts into account when making decisions,

focus groups show that many still have reservations on

the accuracy, lead time and economic benefits of their

application to a specific decision. The El Niño-related

drought of 2002 that affected eastern Australia,

however, has led to a heightened media and farmer

interest in climate science.

In the Philippines, PAGASA issues seasonal climate

forecasts based on the state of the equatorial Pacific

Ocean. The Philippines is a country greatly affected by

ENSO. In this regard, PAGASA releases ENSO bulletins

as part of the National ENSO Early Warning Monitoring

System (NEEWMS).

It is important to ensure the accuracy and

timeliness of climate forecasts to reduce the difficulty

of using probabilistic climate forecasts in decision-

making. Forecasts that shift the odds but do not remove

all the uncertainty are difficult for decisionmakers to

use. Specifically, there is a widespread belief that the

adoption of SCFs is hampered in both the Philippines

and Australia by the lack of robust means of showing

the economic value of SCF for specific decisions.

Australia and the Philippines promote SCFsIn an attempt to address the above shortcoming, a

Memorandum of Subsidiary Arrangement was inked

between the Philippine Council for Agriculture, Forestry

and Natural Resources Research and Development

(PCARRD) and the Australian Centre for International

Agricultural Research (ACIAR) in October 2004 for the

undertaking of a four-year project titled Bridging the

gap between seasonal climate forecasts and

decisionmakers in agriculture. Implementing

institutions for the Philippines are the Philippine

Atmospheric, Geophysical and Astronomical Services

El Niño is a phenomenon that occurs in a specific point in the easternequatorial Pacific Ocean—which is quite a distance away from thePhilippines and Australia—but its effects and impact are nonetheless feltbecause of the interactions between the ocean surface temperature effectand the overlying atmosphere in the tropical Pacific region. Thisinteraction is better known as the El Niño Southern Oscillation (ENSO).

Effect of ENSO in the tropical Pacific

Source: Australian Rainman

3

Administration (PAGASA), the Philippine Institute for

Development Studies (PIDS) and the Leyte State

University (LSU) while for Australia, the key institutions

involved are South Australian Research and Development

Institute (SARDI), New South Wales Department of Primary

Industries (NSW-DPI), and University of Sydney.

The SCF project between Australian and Philippine

institutions will draw on economics and other disciplines

to develop robust ways to use SCFs in risk management.

This project will work with decisionmakers in the

Philippines and Australia to see where, when, and why

skillful but uncertain SCFs can be valuable, and the

circumstances when they are best ignored. The end result

will be increased incomes of rural communities in the

Philippines and Australia.

The project is expected to bring about improved

economic, social, and environmental outcomes in the

collaborating countries given that better management of

climate variability has the potential to improve resource

use efficiency by providing economic benefits through

improved crop planting, management and grazing

strategies.

Case studies in the Philippines and Australia will be

used to assess where economic, environmental and social

benefits may arise. The Philippine studies will focus on

poor Filipino farmers who are vulnerable to climate

variability while Australian studies will consider the impact

of droughts on farming families and rural communities.

Two key methods are to be employed in this project.

The first is to value the potential contribution of SCF to

decisionmaking under climate uncertainty based on

insights from economics and psychology. The second

method is the use of farm and policy-level case studies in

the Philippines and Australia to gain a practical appreciation

of how decisionmakers actually use SCF and how to

bridge the gap between potential and actual use of SCF.

Case studies will use representative farm models to

estimate the potential value of SCFs and will provide

information on how farmers and other decisionmakers

use SCFs to make real decisions. An important component

of the project is the development of extension strategies

based on the case study experiences to promote the value

of SCFs. To help implement this, the project will tap into

extension networks in Australia and the Philippines and

provide tools for agricultural advisers to confidently

promote SCFs to decision problems with the greatest

payoff.

ObjectivesTo improve the capacity of PAGASA to develop and

deliver SCF for the case study regions of the

Philippines;

To distill key practical and methodological features of

economic and psychological approaches to valuing SCF;

To estimate the potential economic value of SCF for

farm and policy or industry level case studies in the

Philippines and Australia;

To identify those factors leading to a gap between

actual and potential values of SCF; and

To develop and implement strategies to better match

forecasts with decisionmaker’s needs. (SCF Project

Updates June 2005)

People and organizations involved...

Philippine Atmospheric, Geophysical andAstronomical Services Administration (PAGASA)PAGASA is the Philippines’ meteorological service

organization and is a member of the World Meteorological

Organization. Its mandate is “to mitigate or reduce the

losses to life, property and the economy of the nation

occasioned by typhoons, floods, droughts and other

destructive weather disturbances.” Its website is http://

www.pagasa. dost.gov.ph/.

Dr. Flaviana D. Hilario is the chief of the Climatology

and Agrometeorology Branch (CAB). She will supervise

the preparation of the SCF and will coordinate with

concerned agencies like the PIDS and LSU in the smooth

implementation of the project.

Ms. Edna L. Juanillo is the head of the Climate

Information Monitoring and Prediction Center (CLIMPC)

of the PAGASA (Weather Bureau). She is involved in the

interpretation and analysis of the different climate

parameters needed in the preparation of SCF. She will

assist in the coordination of the Philippine activities with

PIDS and LSU in the conduct of the study in the first two

years of the project.

Ms. Rosalina de Guzman is the assistant head of

CLIMPC. She is involved in the preparation and issuance

4 SCF Folio

of El Niño/La Niña advisories, weather outlook, and

seasonal forecast. She will participate in the translation

of global climate forecasts into local climate predictions

which is one of the information needed in the

preparation of SCF.

Mr. Ernesto R. Verceles is a weather specialist

assigned at the CLIMPC. He is involved in the

preparation and issuance of El Niño/La Niña updates,

climate information and forecasts. He will participate

in the translation of global climate forecasts into local

climate predictions.

Dr. Aida M. Jose is the former chief of the CAB. As a

local consultant of the project, she is involved in the

overall analysis and interpretation of the data and

information which will be vital in the preparation of the SCF.

Leyte State University (LSU)Leyte State University is situated in Eastern Visayas,

Philippines and is recognized as the center of excellence

for instruction, research and development in agriculture

and related fields, including forestry in the Visayas. It

provides its students with the highest quality of

scientific knowledge to serve the needs of the region.

Its web address is http://www.lsu-visca. edu.ph/.

Dr. Canesio Predo is an assistant professor

(Resource and Environmental Economics) with the

National Abaca Research Center. He is reviewing

methods of valuing SCF and applying these methods

to case studies in the Philippines.

Ms. Eva Monte is an agricultural economics

researcher at LSU. She will be working with Dr. Predo on

the case studies and the development of tools and

information packages on valuing SCFs.

Philippine Institute for Development Studies(PIDS)The Institute is a government research institution

engaged in long-term, policy-oriented research.

Through the Institute’s activities, it is hoped that policy-

oriented research on social and economic development

can be expanded to assist the government in planning

and policymaking. An important goal of PIDS is to

provide analysis of socioeconomic problems and issues

to support the formulation of plans and policies for

sustained socioeconomic development in the

Philippines. Its website is http://www.pids.gov.ph/.

Dr. Celia M. Reyes is a senior research fellow at PIDS.

Her expertise lies in econometric modelling and

poverty analysis. She is applying this expertise to both

farm and policy-level case studies in the Philippines.

Ms. Jennifer P.T. Liguton is the director for Research

Information at PIDS. She is involved in coming up with

strategies to communicate the results of the Project’s

studies to farmers and policymakers as well as to other

stakeholders.

Mr. Mario C. Feranil is the concurrent OIC vice-

president of PIDS and director for Project Services. He

will be responsible, in partnership with Dr. Kevin Parton,

for the monitoring and evaluation aspects of the project.

Mr. Christian D. Mina is an information systems

researcher at PIDS under the supervision of Dr. Celia M.

Reyes. He will be working with Dr. Reyes on the case

studies and the development of tools and information

packages on valuing seasonal climate forecasts.

South Australian Research and DevelopmentInstitute (SARDI)SARDI is a leading research and development institute

that conducts innovative applied research and

development to enhance the efficiency and economic

contribution to South Australia’s industries on field crop,

horticulture, livestock, and fishing and aquaculture as

well as on pastures and sustainable resources, and

natural resource management. Its website is

www.sardi.sa.gov.au/index.html.

Dr. Peter Hayman is principal scientist for Climate

Applications at the SARDI in Adelaide. As project leader

for both the Australian and Philippine groups, he will

draw together the inputs from economists, applied

climatologists and farm advisers and will actively be

engaged in developing learning packages for

intermediaries promoting SCFs. He will particularly

be responsible for developing the information

packages for endusers and will assist in the case

studies in Australia.

New South Wales Department of PrimaryIndustries (NSW/DPI)NSW/DPI is the largest provider of research and extension

services to agriculture in New South Wales. It is a partner

in the development of profitable, sustainable primary

industries for New South Wales to ensure that primary

industries have appropriate access to natural resources;

communities benefit from the wise use of natural

resources; and regional economies are enhanced. Its

website is http://www.dpi.nsw.gov.au/reader/dpi.

5

Dr. John Mullen is research leader for Economics

Coordination and Evaluation at the NSW/DPI and adjunct

professor at the Faculty of Rural Management at the

University of Sydney. He is involved in the review of

methods for valuing SCF and in the proposed case study

in the rangelands of NSW.

University of SydneyThe Faculty of Rural Management has research strengths

in agribusiness, farming systems and natural resource

management. Improvements in the availability and use

of seasonal climate forecasts clearly impact on all three of

these areas. Its web address is http://www.csu.edu.au/.

Professor Kevin Parton is dean of the Faculty of Rural

Management. He will concentrate on the relationships

between the economics and psychology approaches to

decisionmaking and valuation of SCF. Professor Parton will

be involved in policy case studies in both Australia and

the Philippines.

Jason Crean is a postgraduate student at the

University of Sydney and is currently undertaking a PhD

on the value of climate forecasting in selected farming

systems in eastern Australia. He has expertise in the

economic modelling of farming systems and will be

involved in the policy and farm level case studies in

Australia. (SCF Project Updates June 2005)

In a forum on Basic Climatology Concepts and

Information organized by the Philippine Institute

for Development Studies (PIDS), in collaboration

with the Philippine Atmospheric, Geophysical and

Astronomical Services Administration (PAGASA) and Leyte

State University (LSU), on April 21 under the project on

seasonal climate forecasts (SCFs) funded by the Australian

Centre for International Agricultural Research (ACIAR), a

team of climate experts and researchers from PAGASA

briefed an audience of technical and policy-level

representatives from various government agencies and

members of the academe on certain basic concepts and

information about Philippine weather and climate. The

briefings included a compehensive lecture on the El Niño

phenomenon—its definition, characteristics, evolution,

and tools of prediction, among others.

The forum is only the first of a series of fora to be

conducted by the abovementioned institutions under the

four-year ACIAR-funded project and is part of the

information, education, and communication component

of the project to help people have a better understanding

of the effects of certain climatic events and conditions

like the El Niño phenomenon and how to respond to them.

In his lecture on the El Niño event, for instance, Mr.

Ernesto Verceles, a weather specialist from PAGASA,

explained that while the El Niño is a phenomenon that

occurs in a specific point in the eastern equatorial Pacific

Ocean—which is quite a distance away from the

Philippines—its effects and impact are nonetheless felt

in the country because of the interactions between the

ocean surface temperature effect and the overlying

atmosphere in the tropical Pacific region. This interaction

is better known as the El Niño Southern Oscillation (ENSO).

While there is no way that an El Niño and its effects

may be stopped, efforts in research and prediction

modelling may, however, help improve the capacity to

understand the phenomenon and the reliability of

forecasts about the onset of the El Niño, thereby helping

to prepare for it. In the Philippines, PAGASA will play a big

role in providing more reliable SCFs to guide various

stakeholders, more specifically the farm sector. It is

expected that from case studies to be done in different

regions in the country, PAGASA will be in a position to

better match forecasts with decisionmakers’ needs,

thereby closing the gap between actual and potential

values of SCF.

Finally, during the forum, the difference between

weather and climate was explained. Weather is a specific

condition of the atmosphere at a particular time and

space while climate is the average weather for a longer

period of time. The various elements or factors affecting

the weather and/or climate as well as the different climate

types in the various regions of the Philippines were also

presented and discussed. As a supplement, the PAGASA

also gave an outlook of the climate in the Philippines for

the next three months. (SCF Project Updates June 2005)

Lear

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bas

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Philippine weather and climate 101

6 SCF Folio

In our daily lives, the weather plays a particular

role. Whether we commute to our work stations

or work in the farm or do our daily chores as

homebodies, knowing what the weather outlook will

be is useful for our respective purposes.

Beyond the knowledge of having the sun shining

brightly or having rains for the day, however, the average

citizen does not know much about the weather or

climate.

And for a country like the Philippines where

certain weather/climate conditions affect lives,

properties and sources of livelihood on an almost

regular basis, understanding more about the nature,

causes and manifestations of these conditions may, in

a way, help be better prepared for them when they

come. This writeup is thus a starting point for learning

a little more about them.

Weather is the specific condition of the atmosphere

at a particular place and time. It can change from hour

to hour and from one season to another. Climate, on

the other hand, is the average weather of a particular

area that prevails over a particular period of, for instance,

over a month, one season, a year, or even several years.

Basics on Philippine climatology

Weather/climate is measured and characterized by

a number of elements but the three most important

are temperature, humidity and rainfall. Temperature

refers to the degree of hotness and coldness of the

atmosphere. Humidity is the moisture content of the

atmosphere while rainfall is the amount of precipitation

in liquid form falling over a specific area. Its distribution

varies across regions in the country depending on the

direction of moisture-bearing winds and the presence

of mountain systems.

The climate of the Philipines is influenced by the

complex interaction of various factors such as the

country’s geography and topography; principal air

streams; ocean currents; linear systems such as the

intertropical convergence zone; and tropical cyclones

which are classified as tropical depression, tropical

storm or typhoon, depending on their intensities (to

be presented in a separate issue of the Economic Issue

of the Day).

Among these factors, it is perhaps useful to

understand the movements of air streams. Rainfall is

generally a result of the movement and interaction of

cold and warm air masses in a particular period. The

Southwest Monsoon or locally known as Habagat, for

instance, affects the country from May to September

and occurs when warm moist air flows over the country

from the southwest direction. This brings in rains to the

western portion of the country. The Northeast Monsoon

or Amihan, meanwhile, affects the eastern portions of

the country from October to late March. Cold and dry

air mass from Siberia gathers moisture as it travels over

the Pacific and brings widespread cloudiness with rains

and showers upon reaching the eastern parts of the

Philippines. In addition, a cold front affects the country

from November to February and brings increased

cloudiness and heavy rains. This occurs when a mass of

moving cold air overtakes a mass of moving warm air

resulting in towering cloud formations that bring heavy

rains and thunderstorms.

On the whole, the climate of the Philippines (using

temperature and rainfall as the gauge) can be divided

into two major seasons: the rainy season, which sets in

by June and ends around November, and the dry

season, which sets in by December and ends in May.

Figure 1. Climate map of the Philippines basedon the modified Coronas classification

7

The dry season is also subdivided into the cool dry season

from December to February and the hot dry season from

March to May.

The entire country, however, may be characterized

by four types or classifications (Figure 1) of climate based

on the distribution of rainfall.

Type I—has two pronounced seasons: dry from

November to April and wet throughout the rest of the

year. The western parts of Luzon, Mindoro, Negros, and

Palawan experience this climate. These areas are shielded

by mountain ranges but are open to rains brought in by

Habagat and tropical cyclones.

Type II—characterized by the absence of a dry

season but with a very pronounced maximum rain period

from November to January. Regions with this climate are

along or very near the eastern coast (Catanduanes,

Sorsogon, eastern part of Albay, eastern and northern

parts of Camarines Norte and Sur, eastern part of Samar,

and large portions of Eastern Mindanao).

Type III—seasons are not very pronounced but are

relatively dry from November to April and wet during the

rest of the year. Areas under this type include the western

part of Cagayan, Isabela, parts of Northern Mindanao, and

most of Eastern Palawan. These areas are partly sheltered

from tradewinds but are open to Habagat and are

frequented by tropical cyclones.

Type IV—characterized by a more or less even

distribution of rainfall throughout the year. Areas with this

climate include Batanes, Northeastern Luzon, Southwest

Camarines Norte, west of Camarines Sur, Albay, Northern

Cebu, Bohol, and most of Central, Eastern, and Southern

Mindanao. (Economic Issue of the Day Vol. V, No. 2-July 2005)

Typhoons, tropical storms, tropical depressions, and

other weather disturbances are usual occurrences

in the Philippines. According to the Philippine

Atmospheric, Geophysical and Astronomical Services

Administration (PAGASA), an average of 19–20 tropical

cyclones visit the country every year, some of which may

cause deaths to many people and millions of pesos in

damaged property.

But how strong can tropical cyclones be and how

much damage can they cause? What is their pattern of

occurrence?

These questions are important to consider especially

for a typhoon-frequented country like the Philippines so

Tropical cyclone signals: bracingfor the wind

that one can be better prepared to deal with them and

thereupon prevent possible damages and loss of lives.

In a nutshell, the various terms listed herein are

actually interchangeable, depending on the intensity of

the weather disturbance and location. By international

agreement, tropical cyclone is the general term for all

storm circulations that originate over tropical waters. It is

called hurricane over the Atlantic Ocean, cyclone over the

Indian Ocean and typhoon over the Pacific Ocean.

In meteorology, a tropical cyclone is a low-pressure

system wherein the central region is warmer than the

surrounding atmosphere. Its strongest winds are

concentrated close to its center. From pictures taken

above the earth, a tropical cyclone resembles a huge

whirlpool of white clouds. It has a disc-like shape with a

vertical scale of tens of kilometers against horizontal

dimensions of hundreds of kilometers.

Types of tropical cyclonesTropical cyclones are categorized into three types:

Tropical depression – a tropical cyclone with

maximum surface winds ranging from 37 to 62

kilometers per hour (kph) (20 to 33 knots).

Tropical storm – a tropical cyclone with maximum

In meteorology, a tropical cyclone is a low-pressure systemwherein the central region is warmer than the surroundingatmosphere. Its strongest winds are concentrated close to itscenter. From pictures taken above the earth, a tropical cycloneresembles a huge whirlpool of white clouds.

Tropical cyclone is the general term for all storm circulationsthat originate over tropical waters. It is called hurricane overthe Atlantic Ocean, cyclone over the Indian Ocean, and typhoonover the Pacific Ocean.

8 SCF Folio

Signal No. Wind Speed and Time Impact of Winds of Occurrence

1 30–60 kph within the next Twigs and branches may be broken; some banana plants may be tilted;36 hours houses of very light material may be unroofed; flowering rice crop may be

damaged; in general, very little or no damage may be experienced by thecommunity.

2 60–100 kph within the next Some coconut trees may be tilted and broken; few big trees may be24 hours uprooted and many banana plants may be downed; rice and corn may be

adversely damaged; many nipa and cogon houses may be partially or totallyunroofed and old galvanized iron roofings may be peeled off; in general,winds may bring light to moderate damage to the community.

3 100–185 kph within the next Many coconut trees may be broken or destroyed; almost all banana plants18 hours may be downed while many trees may be uprooted; rice and corn crops

may suffer heavy losses; majority of nipa and cogon houses may be unroofedor destroyed and there may be considerable damage to structures of light tomedium construction; widespread disruption of electrical power andcommunication services may also occur; in general, moderate to heavydamage may be expected, practically in the agricultural and industrialsectors.

4 Greater than 185 kph within Coconut, rice, and corn plantations may suffer extensive damage and manythe next 12 hours large trees may be uprooted; most residential and institutional buildings of

mixed construction may also be severely damaged; electrical powerdistribution and communication services may be disrupted; in general,damage to affected communities can be very heavy.

surface winds in the range of 63 to 117 kph (34 to

63 knots).

Typhoon/hurricane – a tropical cyclone with

maximum surface winds of 119 to 239 kph (64 to 129

knots).

A super typhoon is a term used by the U.S. Joint

Typhoon Warning Center in Guam for typhoons that

reach maximum surface winds of at least 242 kph (130

knots).

The areas affected by these tropical cyclones, as

indicated by their respective term, are those in the

tropics, the region of the earth centered on the equator

and sandwiched between the Tropic of Cancer in the

northern hemisphere and the Tropic of Capricorn in the

southern hemisphere. Countries that are situated in

these areas are found in Africa, Asia, South and Central

America, the Caribbean, and those in the Indian and

Pacific Oceans. Most of these are developing countries

such as Kenya, Mozambique, the Philippines, Indonesia,

Malaysia, Egypt, Mexico, Ecuador, Brazil, Saudi Arabia,

and the Bahamas, among others. It also includes

southern China, Australia, and Chile.

Philippine storm warning signalsFor the Philippines, PAGASA devised four warning

signals that describe the meteorological conditions and

impact of the winds of an approaching tropical cyclone

as shown above.

Seasons and path of potential destructionAn average of 100 tropical cyclones are formed every

year around the world. Of this total, the bulk is formed

in one region or area—the western north Pacific Ocean.

An average of 30 cyclones every year are formed here.

They usually move westward approaching the

Philippines.

Once in the Philippine area of responsibility (PAR),

these tropical cyclones, now called typhoons, usually

move northwest; in the process, leaving destruction to

the provinces in northern Luzon. The typhoons then

exit the PAR and head toward Taiwan, southern China

or Japan.

What has been the pattern of frequency that

tropical cyclones or typhoons enter the Philippines?

When and where can they bring potential destruction?

PAGASA estimates that the monthly average

frequencies of tropical cyclones that enter the PAR from

9

January to April are 0.4, 0.3, 0.3, and 0.5, respectively. This

suggests that these months have the slimmest chance of

tropical cyclone activities in the Philippines throughout

the year. Starting May and June, however, an average of

one tropical cyclone for each month occurs and then

jumps to about three each for the months of July, August,

and September. By October and November, an estimate

of about two per month occurs, signaling the start of

descent of the cyclone activities in the Philippines, with

just about one occurrence for the month of December.

Although there is a recession in the number of

tropical cyclone occurrences in the months of October

to December, it is to be noted nevertheless that most of

the destructive cyclones/typhoons that have taken place

were recorded during this period. This is due to the fact

that the paths of these disturbances have, as seen in the

illustrations, a much wider range of possible tracks over

Luzon and Visayas during this period. At the same time,

there is also a high probability that these cyclones tend

to cross the archipelago, creating much damage to the

populace.

Tropical cyclone average tracks

Is there any change in the cyclones/typhoons' path

when seasonal phenomena like El Niño and La Niña take

place? At the moment, the weather bureau is in the

process of further tracking the average paths of tropical

cyclones and determining if there is a difference in their

usual path during the periods of El Niño and La Niña.

(Economic Issue of the Day Vol. V, Nos. 3&4-December 2005)

Referenceshttp://hurricanewaves.org

http://www.hko.gov.hk/informtc/nature.htm

http://www.ndcc.gov.ph

http://www.pagasa.dost.gov.ph

http://www.typhoon2000.ph/info.htm

http://www.wikipedia.org

Lucero, A. Warning system for tropical cyclones in the Philippines.

Powerpoint presentation. PAGASA.

Verceles, E. Climate concepts, climate of the Philippines, and

ENSO. Powerpoint presentation. PAGASA.

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10 SCF Folio

Ask anyone about what he/she thinks El Niño

is and the usual answers would be—a

severe drought or a long hot summer or a

dry spell followed by heavy rains. While all of these are

indeed associated with El Niño, they are, however,

merely the effects or impacts of this phenomenon. What

it really is lies somewhere in the Pacific.

What it basically is…El Niño is a condition that takes place in the Central and

Eastern Equatorial Pacific (CEEP) Ocean, when the sea

surface temperature (SST) becomes unusually warmer

than the normal temperature. This condition can prevail

for more than a year, thus adversely affecting the

economy in both local and global scale.

The sea or ocean surface usually registers a certain

normal temperature. Any departure from this normal

level is considered an anomaly. If the temperature rises

from normal, it is called a positive anomaly. This

condition is associated with El Niño. Conversely, if the

temperature drops from normal, it is called a negative

anomaly and is more popularly related to La Niña. Either

way, any change in the temperature, just like in the

human body, indicates that something unusual is taking

place and something must be done to address its

possible consequences.

Feeling the heatAlthough the physical occurrence of El Niño (and La

Niña) takes place in the Pacific, its effects are felt in other

parts of the world, similar to a ripple effect in a big pond.

This is due to the so-called southern oscillation (SO)

which refers to a “see-saw” in atmospheric pressure

between the western (represented by Darwin in

Australia) and eastern Pacific (represented by the island

of Tahiti).

These variations in the atmosphere in the Pacific,

combined with changes in the SST as discussed earlier,

are responsible for bringing about abnormal climatic

events. The interaction between sea and atmosphere

variations refers to the El Niño Southern Oscillation

(ENSO) and potentially influences extreme climate

events in the world (El Niño refers to the ocean or sea

component of ENSO while the SO refers to the

atmospheric component).

El Niño and La Niña are basically flip sides (warm

and cold phases, respectively) of the ENSO and as such,

do not take place simultaneously in one area/region.

However, in terms of

teleconnection or the links of

climate over great distances, if

the eastern part of the Pacific

experiences an unusual ocean

warming and low atmospheric

pressure (characteristics of the

warm phase or El Niño), then the

western part of the Pacific will

likely experience the opposite

effect, characterized by cooler

ocean and high atmospheric

pressure.

The implicationsThe effects of ENSO on climate

variability all over the globe

Understanding the ENSO phenomenonand its implications

El NiñoEl Niño (EN) is Spanish for “The Christ Child,” a name given by Peruvian fishermen to thephenomenon that they usually observed during the period near Christmas time when the water inthe Pacific Ocean off the coast of Peru would become unusually warm. Every two to nine years, forunexplained reason, trade winds in the Pacific region, which drive the surface warm waters of thetropics to the west Pacific, weaken. As a result, these warm waters of the western Pacific drifteastward, resulting in the occurrence of El Niño in the eastern part of the Pacific.

Southern oscillationSouthern oscilllation (SO) is an east-west balancing movement of air masses between the easternPacific and the Indo-Australian areas. It is measured as the difference between the overlyingatmospheric pressures at Darwin (northern Australia) and Tahiti (south-central Pacific). This termwas coined by the British scientist named Sir Gilbert Walker during the 1920s when he observedthat when the atmospheric pressure rises in the east, the waters of the eastern Pacific are unusuallycold, and when the atmospheric pressure drops in the eastern Pacific, the waters in this part of thePacific are unusually warm. The opposite effects are observed in the western Pacific.

11

inevitably have impacts on the various ecological and

agricultural production systems around the world.

In the Philippines, for instance, an ENSO event can

trigger extreme climatic effects such as droughts, strong

winds, floods and flashfloods, increasing or decreasing

temperatures and many more. The impacts on Philippine

climate are initially felt three or five months after the

development of an ENSO phenomenon in the tropical

Pacific. If the ocean-atmosphere interaction or ENSO is

stronger than the usual, however, the Philippines may feel

the weather abnormalities much earlier.

One of the abnormalities brought about by El Niño,

the warm phase of ENSO, is a generally drier weather

condition, the effect of which is greatly felt during the

dry season. From May to September or during the

country’s rainy season due to the southwest monsoon,

though, rains may still be expected or felt even with an El

Niño occurring in the Pacific.

Once the southwest monsoon rainy season ends by

late September or early October, rains may be much lesser

than normal during an El Niño event. This is critical

especially for rice farmers in Central Luzon who

traditionally prepare for their second cropping season

before the end of the year. If there is indeed an El Niño

event, this implies, among others, that enough water

should have been stored in the water reservoirs so as to

provide irrigation for the crop upon the onset of the dry

season (January to April) when hardly any or no rain might

be expected.

Finally, once the El Niño/La Niña signs start to brew,

there is nothing that can stop them from occurring. It is

nonetheless useful to understand the processes on how

they evolve to be able to be better prepared for them.

(Economic Issue of the Day Vol. V, No. 1-July 2005)

Knowing when El Niño/La Niña is here

In a previous Economic Issue of the Day (Vol. V, No. 1,

July 2005), a basic understanding was presented on

what the El Niño Southern Oscillation (ENSO)

phenomenon is all about, its characteristics and two

phases, and its implications.

ENSO is a phenomenon that takes place in the

central and eastern equatorial Pacific largely

characterized by an interaction between the ocean and

the atmosphere and their combined effect on climate. The

mutual interaction between the ocean and the

atmosphere is a critical aspect of the ENSO phenomenon.

Major ENSO indicators are the sea surface

temperature anomaly (SSTA) and the Southern Oscillation

Index (SOI).

SSTA refers to the departure or difference from the

normal value in the sea or ocean surface temperature. El

Niño events are characterized by positive values (greater

than zero) within a defined warm temperature threshold

while La Niña events are characterized by negative values

(less than zero) within a defined cold temperature

threshold.

The SOI, on the other hand, measures the differences

or fluctuations in air or atmospheric pressure that occur

between the western and eastern tropical Pacific during

El Niño and La Niña episodes. It is calculated on the basis

of the differences in air pressure anomaly between Darwin

in Australia (western Pacific) and Tahiti in French Polynesia

(eastern Pacific). These two locations/stations are used in

view of their having long data records.

Albeit the seeming straightforward description of

these ENSO-related events as noted in the above, it is to

be emphasized that through the years, it has not been

easy to come up with a commonly agreed definition and

identification of these ENSO-related events, i.e., El Niño or

La Niña. The reason is due to the use of more than one

standard index as basis in monitoring ENSO phenomena

and the employ of different methods in determining the

magnitude or value of such index and threshold as well

as the length of time that such magnitude persists. In line

with this, the Philippines adopted the World

Meteorological Organization (WMO) Regional Association

IV Consensus Index and Definitions of El Niño and La Niña.

Region IV includes the North and Central America

member nations of the WMO, whose operational

definitions in use of the two ENSO phases are the

following:

El Niño: A phenomenon in the equatorial Pacific

Ocean characterized by a positive SST departure from

12 SCF Folio

normal (for the 1971–2000 base period) in the Niño 3.4

region, greater than or equal in magnitude to 0.5

degrees C, and averaged over three consecutive

months. Defined when the threshold or value is met

for a minimum of five consecutive overlapping seasons.

La Niña: A phenomenon in the equatorial Pacific

Ocean characterized by a negative SST departure from

normal (for the 1971–2000 base period) in the Niño 3.4

region greater than or equal in magnitude to 0.5

degrees C, and averaged over three consecutive

months. Defined when the threshold or value is met

for a minimum of five consecutive overlapping seasons.

When is El Niño/La Niña occurring?Because ENSO-related phenomena have been a major

source of interannual climate variability around the

globe, especially in recent years, it is important to be

able to determine or identify when an El Niño/La Niña

is occurring or will take place.

As noted earlier, monitoring the occurrence of an

El Niño/La Niña involves the use of two most common

indicators, the SSTA and the SOI, with the SSTA based

on the magnitude of departures/anomalies in the sea

surface temperature in the Niño regions (see box), and

the SOI based on the difference in air pressure between

Tahiti and Darwin.

PAGASA: monitoring El Niño/La Niña eventsin the PhilippinesIn the Philippines, how is El Niño/La Niña identified/

monitored? The country’s national meteorological

agency, the Philippine Atmospheric, Geophysical and

Astronomical Services Administration (PAGASA), defines

and identifies these phenomena on the basis of the

abovementioned indicators which are also being used

by the National Oceanic and Atmospheric

Administration-National Centers for Environmental

Prediction (NOAA-NCEP) of the United States.

Through the years and based on this definition

and data from the NOAA, PAGASA has monitored the

occurrence of El Niño/La Niña by category, as follows:

a) weak El Niño/La Niña – magnitude of +0.5 to +1.0

°C (or -0.5 to -1.0 °C)

b) moderate El Niño/La Niña – magnitude of +1.0 to

+1.5 °C (or -1.0 to -1.5 °C)

c) strong El Niño/La Niña – magnitude of more than

+1.5 °C (or less than -1.5 °C)

Table 1 shows the years when these events and

their categories have taken place in the last decade. It

is to be noted that no two ENSO events are alike in terms

of climate impacts. Accordingly, PAGASA gives out the

appropriate advisories to the various sectors and

decisionmakers concerned on the occurrence/presence

of El Niño/La Niña for their

corresponding action.

(Economic Issue of the Day Vol.

VII, No. 1-January 2007)

ReferencesColumbia University. 2006. When

can we say El Niño will occur

[online]. Available from the

World Wide Web:(http://

www.columbia.edu/~za2121/

Peru-ENSO/Peru-ENSO/Web-

p a g e s / E l % 2 0 N i n o /

W h e n % 2 0 w i l l % 2 0 i t % 2 0

occur.html).

International Research Institute

for Climate and Society. 2006.

Defining ENSO [online]. Available

from the World Wide Web:(http:/

/iri.columbia.edu/climate/ENSO/

background/pastevent.html).

El Niño regions: Although El Niño is a generalized event in the equatorial Pacific, there are differentregions which show different characteristics and different moments in the process. Past studiesshow that the Philippine climate responds more significantly to temperature changes in the NIÑO3.4 region.

Source: International Research Institute for Climate and Society

Box. NIÑO regions

13

National Oceanic and Atmospheric Administration (NOAA). 2006.

ENSO cycle: recent evolution, current status, and predictions

[online]. Climate Prediction Center, National Centers for

Environmental Prediction. Available from the World Wide

We b : ( h t t p : / / w w w. c p c. n c e p. n o a a . g ov / p r od u c t s /

analysis_monitoring/lanina/.

Philippine Institute for Development Studies/Australian Centre

for International Agricultural Research. 2006. SCF Project

Updates Vol. II Nos. 1&2, 2006. Makati City: PIDS.

Trenberth, K.E. 1997. The definition of El Niño. Bulletin of the

American Meteorological Society 78:2771-2777.

Reac

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Reaching out to local populationon seasonal climate information

Part of the information dissemination activity of

the project funded by the Australian Centre for

International Agricultural Research (ACIAR) on

seasonal climate forecasts (SCFs) was a seminar-workshop

held on June 30, 2005 at the Leyte State University (LSU)

in Baybay, Leyte. In coordination with the Philippine

Atmospheric, Geophysical and Astronomical Services

Administration (PAGASA) and the Philippine Institute for

Development Studies (PIDS), the LSU hosted the seminar-

workshop to inform the local people, particularly

members of the academe in the region, agricultural

officers, and other local officials, about the project and the

value of SCFs in their decisionmaking processes in relation

to crop production, especially in addressing the impact

of El Niño and other extreme climate events. The seminar

also aimed to strengthen the coordination and

cooperation between PAGASA and the agricultural sector

in order for the latter to be better served through proper

application of weather and climate information.

Similar to what had been presented in the first

Pulong Saliksikan held at the PIDS last April, resource

persons from PAGASA presented basic climatology

concepts and information such as Philippine climatology,

basic El Niño Southern Oscillation (ENSO) concepts,

tropical cyclone warning system as well as a climate

outlook for the province of Leyte. After the PAGASA

lectures, responses from the local government unit (LGU)

representatives regarding their agriculture response

strategies to extreme climate events such as El Niño and

La Niña were presented. The LGU representatives

discussed the various measures they adopt under these

circumstances, as divided into the (a) predisaster phase,

(b) disaster phase, and (c) postdisaster phase.

A lecture on PAGASA’s climate information products

and services offered then followed, after which the

participants were divided into two groups and were asked

their assessment of such products and services in terms

of usefulness, timeliness, ease of understanding, and

comprehensiveness. Suggestions on how said products

may be further improved were likewise solicited from the

participants. During this portion, exercises such as the

plotting of a tropical cyclone track and interpretation of

certain/selected PAGASA climate information products were

also given to the participants. (SCF Project Updates, June 2005)

Period Event Category

May 1994 – April 1995 El Niño weak to moderateOctober 1995 – April 1996 La Niña weakJune 1997 – May 1998 El Niño strongAugust 1998 – July 2000 La Niña moderate to strongNovember 2000 – March 2001 La Niña moderateJune 2002 – April 2003 El Niño weak to moderateAugust 2004 – March 2005 El Niño weak

Source of data: Climate Prediction Center – National Oceanic and AtmosphericAdministration (CPC-NOAA), 2006

Table 1. El Niño and La Niña episodes during the past decade

The seminar aimed to inform the local people, particularlymembers of the academe in the region, agricultural officers,and other local officials, about the project and the value of SCFsin their decisionmaking processes in relation to cropproduction, especially in addressing the impact of El Niño andother extreme climate events.

14 SCF Folio

No one can tell for sure what the next season

will be like. Even when a climate in a

particular place or region is generally

predictable, there is a varying difference in the yearly

duration, intensity and timing of rainy and dry periods.

Thus, it is important to know and understand SCF and

how it may benefit the population.

Global changes in weather and climate are largely

brought about by the cycle of atmospheric and pattern

changes in the Pacific Ocean called the El Niño Southern

Oscillation (ENSO). This usually occurs in December;

hence, the term “El Niño” for the “Christ Child,” and

usually has a cycle duration of four years. The ENSO is a

complex process but basically it involves the unusual

warming and cooling of the ocean’s surface sea

temperature. The El Niño is the warm phase of the ENSO

while La Niña is the cool phase. The changes in

temperature that these phases bring affect weather and

climate in many parts of the world, even those that are

far from the Pacific Ocean.

With advances in science and technology, people’s

knowledge on seasonal climate changes such as ENSO

has grown considerably. A seasonal climate forecast is

an estimate of how rainfall or temperature in a coming

season is likely to be different from the prevailing

average climate. SCFs use dynamical (based on laws of

physics) or statistical (based on historical patterns)

methods to predict the climate. They usually forecast

“above median” or “below median” rainfall. Seasonal

climate forecasting is usually done three months to a

year in advance or longer.

Why it is important to understand SCFsWeather and climate are significant forces in people’s

lives. Important and not-so-important decisions are

made depending on the weather or ensuing climate.

Planning for social and economic benefits would be

greatly enhanced by being able to forecast seasonal

conditions in the months ahead. Conversely, it can mean

human lives and incomes lost when changes in climate

are not anticipated. Thus, knowing and understanding

SCFs can save lives, lessen the costs and present

Making the most out of seasonal climateforecasts (SCFs)

opportunities to various sectors for better planning and

decisionmaking.

The agriculture sector would naturally be the

major beneficiary of SCF. For the Philippines, it is one of

the country’s top industries which accounted for about

18 percent of the total gross domestic product (GDP)

and whose labor force reached 11.38 million in 2004.

Since agriculture is vulnerable to climate variability,

farmers may benefit from SCFs by being able to choose

what crops to plant and when to plant them. While the

risks may not be completely eliminated, information

from SCFs can lessen the costs that would have been

incurred and may even enable farmers to make

substantial yields and higher incomes.

Other end users of SCFs include the energy

sector—suppliers of electricity and natural gas which

benefit from forecasts to help them plan energy usage

and make operations run efficiently. The tourism

industry is likewise a logical beneficiary as travel agents

and event organizers are able to put together vacation

packages and schedule occasions at appropriate times.

Retailers and other businesses can also benefit from

valuable climate forecasts as they will be able to time

their procurement of stocks that may be in demand

once the weather changes. National and local

governments can strengthen their civil defense

programs by being able to stock up on supplies and

train for emergency disaster operations and drought

relief activities.

Limitations of SCFs: bridging the gapCertainly, SCF is still an imperfect science even with the

advancement of technology and research. The accuracy

of the forecasts is the primary concern which may

fluctuate over a period of time and with successive

forecasts. It is not known what percentage of farmers

in the Philippines rely on SCFs in their decisionmaking.

It is said that the use of SCFs in the country and in

Australia is “hampered by the lack of robust means of

showing the economic value of SCF-specific decisions.”

Some of the major concerns regarding SCFs are

their accuracy and timeliness, the difficulties

15

encountered in applying them to farm management

decisions, and the apparent lack of evidence of their

economic value to reduce the risks associated with their

adoption. In view of this, the application of SCFs in

decisionmaking has been more difficult than initially

thought.

Ground level: reaching out to end users for SCFinformationTo ensure that the SCFs are rendered useful to their

beneficiaries, it is important that they reach them in a

timely fashion and that they contain the needed

information for the decisionmakers. Thus, information like

when the rains will come, how frequently they will occur,

and how much rainfall is to be expected must be delivered

in the clearest, simplest, and most accurate manner. This

may be achieved by conducting frequent information

blitzes to the farmers on the basics of weather, climate

and seasonal forecasts, issuing frequent weather and

climate analyses in popular mass media, and making

information readily available and accessible to the farmers

and other end users.

A study on the usage of SCFs in Zimbabwe found

that farmers complained of receiving climate forecasts

after they have made planting decisions. They also did

not understand nor trusted the forecasts. Thus, any

seasonal climate forecast communications system that

will be developed by any country should involve the

active participation of farmers and other stakeholders. In

so doing, SCFs would have greater relevance, credibility

and legitimacy. (SCF Project Updates, December 2005)

Sources

SCF Project Updates Vol. 1, June 2005.

“Valuing seasonal climate forecasts” by Dr. John Mullen.

www.nscb.gov.ph.

w w w . k s g . h a r v a r d . e d u / s e d / d o c s / k 4 d e v /

lemos_k4dev_031002.pp.

www.census.gov.ph/data.

http://iri.columbia.edu/outreach/meeting/MediaWS2001/

Glossary.html.

http://www.bas.gov.ph/agri_dev.php.

To ensure that the SCFs are rendered useful to theirbeneficiaries, it is important that they reach them in a timelyfashion and that they contain the needed information for thedecisionmakers. Thus, information like when the rains willcome, how frequently they will occur, and how much rainfallis to be expected must be delivered in the clearest, simplest,and most accurate manner.

Tale of two surveys: feedback to PAGASA’sclimate information products and services

O n June 30 and December 1, 2005, seminar-

workshops on “Toward bridging the gap between

seasonal climate forecasts and decisionmakers in

agriculture” were held in Baybay, Leyte and Malaybalay,

Bukidnon, respectively. These seminars were part of the

dissemination program of the four-year project with the

above title sponsored by the Australian Centre for

International Agricultural Research (ACIAR) and were

jointly conducted by the Philippine project implementing

institutions, namely, the Philippine Atmospheric,

Geophysical and Astronomical Services Administration

(PAGASA), the Philippine Institute for Development

Studies (PIDS), and the Leyte State University (LSU). The

purpose of these seminar-workshops was to introduce the

project to various local government units, members of

academe, and farmer groups in terms of its objectives,

plan of activities, expected outputs, and possible utility in

the decisionmaking and risk management of

stakeholders/decisionmakers in agriculture. Some basic

concepts relating to the project like the El Niño Southern

Oscillation phenomenon, tropical cyclones, climate

outlook and local forecasts, and other useful

meteorological terms and information were also

explained. Participants in these two seminars were from

LGUs (mostly municipal agriculturists), the academe, and

a few groups representing farmers.

To help PAGASA in its goal of improving its service

delivery, especially in terms of its climate information

products and services, to the agriculture sector and other

related stakeholders, the participants were asked to

16 SCF Folio

answer a survey questionnaire during the seminars. The

questionnaire had two parts. The first referred to the

participants’ profile which identified the respondents’

designations and sector/category representation. The

second referred to the participants’ feedback which had

11 questions on what the respondents thought about

PAGASA’s products and services. Aside from directly

offering information to PAGASA, the responses to the

questionnaire may also provide some insights to the

project team members on how decisionmakers in

agriculture source and make use of information

regarding climate, including seasonal forecasts.

FindingsMajority of the respondents were municipal

agriculturists and members of the academe with a few

members of farmers’ groups. All of them considered

weather/climate as a factor in planning and

decisionmaking in their work/source of livelihood, with

the majority claiming it is a critical factor.

Radio/tv were cited as the sources of information

about weather/climate used by the majority of the

respondents, with PAGASA stations coming in second

and the rest a split among local practices/beliefs,

broadsheets/tabloids, advisories from head offices and

associates and extension workers.

In terms of awareness of PAGASA’s products and

services, majority of the respondents in Leyte were

aware while less than half of the respondents in

Bukidnon were. Those who were aware and went on to

rate these products and services gave generally good

assessments.

Suggestions given by the respondents on how to

improve PAGASA’s products and services were basically

the same as gleaned from the two surveys. Essentially,

what the respondents want is for PAGASA to have a

stronger presence in their municipalities and establish

a stronger linkage with them. There was also a clamor

for publications that are easier to understand, preferably

in the vernacular, and more information and education

campaign (IEC) activities, trainings and seminars from

PAGASA. Establishment of agromet and weather

stations in their local government units (LGUs) was also

shared by many of the respondents as well as the

improvement of PAGASA’s facilities. Perhaps owing to

the difference in the sector they belong to, the

members of the academe in Leyte have access to the

internet and thus wanted weather/climate data

available online.

The respondents in Leyte recommended a closer

link between PAGASA and LGUs in order that the LGUs

themselves could request the kind of information that

are more suited to their constituents and localities. They

also cited the need for more site-specific data that the

local weather stations could regularly disseminate to

the community. Those in Bukidnon, on the other hand,

basically wanted to have agromet stations and rain

collector systems facilities in addition to more related

publications and trainings from PAGASA.

Implications and recommendationsIt is clear that PAGASA needs to do more to reach the

people who use its products and services to make

decisions that affect their work, especially since these

people are in the rural areas and far from information-

rich metropolises.

In order to achieve this, the weather bureau needs

to have more partners in nongovernment organizations

(NGOs), LGUs, the academic research community and

individual experts who can help disseminate and

explain weather/climate information. The more

vigorous partnership with these groups and individuals

would help establish better communication among the

stakeholders and help make the receivers of

information inform PAGASA of the data they need in

their localities.

More effort must also be made in making the

information more understandable and more accessible

to the clients. This would indeed be challenging since

scientific data are difficult to translate to local dialects

and so it is necessary to have more seminars and

lectures by PAGASA particularly in the regions.

Lastly, the mass media should be tapped not just

to report weather forecasts that are usually steeped in

weather jargon but also to explain basic concepts in

order to reach more people. (SCF Project Updates,

December 2005)

PAGASA needs to do more to reach the people who use its productsand services to make decisions that affect their work, especiallysince these people are in the rural areas and far from information-rich metropolises...More effort must also be made in making theinformation more understandable and more accessible to theclients.

17

Communicating through climate indicatorsigns

Bronya Alexanderand Peter Hayman

M otorists are often

exposed to

informative road

signs such as bushfire risk or

number of road accidents. So why

not have a sign to convey seasonal

climate information? Based on an

idea from the Birchip cropping

group in Victoria, along with

funding from the South Australian

Grains Industry Trust Fund and

other organizations, the South

Australia Research and

Development Institute (SARDI) has developed the Climate

Indicator signs. These large signs are used to convey a

range of different types of seasonal climate information

through the use of colored dials. They are placed in

paddocks on the road side so that farmers and

agriculturists can see the latest information and outlooks.

The signs have also been shown and discussed at

agricultural field days like the one shown in the photo

above.

There are six dials on the signs as seen in Figure 1

and described below.

1) Current growing season rainfall (GSR) decile –

this is calculated by comparing the amount of current

season rainfall with the long-term rainfall at the closest

meteorology station.

2) Forecast GSR deciles – the Department of

Agriculture and Food Western Australia (DAFWA) has

designed an experimental system for producing seasonal

climate forecasts. This system draws from indices based

on the El Niño Southern Oscillation (ENSO), and produces

five years that are considered to have performed similarly

to this year. The GSR from these five analogue years are

indicated via the five arrows on the dial.

3) Probability of exceeding median rainfall using

SOI – this shows two arrows. One represents the current

outlook from the Australian Government Bureau of

Meteorology for the chance of exceeding the median

rainfall over the following three months. The other arrow

is the outlook based on the SOI, provided by the

Queensland Department of Primary Industries.

4) Yield Prophet – this indicates the expected crop

yield from the Yield Prophet model developed by the

Birchip Cropping Group. Yield Prophet is the interface to

the crop simulation model called APSIM (Agricultural

Production Systems Simulator), which simulates crop

growth on a daily time step.

5) Nitrogen Calculator – this model, developed by

CSIRO (Australian Commonwealth Scientific and Research

Organisation), estimates the expected crop yield and the

corresponding nitrogen amounts recommended for the

soil. The expected yield from Nitrogen Calculator is

indicated on the dial.

6) Soil moisture guide – this shows the Yield

Prophet estimate for current stored soil moisture.

The SARDI Climate Applications Unit is updating the

signs in Morchard (upper north), Paskeville (Yorke

Melissa Rebbeck from SARDI presents the Climate Indicator Signs at a Yorke Peninsulafield day in South Australia in September 2006.

____________

The authors are Project Officer and Principal Scientist on ClimateApplications, respectively, both from the South Australia Researchand Development Institute (SARDI).

18 SCF Folio

Peninsula), and Tarlee (mid-north) in South Australia this

season. An electronic version of the signs has also been

created to help with communicating and distributing

the outputs via email. Some focus group sessions will

be held for farmers in these areas to discuss how to use

the information in the signs in decisionmaking. The

ACIAR project Bridging the gap between seasonal

climate forecasts and decisionmakers in agriculture has

been assessing how the information on the signs has

been used in decisionmaking and analyzing the relative

weight that should be given to measurements such as

the level of water stored in the soil or rainfall to date

versus predictions of the coming season based on

seasonal climate forecast. (SCF Project Updates, June 2007)

The Philippine Atmospheric, Geophysical and

Astronomical Service Administration (PAGASA),

the country’s national meteorological agency,

offers a range of climate information products on a

regular basis. It has around 10 advisories/information

products designed to inform and warn the populace

on upcoming climatic/weather conditions.

More significant to seasonal climate variability are

PAGASA’s seasonal climate forecasts (SCFs). SCF is one

of the tools which could help farmers and

decisionmakers better prepare for seasonal variability.

SCF applies probabilistic principles in projecting climatic

deviations. PAGASA uses seasonal predictions from both

national and international climate centers in coming up

with its own forecasts for a certain period. International

agencies tapped for the purpose are the National

Center for Environmental Prediction/Climate Prediction

Center (NCEP/CPC), International Research Institute for

Giving better seasonal climate forecastsand climate-related information

Figure 1. Electronic version of the Climate Indicator signs created to allow for easy distributionto farmers and consultants via email

19

Climate and Society (IRI), and the Australian Bureau of

Meteorology (ADPC and IRI 2005).

PAGASA’s Climate Monitoring and Prediction Center

(CLIMPC) comes up with monthly and seasonal rainfall

forecasts, and an annual seasonal climate forecast or

outlook. It uses the average values of five different

statistical techniques in forecasting rainfall. These include

the analogue method, Fourier analysis, Rainman, Principal

Component Analysis using sea surface temperature as

predictor, and climate predictability tool (CPT). Fourier

analysis uses long time data series; Rainman is a software

developed by the Australian Center for International

Agricultural Research (ACIAR) that uses ENSO indicators;

and CPT is a forecasting tool from the IRI.

Though the list of climate information products from

PAGASA is long, only El Niño/La Niña Advisory and Tropical

Cyclone Warning effectively reach majority of the farming

populace. From the study of Reyes et al. (2006), 94 percent

of farmers in Isabela were aware of ENSO forecasts while

85 percent received tropical cyclone warnings. The rest

of the information products got a low awareness rating

ranging from 2 percent to 19 percent. Usefulness and

reliability ratings were acceptable with only a few

expressing extreme discontent on the products (Table 1).

However, the figures still indicate that much has to be

done to properly disseminate climatic information,

improve its accuracy, and package the products in more

useful ways.

PAGASA has a wide range of meteorological

products, which could address a variety of climate-related

queries and informational needs among farmers. The

usefulness of these products would be in question if

access to them by target clienteles is impaired. An

advocacy to use wider communication channels would

address this concern. Television and radio programs have

proven to be effective means of bringing information to

farmers in the countryside. Print materials in layman form

and preferably written in the local dialect would also help

a lot in informing farmers and other agricultural

stakeholders.

Another related challenge is the updating and

review of national meteorological archives. Data from all

meteorological stations should be cleaned and

completed for ease in analysis and data processing. This

would also open up a lot of windows for the application

of new technologies and methodologies like the

application of simulation modeling in assessing the

impact of climatic variability.

A more complex issue to tackle is the upgrading of

PAGASA’a capacity to come up with localized seasonal

climate forecasts, aside from the national and/or regional

forecasts it currently gives. Many farmers had aired the

need for more area-specific advisories/information given

the archipelagic nature of the country and the diversity

of local climate/weather conditions. This is a more long-

term goal, which would require huge investments in

establishing local facilities and training necessary

manpower. A possible mechanism to make this more

attainable is to link with local governments and

communities for manpower and resources support.

PAGASA has been doing much to provide the best

meteorological service to the country’s population but

the challenge to do better is ever pressing. The bottom

line is that forecasts and other climate-related information

should reach the most number of users at the earliest

possible time. (SCF Project Updates, December 2007)

Table 1. Awareness, usefulness, and reliabilty of PAGASA climate information products

Product Awareness Usefulness* (%) Reliability** (%) (%) 1 2 3 4 5 1 2 3 4

Monthly weather situation and outlook 19 1 4 4 8 4 2 6 6 6Annual seasonal climate forecast 19 1 5 7 2 2 1 4 8 5El Niño/La Niña advisory 94 11 16 38 16 13 9 26 24 18Tropical cyclone warning 85 5 14 32 16 14 6 22 27 1810-day advisory 7 - 1 5 - 1 - 2 2 1Farm weather forecast 5 - 1 1 - 2 - 1 - 2Philippine Agroclimatic Review and Outlook 2 - - - - 2 - - - 2Press release on significant events 2 - - 1 - 1 - 1 - 1Phil agri-weather forecast 4 - - 2 - 1 - 1 1 1Climate impact assessment bulletin for agriculture 4 - - 2 - 1 - 1 1 1

*Usefulness rating: 1 - not useful, 2 - somewhat useful, 3 - useful, 4 - highly useful, 5 - vital**Reliability rating: 1 - unreliable, 2 - somewhat reliable, 3 - reliable, 4 - excellentSource: Reyes et al. 2006

20 SCF Folio

Bringing SCFs into the realmof agricultural decisionmaking in Isabela

For the ACIAR-funded project titled “Bridging

the gap between seasonal climate forecasts

(SCFs) and decisionmakers in agriculture,”

one of the ultimate challenges is on how to be able to

introduce the concept of SCFs and make information

relating to them understood by, available to, and used

by the key stakeholders in the agriculture sector in their

decisions and options for decisionmaking. The end

objective is to help improve productivity and overall

welfare in said sector.

Certainly, this was a challenge posed to the

Philippine project team composed of members from

the Philippine Atmospheric, Geophysical, and

Astronomical Services Administration (PAGASA), the

Philippine Institute for Development Studies (PIDS), and

the Philippine Rice Research Institute (PhilRice), during

the seminar-workshop that it conducted at the Cagayan

Valley Integrated Agricultural Research Center (CVIARC)

of the Department of Agriculture in Ilagan, province of

Isabela on 14 February 2008 to present some of the

highlights of the project and key findings of its study

surveys in the province.

A good start: full provincial leadership supportThe province of Isabela is one of the five study sites in

the Philippines chosen for the project to see where,

when, and why SCFs can be valuable—under what

circumstances—and how they may be incorporated as

a major factor in the process of decisionmaking among

the stakeholders in said areas. The other Philippine

study sites are in the key corn-producing areas of

Bukidnon, Cebu, and Leyte, and in major rice-growing

areas of Nueva Ecija. Counterpart case studies are also

being conducted in certain areas in New South Wales

(NSW) and Southern Australia in Australia, the other

country site of the project.

Isabela was selected not only because it is—and

has always been—one of the top producers of both rice

and corn in the country but also because it is a place

that has often been adversely affected by extreme

climate events in varying degree. This was stressed upon

by PAGASA Director Dr. Prisco Nilo, as he pointed out

that the SCF project is basically about the application

of SCFs by various decisionmakers in agriculture, both

at the national and local levels, as a potential means of

mitigating the adverse impacts of climate variability.

To which Isabela’s governor, the Honorable Maria

Gracia Cielo Padaca, in her keynote address during the

seminar-workshop, expressed elation because she

believes that making the various stakeholders in

agriculture in the province acquainted with the

concepts of SCFs and their possible application in their

decisions would provide them with more knowledge

and understanding on how they can turn the climate

adversities into opportunities for them to adopt better

farming systems through, say, crop diversification.

Governor Padaca acknowledged the importance

of the project’s objectives and activities in the province

of Isabela and urged the participants to lend

attentiveness to the presentations so that they may fully

understand the implications of the information and be

able to share them with their fellow Isabelinos who are

also challenged by seasonal climate variability. At the

same time, the governor expressed her wish that the

information to be conveyed by the project in general

are transmitted in a form that could easily be

understood, especially by the farmers.

Basic climatology concepts and their implicationsServing as a springboard for the presentation of the

SCFs for Region 2 which includes Isabela, the PAGASA

team of Ms. Daisy Ortega and Ms. Rosalina de Guzman

first explained some basic climatology concepts and

specifics affecting Region 2.

Region 2 is among the areas in the Philippines

classified as having Climate Type III, one of the four

climate typologies in the Philippines that are based on

the distribution of rainfall. Type III is characterized by

seasons that are not very pronounced but are relatively

dry from November to April and wet during the rest of

the year. For this climate type, while the area (Region 2,

in this case) is partly sheltered from tradewinds, it is

open to the southwest monsoon (habagat) which

brings in rains to the western portion of the country.

21

Very often, this leads to extreme climate occurrences

and subsequent calamities. As Governor Padaca earlier

noted, it is unfortunate that while their province has a

significant contribution to the food supply of the

Philippines, it is a frequent victim of climate calamities that

eventually result in damages in products and properties

worth billions of pesos. It is in this light that SCFs have to

be continuously improved as well as disseminated and

properly explained in terms of their impact, degree of

uncertainties, value, and applications.

Understanding SCFsSimply put, SCFs are predictions of the likelihood of the

total amount of rainfall to be above, near, or below the

normal range of rainfall received for a particular area in

the coming three to six months. SCFs differ from weather

forecasts in that they provide a longer lead time, say, three

months or sometimes even six months. The question,

however, is: since weather forecasts beyond seven days

tend to decrease in accuracy, how can SCFs provide useful

forecasts if they have a longer lead time period?

The reason is because over the years, certain skills in

predicting “anomalies” or “departures from the normal” in

the seasonal average of the weather have been

developed. These anomalies are usually associated with

the earth’s surface conditions that affect the climate like

the sea surface temperature. These are best manifested

in the phenomenon of the El Niño Southern Oscillation

(ENSO)—both in its warm (El Niño) and cold (La Niña)

phases—which causes much of the climate variability in

the world.

SCFs as probabilistic type of forecastsIn presenting the SCFs for Region 2, Ms. de Guzman

introduced the example of the “spinning wheel” which is

divided into three terciles representing three ranges of

values of rainfall. One tercile represents the values in the

lower range; another, the values in the middle range; and

the other, in the upper range. In short, each of the terciles

refers to values that are either: (a) lower than the normal

amount of rainfall; (b) near (or middle range) the normal

amount of rainfall; or (c) above the normal amount of

rainfall. Without any forecasting, the probability of any one

of these three terciles occurring will always be the same—

one out of three—every time one spins the wheel.

With forecasting (SCFs), however, based on

measuring and calculating the climate “anomalies”

mentioned earlier, one is able to predict the higher (or

lower) probability of either one of the terciles occurring

than when no forecasts were made.

Responding to El Niño/La Niña: Isabela’s strategies for calamity mitigation

The province of Isabela is no stranger to natural calamities. In view of its geographical location and topographic characteristics, it isregularly frequented by occurrences brought about by climate variability. In the past two or three decades, for instance, the province hasseen the onslaught of El Niño/La Niña occurrences.

Because of this, the provincial government, in particular, the Office of the Provincial Agriculturist (OPA), has learned not only tocope with the adverse effects of such extreme climate events after their occurrence but also to adopt agricultural preparation strategiesbefore and during the onset of the phenomena.

During the seminar-workshop sponsored by the project on “Bridging the gap between seasonal climate forecasts (SCFs) anddecisionmakers in agriculture” in Ilagan, Isabela on February 14, 2008, the province’s provincial corn and rice coordinators, Mr. FlorencioViesca Jr. and Mr. Romeo Cadauan, respectively, presented some of these strategies adopted by the OPA in response to El Niño/La Niñaevents before, during, and after said events’ onset.

Before the occurrence of said climate phenomena, the OPA conducts a series of information dissemination activities on their possibleand expected effects as well as the alternative crops that can be recommended for planting during this time. The dissemination activitiestake the form of meetings, briefings, radio, television and print features, and leaflets, among others. During the onslaught of the calamity,the OPA, together with all the local government units (LGUs) of the province, the Department of Agriculture’s Cagayan Valley IntegratedAgricultural Research Center and Bureau of Agricultural Statistics, and other partners monitor the extent of damage caused among therice and corn farms within the province and, if and where necessary, position available irrigation pumps in required locations.

After the calamity, meanwhile, a team of concerned agencies first validate the areas affected by computing for the amount of damagesand losses caused by the calamity. Thereafter, the Department of Agriculture and sometimes the LGUs, under counterpart agreements,implement the seed rehabilitation program by giving out free corn, vegetable, and legume seeds to farmers. In addition, the provincialgovernment has also recently advocated the idea of crop diversification by encouraging the affected farmers to plant legume and vegetableseeds, apart from corn, on at least a small portion of their farm areas.

22 SCF Folio

For instance, given the observed “anomalies” in the

surface conditions like the sea surface temperatures

associated with an El Niño, the probability of having the

“above normal” rainfall is 15 percent; the “near normal”

is 35 percent; and the “lower than normal” is 50 percent.

This means that the chance or probability for

experiencing “lower than normal” rainfall or a drier

episode is higher at 50 percent. However, precisely

because the probability is only 50 percent, there is also

equally a 50 percent likelihood that this condition of

getting “lower than normal” rainfall may not happen.

As such, there is still a degree of uncertainty attached

to the forecasts. Moreover, it should be noted that the

forecasts for a particular period may vary across

different locations depending on various other factors

like topography.

The ACIAR-sponsored SCF project: what ithopes to doFollowing the presentations on the concepts related to

SCFs, project team member from PAGASA, Dr. Flaviana

Hilario, presented the rationale and objectives of the

“Bridging the gap...” project as well as the activities that

it will undertake in order to address the project’s

objectives. Among the objectives are: (a) to improve the

capacity of PAGASA to develop and deliver SCFs for the

case study regions of the Philippines, including the

province of Isabela; (b) to estimate the potential

economic value of SCFs for farm and policy case studies

in the Philippines and Australia; (c) to identify the factors

that may lead to gaps, if any, in the actual utilization by

the stakeholders of the SCFs vis-à-vis the SCFs’ potential

economic value; and (d) to develop and implement

strategies to better match the forecasts (SCFs) with the

stakeholders’ needs.

Situation in the field: possible interventions tohelpHow useful are SCFs and climate-related information

to farmers and other agriculture decisionmakers in the

field? In order to have a better understanding of this,

the SCF project conducted a number of case studies in

selected sites. As mentioned earlier, certain locations in

Isabela were selected as sites for the conduct of surveys

and focus group discussions (FGDs) with farmers to get

their knowledge, perception, and attitude on climate

information and SCFs as well as to have more

information about their farm production systems,

points of decisionmaking, and coping mechanisms

during extreme climate events.

Dr. Celia Reyes, project team member from PIDS,

presented the highlights of the results of the surveys

and FGDs conducted among farmers in various sites in

Isabela as well as their policy implications. The results

indicate that despite of the many assistance programs

extended by the national and local governments in

Isabela, there is still much that need to be done. For one,

while the respondents all agree on the importance and

need for climate information and forecasts to help in

their preparations against possible adverse climate

effects, their actual adoption of risk management and

mitigation measures falls short of the potential benefits

that could be had because other related or

complementary mitigation measures were either not

present or inadequate. As gathered, the types and kinds

of assistance needed and preferred by the farmers are:

(a) better, and preferably localized, climate information;

(b) accessible credit; (c) crop insurance; and (d) special

assistance programs like irrigation and seeds provision.

(Details of these preferred mitigation tools by farmers

are discussed in the December 2007 issue of this SCF

Project Updates newsletter.)

A similar presentation that provides a comparative

look at the farmers’ perception, knowledge, and

attitudes on SCFs in the province of Nueva Ecija was

then given by Ms. Rowena Manalili of the PhilRice team

based on their farm and household surveys conducted

in rainfed rice farming communities in said province.

Disseminating SCFs: aiming for their better useBased on the field surveys, interviews, and the

questions/comments raised during the open forum in

this Isabela seminar-workshop, it became apparent that

getting farmers and other stakeholders in agriculture

to make good use of climate information and SCFs is

premised on how well the information is understood

and appreciated by them.

The process therefore basically entails that said

information are properly disseminated to them and

thereupon explained thoroughly through information

and education-sharing type of activities and methods.

This, according to Ms. Jennifer Liguton of the PIDS

project component team, is how the process of

disseminating the SCFs should begin. Ms. Liguton then

traced the present manner of disseminating SCFs as

originating from the country’s national meteorological

23

agency, PAGASA, and sent out to the various national

agencies and media, with the hope that such information

are brought by these entities across and down to the

various loci of potential users and decisionmakers in

agriculture.

Unfortunately, as gathered during the discussions,

not all the targeted users—basically the farmers—are able

to get the information in the manner that will be most

useful to them based on this present dissemination

scheme. In most cases, it becomes clear that not all

national agencies pass on the information immediately

and appropriately down to their regional, provincial, and

municipal offices and not all information channeled over

radio, television, and print media feature the implications

that are relevant for the intended users to know.

Thereupon, the implication is for PAGASA to adopt a

deliberate strategy for dissemination that makes use of

conduits and various partners that may provide useful

interpretations and sector-specific advice regarding the

climate information and forecasts. Ms. Liguton

enumerated some of these conduits/partners that may

be tapped, namely:

local government units. Partnerships with them

through Memoranda of Agreement (MOA) may be

initiated by PAGASA, with the provincial level as the locus

which will thereupon course the SCFs to the next lower

levels;

extension workers. Agricultural field workers,

being natural links with farmers, will play a major role in

disseminating, explaining, and interpreting the SCFs to

farmers as well as giving them appropriate advice on how

to make the best use of the SCFs;

traders/suppliers. Being the major source of

financing for farmers, they have a direct link with farmers

and given the proper information and knowledge about

SCFs, they may also provide appropriate advice to farmers

on the type and quantity of inputs to acquire and use;

media. Focused programs at certain given times

most practical for farmers may be co-developed with

PAGASA;

community leaders/farm leaders. Being looked

up by farmers, they can serve as good disseminators of

climate news, forecasts, and advice;

research and academic-based institutions. Those

engaged in agriculture- and climate-related research

projects and have regular contacts with farmers and

farmer groups are also logical partners; and

NGOs, including faith/church-based groups. In

recent years, a number of these groups have involved

themselves in environmental concerns and thus may be

tapped to help in the dissemination and interpretation

of SCFs during their regular congregation meetings.

There are, however, requirements called for to ensure

the successful use of the abovementioned potential

conduits/partners in dissemination. Among them are: (a)

formalized partnerships through the forging of

agreements such as in PAGASA with LGUs, PAGASA with

media, LGUs with traders/financiers, and PAGASA with

research and academic institutions; (b) appropriate

training for the partners/conduits on the interpretation

of SCFs and on the meaning of their probabilistic nature

of forecasting; (c) regular briefings; (d) seminar-workshops;

and (e) development and distribution of appropriate

printed informational materials about SCFs like manuals,

brochures, posters, calendars, comics, and newsletters with

the help of research and academic institutions. See Figure

1 for a proposed dissemination chart for Isabela using

such conduits.

Having their say: feedback from the participantsThe stimulating open discussions where the participants

fielded questions, gave comments, and raised points of

clarifications are a gauge of how receptive the participants

were to understanding and making use of SCFs in their

respective realm of decisionmaking in agriculture in

Isabela. The following are the points taken up.

Dissemination of climate informationand forecasts

Forging of a MOA between PAGASA and the

provincial government of Isabela where the Office of the

Provincial Agriculturist (OPA) will be the center of all

climate information received as well as the one

responsible for relaying the information to all the Offices

of Municipal Agriculturist (OMAs) and units below.

In response to the Isabela Provincial Agriculturist’s

(Mr. Danilo Tumamao) request that PAGASA sends its

forecasts directly to the OPA as well as to the OMAs so

that these offices will be the ones to share the information

with their local executives, Dr. Nilo suggested that all

information, i.e., forecasts, advisories, etc., related to

agriculture that PAGASA produces be sent directly to the

OPA which will thereupon be responsible for relaying the

information to all the OMAs and other units below.

After some discussions, it was agreed that a MOA

between PAGASA and the provincial government of

24 SCF Folio

Isabela will be prepared and forged regarding this

particular arrangement. Relatedly, Mr. Tumamao

suggested that all the technical information released

by PAGASA as well as the outputs of the SCF project be

translated into a form easily understood by the end-

users, especially the farmers, so that the OPA can easily

disseminate them to the OMAs and all other types of

clients according to location and capacity.

This proposed tie-up/arrangement was welcomed

by the participants, especially by Mr. Arcadio Garcillan

who also expressed the desire to have an opportunity

to gather together the provincial and municipal

agriculturists as well as farmer-leaders and have a closer

access to the SCFs.

Use of broadcast media to disseminate climate

information.

In relation to the proposed more focused

dissemination of climate information by the media,

especially radio stations, a farmer-leader from Barangay

Jones suggested that climate forecasts being delivered

to the OPA also be furnished radio stations for inclusion

in their newscasts for 7:00 a.m., 12:00 noon, and 6:00

p.m. Director Nilo promised that PAGASA will arrange

with local radio stations for them to call up PAGASA–

Echague office regularly before 6:00 a.m. for the latest

w e a t h e r / c l i m a t e

updates and broadcast

these in their programs

for the farmers’

information.

R e g u l a r

interaction between

PAGASA and LGUs on

climate information.

Some participants

also raised the

possibility of having a

representative from

PAGASA attend the

regular meetings of the

municipal agriculture

officers (MAOs) so that

he/she may update the

MAOs on the latest

forecasts/advisories and

explain to them the

meaning/interpretations of the forecasts as well as their

implications.

Dr. Hilario of PAGASA agreed to this arrangement

and requested the representative of the MAOs to

provide PAGASA–Echague office with advanced notices

of the schedule of the MAOs’ meetings. Dr. Hilario also

expressed her hope that the local PAGASA office can

be more visible in all relevant activities of the local

agricultural offices in the same vein that PAGASA central

office is actively participating in all relevant activities of

various national government offices.

Request for more localized or site-specificclimate forecasts and rain gaugesRegarding the requests for more localized and site-

specific forecasts, PAGASA pointed out that it is currently

downscaling the climate forecasts for specific areas in

Isabela, the province being one of the SCF project’s case

study sites. However, it stressed that it is not easy to

develop forecasts for each area since PAGASA does not

have a station nor rain gauges in all of these localities.

Moreover, PAGASA has to have a longer period (more

years) of weather data to be able to develop more

skillful and accurate forecasts.

As a starter, PAGASA said that it is exploring certain

schemes where it can install rain gauges in every

Figure 1. Proposed dissemination chart for Isabela

25

municipality. LGUs may send in their formal requests for

the installation of the instrument and likewise indicate if

they will be willing to enter into counterpart

arrangements with PAGASA on the operation and

maintenance of the rain gauges.

Relatedly, Isabela’s Assistant Provincial Planning and

Development Coordinator noted that since the rainfall

data of Echague do not give the true picture of the whole

province of Isabela, PAGASA previously distributed 11 rain

gauges to the following municipalities in Isabela: San

Mariano, San Guillermo, Roxas, San Isidro, Palanan, and

Reina Mercedes. Farmers from these areas are therefore

advised to get their climate data from the municipalities

where they come from and adjust their cropping patterns

accordingly.

Information on the probability and levelof accuracy of the SCFsOn the request for PAGASA to disseminate to the LGUs

and farmers, through radio broadcasts, also the probability

On the side: additional feedback

Supplementing the information/feedback gathered from the participants during the seminar-workshop and focus group discussions arethe insights gathered from the results of the evaluation and dissemination questionnaires given to the participants.

Below are some of the key points gathered.

On PAGASA’s products and servicesA majority of the 71 participants who attended the seminar-workshop came from the LGU sector (48%), followed by the farmer sector(32%), and government (20%) sector. Ninety-seven percent of the participants claimed that weather/climate is a factor in theirdecisionmaking process while 62 percent of them said that the role of weather/climate in their decisionmaking is of critical value. Radio/television ranked the highest—at 97 percent—as their main source of information on climate, followed by PAGASA station (52%) andbroadsheet/tabloids (38%). Ninety-three percent of the participants are familiar with PAGASA’s products and services, with the top threeproducts they are aware of being tropical cyclone warning, El Niño/La Niña advisories, and the annual seasonal climate forecast. Participantsrated PAGASA’s products in terms of accessibility, content, ease of understanding, timeliness, and delivery/medium of dissemination.For accessibility, 48 percent said PAGASA’s products are very good; for content, 63 percent said they are very good; for ease of understanding,45 percent said they are very easy to understand; for timeliness, 50 percent said they are timely; and for delivery/medium of dissemination,53 percent said they are very effective.

As to the ways that PAGASA may improve their products, the suggestions include: improve accuracy of the weather forecast;information must reach far-flung barangays; and more pamphlets be distributed for guide and localized forecasting. Essentially, theparticipants wanted the PAGASA to exert greater effort in the dissemination of their products. They also said that they need climateinformation so that the timing of planting and harvesting can be scheduled to minimize losses and increase their production.

On dissemination of climate information/SCFsMore seminar-workshops and better training of farmers are needed since they are the keys to better diffuse SCF knowledge. Participantssuggested some specific types of climate information that will benefit them. These are: when it’s going to rain; more accurate weatherupdates; and length of dry spells. Seventy-eight percent of the participants wanted this kind of information every 2–3 months; 22 percentsaid every quarter, and 13 percent, during the critical months. A majority of farmers prefer to receive this information through television(19%), radio (16%), extension workers (12%), and print (11%). When asked about their role regarding the dissemination of SCF, 77percent of the participants said that they are both users and disseminators of the information.

On the seminar-workshopThe top three recommendations given by the participants are:

daily releases of news on SCFs through local TV and radio stations,increase in the percent assurance/accuracy or probability of the weather forecast, anddesignation of a PAGASA representative to be present during the local agriculturists’ regular meetings.

The participants found the seminar-workshop to be highly successful. They learned from the informative sessions on the basics ofPhilippine climatology, climate outlook for Isabela, farmers’ perception on SCF, overview and the status of the project, and the disseminationprogram of the project. They also found the seminar-workshop materials and handouts as well as posters on display, which are brief andvery informative, to be very useful. On the whole, the participants were extremely satisfied about the seminar-workshop because inaddition to the knowledge that they have gained, they were also able to have informal exchanges with other participants on various projects.

26 SCF Folio

of occurrence of the particular forecasts so that farmers

may have a wider outlook or range for the planning of

their farming activities, PAGASA responded that SCFs

are really based on the principle of probability. In

disseminating the forecasts, therefore, the degree of

probability is always included. Because of this, the

meaning of the probability principle needs to be clearly

explained to the farmers and other end-users, especially

on the implications.

Director Nilo further emphasized that in climate

science, there are datasets on which forecasts are based

and certain methodologies are followed. Per the

datasets and methodology available at the PAGASA, the

level of a 100 percent—or even just 90 percent—

accuracy in terms of the probability or likelihood of the

occurrence of the forecasts cannot yet be delivered. In

Isabela, he said that the highest probability that they

can give, for instance, for rainfall to be above normal

during a La Niña period is only 50 percent. Nonetheless,

PAGASA is continuously trying to improve its skills in

this particular aspect so that they can respond better to

the needs of farmers.

Relatedly, PAGASA noted, in response to another

query, that the standard coverage of a weather station,

according to the World Meteorological Organization, is

50-km radius. Forecasts for a site made on the basis of

such radius are hence quite effective or skillful.

Possible strategic alliance with traders-financiers on provision of input selection adviceto farmers based on climate forecasts receivedIn order to have a better matching of seed varieties

with the cropping season, there were suggestions and

likewise an agreement in principle to have a better

understanding by both the farmers and traders/

suppliers of the various seed varieties suitable to certain

months of the year. In response to the points raised by

some farmers on the quality of seeds, in particular,

hybrid corn seeds, being sold to them by certain seed

companies and traders, the research director of the

Isabela State University (ISU) suggested the setting up

of an independent body that would assess the

performance of seeds being sold by seed companies

vis-à-vis their suitability to the farms as well as cropping

season.

In this regard, it was noted that a strategic alliance

between traders-suppliers and farmers could possibly

be established through the help of the MAOs and

PAGASA. By regularly supplying traders-suppliers with

information and explanations of the meaning and

interpretations of SCFs and what possible implications

these might have on the characteristics and

performance of various input varieties, traders-suppliers

may be influenced to keep in stock the appropriate

inputs and varieties as well as be enjoined to provide

the corresponding appropriate advice to farmers on the

varieties that will prove to do well under such

circumstances. Conversely, farmers may likewise

indicate their preferences of the varieties they need

given their farms’ circumstances to which traders-

suppliers may correspondingly adjust their supplies.

A final noteDr. Celia Reyes concluded the seminar-workshop by

providing a summary of the following major

agreements reached as well as the next steps

considered:

A MOA between the PAGASA and the province

of Isabela, through the Office of the Provincial

Agriculturist (OPA), will be forged to ensure that all SCFs

and other PAGASA climate information/products reach

the stakeholders/decisionmakers in agriculture in the

province.

PAGASA will now provide modified forecasts

on the basis of probabilities as explained earlier. These

modified forecasts therefore call for a clearer

explanation of the meaning and implication of the

probabilities.

The PAGASA central and local offices, with the

help and collaboration of the OPA and MAOs, will forge

agreements/arrangements with the local media,

especially radio stations, on the regular dissemination

and explanation of SCFs and their meanings/

implications to farmers and farmer-groups through

special programs focusing on agriculture-related

climate information and forecasts.

Finally, strategic alliances with traders-

suppliers may be explored where, through regular

information and briefings supplied/given to them by

PAGASA and the OPA, they may be used as conduits in

passing on such information and giving appropriate

advice to farmers on the corresponding farm inputs

selection that the latter should make. (SCF Project

Updates, March 2008)

27

Yes, seasonal climate forecast (SCF) is popular

among corn farmers in Bukidnon. This is

according to a recent study on “Corn farmers’

decisionmaking based on probabilistic climate

forecast” conducted by a team of researchers from the

Visayas State University (VSU) based on the results of focus

group discussions among farmers from selected sites in

the province of Bukidnon in Mindanao. The study found

that farmers are aware of SCF, their sources of which

included television, radio, and the PAGASA station in

Malaybalay City. At the same time, it was learned that

PAGASA and the City Agriculture Office often hold

seminars and workshops on the SCF.

Notwithstanding this, however, “farmers depend

more on their indigenous climate forecasting than on

SCF,” the study reported. For one, the study found that

farmers think of climate forecasts as deterministic rather

than probabilistic [please see explanation of probabilistic

SCF is popular in Bukidnon but...

Gian Carlo Borines, Rotacio Gravoso,Jude Nonie Sales, and Ulderico Alviola

nature of SCFs in SCF Project Updates March 2008, page

2]. Thereupon, if the forecasts given do not jibe with what

climatic condition actually takes place, then farmers tend

to lose confidence in the forecasts. They also said that

climate forecasts are hard to understand. Thus, they

suggested that said forecasts use simple words and be

downscaled to their locality.

The decisionmaking exercises utilizing hypothetical

forecasts showed that under unfavorable climate

forecasts, farmers would apply coping mechanisms like

growing short-season crops, backyard gardening, raising

animals, and finding a job in sugarcane plantations and

industries in Malaybalay City. Generally, farmers’ decisions

were aimed to maximize profits and minimize cost. (SCF

Project Updates, June 2008)

Cebu workshop stresses needto disseminate SCF

The need to disseminate seasonal climate forecasts

(SCFs) has been repeatedly underscored by

researchers and farmers alike in the seminar-

workshop on the “Role of seasonal climate forecast” held

on September 29, 2008 at the Cebu Business Hotel, Cebu City.

Participated in by about 40 farmers, representatives

from the agricultural offices in Cebu, researchers from the

Philippine Atmospheric, Geophysical and Astronomical

Services Administration (PAGASA), Philippine Institute for

Development Studies (PIDS), Visayas State University

(VSU), the academe, and Cebu’s media, the workshop was

part of the dissemination effort of the project, “Bridging

the gap between seasonal climate forecast and

decisionmakers in agriculture,” a collaborative project

between Philippine implementing agencies—PAGASA,

PIDS, and the VSU—and their Australian counterparts.

During the workshop, Dr. Flaviana Hilario, Weather

Services Chief of the Climatology and Agrometeorology

Branch (CAB) of PAGASA, noted that SCF is among

PAGASA’s climate products and services that have been

introduced to the public, particularly farmers and

fisherfolks, in recent years and whose benefits to farmers

and fisherfolks, especially during occurrences of climatic

anomalies, have been cited by several studies. She

acknowledged, however, that its dissemination to its

intended end-users has been wanting.

In his presentation, meanwhile, Dr. Canesio Predo of

the VSU, said that the use of SCF allows farmers to improve

28 SCF Folio

profits resulting from better farm management

decisions as they take advantage of the opportunity

during good seasons and minimize losses during bad

seasons. He also discussed the various tactical farm

management applications of SCF to address climate

variability such as crop choice, timing of cropping period

or planting time, and levels of input use, among others.

He likewise presented research findings that show how

farmers found SCF to be valuable in better managing

cropping systems. In particular, SCF was found to be

valuable in deciding what crop/variety to plant during

the growing season. The findings also indicated that

farmers using SCF have realized higher incomes than

those who are not. However, Predo stressed that farmers

need to be conscious of when to apply and when to

disregard the information provided by the SCF.

In underscoring the need to disseminate SCF, Mr.

Renelio J. Mabao, City Agricultural Officer of Toledo City,

reported that to date, they only get weather forecasts

through the radio and television, especially during bad

weather. It is only when “there are forecasts on the

occurrence of El Niño or El Niña from PAGASA that either

Climate information needs assessment for Cebu

The specific types of climate-related information that the respondents during the Cebu workshop want to receive are predicted rainfall(12.5%), rainfall and temperature pattern (12.5%), onset and termination of wet and dry spells (12.5%), and seasonal climate forecast

(25.0%) as shown in Table 1.The reasons of the participants on why they need the specific types

of climate-related information include: for instruction and extensionservices (12.5%), for decisionmaking (12.5%), for maintaining crops onlarge scale (12.5%), for recommending possible crops to be planted(12.5%), and for disseminating information and assisting clients indecisionmaking (12.5%).

Table 2 presents the participants’ responses on the time andfrequency of receipt of the information. Participants said that they wantto receive the information during critical periods (12.5%), more than halfsaid that they want to get them on quarterly (62.5%) basis, and some(25%) answered that it should be within 2–3 months before the usualplanting season.

The channel through which the participants want to receive theinformation are through bulletins from weather station (25%), radio(20.8%), television (16.7%), extension workers (8.3%), print (8.3%), fax(8.3%), internet (e-mail) (8.3%), and pamphlets, manuals, etc. (4.2%).

The results also show (Table 3) that it is with community leadersand community associations that the participants interact more regardingcommunity welfare issues (at 33.3% and 26.7%, respectively). Localgovernment officials/representatives are next (20%), followed equallyafterwards by the media and nongovernment organizations.

Finally, more than half (62.5%) of the respondents saidthat they are both user and disseminator concerning thedissemination of seasonal climate forecast (Table 4).

Table 4. Role of respondents regardingdissemination of seasonal climate forecast

Item n %

User 3 37.5Both user and disseminator 5 62.5Total 8 100.0

Table 1. Specific types of climate-related informationthat the participants want to receive

Item n %

Predicted rainfall 1 12.5Rainfall and temperature pattern in Argao 1 12.5Onset and termination of wet and dry spells 1 12.5No answer 3 37.5Seasonal climate forecast (SCF) 2 25.0Total 8 100.0

Table 2. When and how often would the respondentswant to receive the information

Item n %

2–3 months before usual planting season 2 25.0During critical periods 1 12.5Quarterly 5 62.5Total 8 100.0

Table 3. Sector/group that the respondents normally interact/discuss on issues affecting community welfare

Item n %

Local government officials/representatives 3 20.0Community leaders 5 33.3Media 1 6.7NGOs/faith-based groups 1 6.7Community associations 4 26.7No answer 1 6.7Total 15 100.0

29

the Provincial Agriculture Office (PAO) or the Department

of Agriculture Regional Field Office (DA-RFO) calls for a

meeting for precautionary measures,” Mr. Mabao said.

Mr. Mabao said that they disseminate these forecasts

that they get during their meetings with the farmers.

Fisherfolks, meanwhile, depend on the daily weather

forecasts from PAGASA on whether or not they will go

fishing. “Thus, it would be better if there could be a way

by which PAGASA could send us a copy of their SCFs in

advance so as to improve the system of forecasting,”

Magbao added.

In a related focus group discussion (FGD) that the

representatives from PAGASA, PIDS, and VSU had with

corn farmers and their spouses at Brgy. Sangi, Toledo City

(see photo below), Julieta Daclan, one of the farmer-

leaders of said barangay, explained that “there is no such

thing as proper time for planting corn” in Barangay Sangi.

The reason for this, she said, is that most of the farmers

are totally dependent on their corn produce as their

source of living. Thus, immediately after harvesting, land

preparation follows and then, after 3–5 days, the planting

starts, ensuring that the farmers will not all be harvesting

at the same time.

The farmer-leader explained that they harvest their

corn after 72–73 days after planting during the dry season

and after 75 days during the wet season. They harvest

corn as young corn and seldom allow the corn to mature

and be milled into grain.

She also admitted that the climate change has

affected their produce, thereby affecting their livelihood

too. “If PAGASA can inform us ahead that there will be a

drought for the coming three months, then we will plant

the native variety of corn that could withstand drought,”

she stressed.

Responding to the call for a more proactive

dissemination of the SCF, Ms. Jennifer Liguton, Director

for Research Information at PIDS, discussed the need for a

strategic dissemination of SCF involving PAGASA local

offices, community organizations, the media, extension

workers, and the academe. She emphasized that the SCFs

will be more assured of reaching the various stakeholders,

especially the farmers, if the dissemination of said

information is devolved. For instance, forecasts from

PAGASA’s central office will be sent to PAGASA’s local

offices or to the Department of

Agriculture, then passed on to

the provincial and municipal

agricultural offices. Extension

workers will play a key role in

the process as they pass on the

information to farmers. The

SCF dissemination will likewise

be more effective if the

information is presented and

explained in simple and easy-

to-understand terms, and if

the forecast is suitable to local

application, specific to sites,

and issued on timely basis.

(SCF Project Updates, September

2008)

30 SCF Folio

The last of the series of seminar-workshops on

“The Role of Seasonal Climate Forecasts in the

Agriculture Sector” was held at the Pine Hills

Hotel in Malaybalay, Bukidnon on 27 November 2008.

It was well attended and featured speakers coming from

PAGASA, Visayas State University (VSU), and the

Philippine Institute for Development Studies (PIDS) who

discussed current issues affecting the climate and corn

industry in Bukidnon. The workshop also featured Engr.

Alson G. Quimba, Acting Provincial Agricultural Officer

of Bukidnon, who talked about how climate change is

becoming to be a reality in the province, what with new

climate pattern occurrences like strong typhoons and

flooding taking place in the province, and discussed

how the province is dealing with these. Meanwhile, the

keynote speaker, the Hon. Jose Ma. R. Zubiri, governor

of Bukidnon, in a message read on his behalf, recognized

the importance of the seminar-workshop, particularly

in the applicability of the research results for use by

decisionmakers in agriculture, and said that the local

government welcomes projects like these because they

allow them to look at their strengths and limitations for

the good of the people.

A total of 85 participants representing the different

municipalities of Bukidnon, municipal and city

agriculturists, officials from the Governor’s office, and

members of the academe attended the seminar-

workshop. Members of the project team lectured on

climate concepts to acquaint key decisionmakers in

agriculture in Bukidnon on the possible role of seasonal

PAGASA hosts seminar-workshopon seasonal climate forecasts

climate forecasts in improving productivity and overall

welfare of the agriculture sector in the province.

Also presented were studies relating to risk-

efficient planting schedule for corn in Bukidnon, and

climate variability and corn farming in Bukidnon as well

as the Decisionmaking Game based on SCF using a

spinning wheel. Dr. Canesio D. Predo, Assistant Professor

of VSU, led the game where the participants were able

to apply the knowledge they gained from the

workshop. Ms. Jennifer P.T. Liguton, Director for Research

Information of PIDS, then presented the different

communication pathways to be employed by the

project in disseminating its various outputs to

agricultural stakeholders.

Finally, Dr. Flaviana D. Hilario of PAGASA, in her

closing remarks, assured the participants that regular

SCF updates will be provided to the province since

Bukidnon is one of the pilot areas of the project. (SCF

Project Updates, September 2008)

31

An

alys

is a

nd

res

earc

h/s

urv

ey r

esu

lts Assessing rainfall variability in Philippine

study sites: the Rainman application

B ecause of its geographical location, the

Philippines is prone to extreme weather and

climate events. Floods and droughts have, for

instance, been common occurrences in the country

especially in the recent past resulting in massive

destruction of property, loss of life, diseases, and food

shortages. Sectors of the economy, including agriculture

and water resources, have likewise been severely affected

by these weather/climate events.

The Philippine Atmospheric, Geophysical and

Astronomical Services Administration (PAGASA) monitors

weather and climate conditions from both local and global

perspectives. It has a network of weather stations

strategically located all over the country that monitor

meteorological and weather elements. These parameters

are then analyzed using various statistical techniques and

procedures to come up with weather or climate forecasts.

Provision of these forecasts and early warnings of

potential crop failure due to drought, with a lead time of

30-60 days before harvest, is important because it enables

policy/decisionmakers to implement alternative courses

of action to mitigate potential damages to the agricultural

sector. Seasonal forecasting is an

attempt to provide information on

the likely conditions of the weather

several months in advance.

The Climate Information,

Monitoring and Prediction Center

(CLIMPC), one of the sections of the

Climatology and Agrometeorology

Branch (CAB) of PAGASA, is

responsible for the issuance and

dissemination of seasonal climate

forecasts and advisories. With the

recent advancement in the

understanding of the El Niño

Southern Oscillation (ENSO)

phenomenon and climate

prediction, seasonal to interannual

prediction has made it possible to

predict climate with improved

accuracy and with lead times

ranging from one season to over a year in advance. This

improvement means that impending extreme climate

events can be predicted with greater accuracy.

Predictability of the climate from season-to-season

and year-to-year arises from the interaction of the ocean

and the atmosphere. The best-known example is the

ENSO phenomenon. The combination of the slowly

changing temperature of the oceans and their

interactions with the atmosphere provides a degree of

predictability for seasonal climate in many regions of the

world. Based on global studies, ENSO and other sea

surface temperature anomalies are known to influence

global climate, altering rainfall and other climate variables

throughout much of the tropics and subtropics and in a

few locations in mid-latitudes. Seasonal climate prediction

is based on the expectation of the effects of these

influences in the coming season. In this regard, climate

forecasters normally ask two basic questions: (1) what will

the sea surface temperature anomalies be in the coming

season? and (2) how will they impact on global climate?

There are models available which can evaluate the

effects of ENSO on seasonal climatic patterns and on the

Statistical test results on forecasts of rainfall in Southeast Asia(Analysis of historical data—1903 to 1995—using SST Phase forecast in September for rainfallperiod: Oct to Dec, leadtime of 0 months)

32 SCF Folio

variability of rainfall in the Philippines. One of these is

Rainman. This brief writeup focuses on the use of this

program in evaluating the effects of the ENSO

phenomenon on seasonal climatic patterns and

variability of rainfall in three selected study sites of the

Philippines—Isabela in the island of Luzon; Baybay

(Leyte) in the Visayas; and Malaybalay (Bukidnon) in

Mindanao.

The Rainman Program: providing an enhancedmethod of forecasting ENSO effects on rainfallRainman is an integrated package about rainfall and

streamflow information developed by the Queensland

Department of Primary Industry, Australia in a previous

ACIAR-funded project. A unique feature of Rainman is

the seasonal rainfall analysis which may be done with

monthly data and also daily data where they are

available. Here, one can see what influence either the

Southern Oscillation index (SOI) or the sea surface

temperature (SST) may have on rainfall, using any

length of season (1–12 months), up to the coming year.

This prediction or forecast is helpful for those making

management decisions in a highly variable climate.

The initial results of the seasonal climate forecasts

for 12 overlapping seasons (i.e., December-January-

February; January-February-March; February-March-

April; and so on) at zero lead time (meaning that for

forecasts for, say, February-March-April, the data used

are those for January) in the three study sites earlier

mentioned are presented here. The statistical skills of

these forecasts were evaluated

using the SST forecast phase system

(the Pacific effects) of Rainman to

indicate whether changes in rainfall

pattern as predicted or forecasted

are real or are due to chance.

The Philippine study sitesand the test applicationsThe Philippine component of the

ACIAR project on seasonal climate

forecasts selected four sites for its

case studies, namely: Isabela in the

island of Luzon; Baybay (Leyte) and

Cebu in the Visayas; and Malaybalay

(Bukidnon) in Mindanao. For this

particular study, however, certain

considerations were taken into

account and some changes/

substitutes were made.

In particular, the significance of

the test results is sensitive to the

number of years of data; the more

years (minimum is 30 years), the

better. In this light, the absence of

longer climate record for the stations

in Baybay, Leyte and in Isabela

influenced this study’s use instead

of the climate data in nearby areas

( Tacloban for Baybay and

Tuguegarao in Cagayan Valley for

Isabela) that have the same climate

types as the original study sites.

The Philippine study sites

*Data substituted for Isabela

33

For the Malaybalay site, meanwhile, since the

available climate record is about 79 years, the same site

was used. On the other hand, no evaluation was done as

yet for the Cebu site.

As mentioned, the SST phase system using the Pacific

Ocean effects was the one applied in evaluating the

impact on the study sites. In particular, the following main

effects of the Pacific Ocean were tested: (1) cooler Pacific

Ocean pattern where phases 1, 4, and 7 (which are

associated with wetter than normal rainfall condition in

the Philippines) were combined; (2) neutral Pacific Ocean

pattern where phases 2, 5, and 8 (wherein neutral

conditions indicate that there is an equal chance of

getting above normal or below normal rainfall in the

Philippines) were combined; and (3) hotter Pacific Ocean

pattern where phases 3, 6, and 9 (which are associated

with drier than normal rainfall condition in the Philippines)

were combined.

Results of analysisThe following are the key results of the analysis/

evaluation:

An analysis of the historical data (from 1919–2004)

in Malaybalay found that there is a 70 percent chance or

probability of having the rains exceed the median rainfall

during a cooler Pacific Ocean from September to February

while there is a lower chance—at 20 to 30 percent—of

getting a median rainfall during a hotter Pacific Ocean

from September to March.

For the study site in Tacloban, analysis of historical

data showed that for a constant lead time (0 month)

before a three-month rainfall period, there is a 60–80

percent chance of exceeding the median rainfall starting

the month of November up to March during a cooler

Pacific Ocean. During Phases 3, 6, 9 of the hotter Pacific

Ocean pattern, the chance of getting above median rainfall

decreases from 40 to 20 percent from September to March.

The seasonal forecast skill in Malaybalay and

Tacloban is statistically significant starting the month of

October up to March.

Meanwhile, like in Tacloban, the percent chance of

exceeding the median rainfall in Tuguegarao is increased

from 60–80 percent during a cooler Pacific Ocean while

the chance of getting this level is reduced during a hotter

Pacific Ocean.

What do the above results mean?Simply told, the impact of ENSO on the Philippines varies

with season and location. Generally, the forecast skill is

higher for October to March.

With regard to the status of the ENSO, the results

indicate that during the onset of El Niño and La Niña

(hotter Pacific Ocean and cooler Pacific Ocean

occurrences, respectively), the trends established in the

chances of getting lesser (for the El Niño period) or more

(for La Niña period) amounts of rain than the median

rainfall are more distinct.

Unfortunately, however, there are also neutral

conditions when there is an equal chance of getting

above or below normal rainfall in the country. During this

period, the forecast skill is not statistically significant and

decisionmakers need to use the long-term climate

record.

ConclusionAs the results in this initial study suggest, more specific

climate information provided in advance of a particular

planting or harvest season will be of great help to those

who make specific decisions in the agriculture sector.

For this study, focus was on the use of the SST phase

system as an ENSO indicator at zero lead time. There are,

however, other features in Rainman that can look, for

instance, at the seasonal forecast skill using various lead

times like, say, 30–60 days before a harvest season.

In this regard, Rainman will be used and tested in

the coming months to provide better answers to the

specific needs of the users.

What is important is to be able to determine which

forecasting system will be able to yield better results

depending on various variables like season, location, time

of year, lead time, and the status of ENSO. (SCF Project

Updates, December 2005)

As the results in this initial study suggest, more specificclimate information provided in advance of a particularplanting or harvest season will be of great help to those whomake specific decisions in the agriculture sector...What isimportant is to be able to determine which forecasting systemwill be able to yield better results depending on variousvariables like season, location, time of year, lead time, andthe status of ENSO.

34 SCF Folio

A decade of destruction from seasonalclimatic aberrations

Much had happened in the Philippines’

agricultural sector over the past decade.

Great technological milestones were

made but setbacks were also ever present. Productivity

in the crop sector has generally been increasing over

the last 10 years but production losses, especially those

from seasonal climatic aberrations, have also been huge.

Data from the Department of Agriculture prove

the vulnerability of the farming sector to the

unpredictability of nature. Droughts, floods, and

typhoons have been wreaking havoc on crops and

causing untold miseries among farmers. From 1995–

2004 alone, climatic aberrations had damaged a total

of 4.1 million hectares of prime rice and corn farmlands.

Cumulative losses incurred amounted to P16 billion for

rice farmers and P7.2 billion for corn growers (Table 1).

A major cause of the climatic catastrophes being

experienced in the country, and in other parts of the

world, is the El Niño Southern Oscillation (ENSO)

phenomenon. ENSO has two major phases: the El Niño

or warm event and the La Niña or cold event. El Niño

conditions lead to drier seasons due to suppressed

tropical cyclone activity and weak monsoon

characterized by delayed onset and early termination

of the rainy season and by prolonged dry

periods. La Niña, on the other hand, is

characterized by above normal rainfall and

longer rainy seasons. The impact of ENSO

was clearly documented during the 1997–

1998 El Niño/La Niña episode when a total

of P7.6 billion in rice and corn production

losses were incurred.

More alarming is the seemingly

frequent occurrence of the ENSO

phenomenon in recent years. There has not

been a single year from 1994 up to the

present when either the cold or warm phase

of ENSO was not present (Table 2).

This fact is distressing given the

trend that the event only occurred

on average by intervals of 2–7 years

during the last 300 years. This

apparent increase in climatic

variability equates to elevated risks

in agricultural production and

postproduction operations.

Risks are easily converted to

losses when not properly

addressed. ENSO impacts all

segments of society but among

the most affected are resource-

constrained farmers whose

livelihoods are greatly dependent

on the changing seasons. This is

-500,000

1,000,0001,500,0002,000,0002,500,0003,000,0003,500,0004,000,0004,500,0005,000,000

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

YEAR

AM

OU

NT

Palay Area(ha) Palay Volume(MT) Palay Value (P'000)

Corn Area(ha) Corn Volume (MT) Corn Value (P'000)

Palay and corn damages

Table 1. Damages to rice and corn production due to droughts, floods, and typhoonsfrom 1995–2004

Year Palay Damages Corn DamagesArea (ha) Volume(MT) Value (P’000) Area (ha) Volume (MT) Value (P’000)

1995 581,511 953,436 3,977,341 126,863 192,979 476,4121996 95,326 114,979 234,706 13,196 418,481 704,4161997 201,021 204,186 433,284 30,675 27,697 82,4391998 1,281,838 1,863,848 4,679,394 350,357 497,075 1,846,0041999 278,956 258,487 809,088 9,883 5,714 32,8732000 375,029 510,553 1,594,869 19,394 10,535 57,5982001 214,593 296,040 805,059 140,882 162,808 546,1432002 121,199 220,760 548,347 53,271 87,046 330,3542003 287,199 413,155 1,320,091 255,565 663,901 1,696,1242004 362,086 649,531 1,696,584 148,578 492,183 1,436,241

Total 3,798,758 5,484,975 16,098,763 1,148,664 2,558,419 7,208,604Mean 379,876 548,498 1,609,876 114,866 255,842 720,860

Source: Department of Agriculture, 2006

35

most evident among rainfed farmers who rely exclusively

on rainfall to irrigate their crops.

Other agricultural businesses that operate with

better resources and more modern technology on better

farmlands are also not spared from the same risks.

Prolonged dry spells, excessive rains, and flooding are

critical events that could easily destroy a season’s crop.

The coming of rains signals the start of a new planting

season but the same gift from nature—or lack of it—could

easily wipe out a standing crop. The need to safeguard

the interests and investments of local farmers and

industry players is therefore of great importance.

To address these concerns, the Philippine

government has been implementing a range of risk

management programs for farmers and other agricultural

stakeholders. These include price stabilization measures,

typhoon and/or drought relief, livestock and feed

subsidies, fertilizer, and other input subsidies as well as

subsidized crop insurance schemes. Specialized projects

are also being implemented in collaboration with local

and international partners to aid in the effort.

An example of this workable partnership is the

ACIAR-funded Bridging the gap between SCF and

decisionmakers in agriculture. The project is a

collaborative undertaking between the governments of

Australia and the Philippines, through the Philippine

Atmospheric, Geophysical and Astronomical Services

Administration (PAGASA), the Philippine Institute for

Development Studies (PIDS), and the Leyte State

University, for the Philippines. It essentially deals with

managing climate variability through better forecast

information and better utilization and appreciation of

these forecasts by agricultural decisionmakers.

Though not much could be done when a “prolonged

drought” or a “super typhoon” strikes, there is still a wide

array of applicable tools that could help agricultural

workers mitigate environmental challenges and decide

intelligently in the face of seasonal uncertainties. A crop

farmer will have a healthier chance of going through

seasonal abnormalities and coming out unscathed if he

is well informed. The decision to push through with the

cropping season should ideally be the product of an

enlightened process.

A decade of destruction and challenges from

seasonal climate variability should have provided ample

insights and learning to everyone concerned. The coming

years should now serve as testament to this added

wisdom, ushering in a more secured, productive, and

profitable era for rice and corn farmers in the country. (SCF

Project Updates, December 2006)

Table 2. El Niño and La Niña episodesduring the past decade

Period Event

May 1994 – April 1995 El NiñoOctober 1995 – April 1996 La NiñaJune 1997 – May 1998 El NiñoAugust 1998 – July 2000 La NiñaNovember 2000 – March 2001 La NiñaJune 2002 – April 2003 El NiñoAugust 2004 – March 2005 El Niño

Source: Climate Prediction Center-NationalOceanic and Atmospheric Administration(CPC-NOAA), 2006

El Niño is here again!

El Niño is back and here to stay, at least until the first

half of year 2007.

Climate monitoring bodies from all over the

world, including the local meteorological agency PAGASA,

have confirmed that the warm phase of the El Niño

Southern Oscillation (ENSO) is continuing to progress. As

of October this year, sea surface temperatures (SSTs) in

the central equatorial Pacific have been rising and the

Southern Oscillation Index (SOI) has been decreasing.

Over the past six months, most of the statistical and

coupled model forecasts employed by climate monitoring

agencies like the Climate Prediction Center (CPC) in the

United States have projected warmer conditions in the

tropical Pacific. Weaker-than-average low-level equatorial

easterly winds have also been observed across most of

the region. CPC stated that collectively, current oceanic

and atmospheric anomalies are consistent with the early

stages of El Niño.

36 SCF Folio

In the Philippines, PAGASA had already come up

with local advisories related to the progressive evolution

of the current El Niño episode. The meteorological agency

reported that the event is likely to intensify during the

next three months and persist through April to June 2007.

Below normal rainfall conditions were already

observed by PAGASA over the past months in parts of

northern and western Luzon, most of northern Panay

Island including Iloilo, southern Cebu, the western parts

of Bohol and Zamboanga provinces, most parts of the

CARAGA provinces, Davao Oriental, eastern part of

Davao del Norte and the southern tip of Davao del Sur,

and South Cotabato. Only the intertropical convergence

zone (ITCZ) and the occurrence of destructive typhoons

had brought above normal rainfall in affected areas, as

witnessed in the recent typhoons Milenyo, Neneng,

Ompong, and Paeng.

Rainfall forecasts for November included below

normal projections in most parts of the country, except

in Isabela, Quirino, Aurora, South Cotabato, and Surigao,

and Regions IVB, V, and VIII where rainfall is forecast to

be normal.

This early, the threat to the country’s water reserves

is already being felt by some sectors. Possible shortage

of water supply in Metro Manila is a cause of alarm

because the low rainfall volume might lead to a lower

water level in Angat Dam. Dependent on rainfall to

replenish its water reserve, the dam supplies water to

Metro Manila’s 12 million residents and irrigates the vast

agricultural lands of Central Luzon. The same problem

is expected to be experienced in other parts of the

country as El Niño intensifies.

The government has already advised everybody

to continue implementing appropriate measures to

mitigate the potential adverse impacts of the episode

on agriculture, water resources, hydropower generation,

health and sanitation, and other affected sectors. (SCF

Project Updates, December 2006)

Researcher presents findings on SCFimpact simulation

Dr. Felino Lansigan, Professor of Statistics at the

University of the Philippines Los Baños

(UPLB), presented the results of his study

titled “Analysis of the effects of climate variability on

corn productivity in the Philippines” on September 22,

2006 at the NEDA sa Makati Building, Makati City.

Working with the ACIAR-funded project Bridging

the gap between SCF and decisionmakers in agriculture,

Dr. Lansigan discussed the initial results of his research

during the “Pulong Saliksikan at PIDS” before an

appreciative crowd of government and NGO

representatives. He presented the effects of climatic

variability on corn yield under different El Niño southern

oscillation (ENSO) phases in three different locations,

namely: (a) Los Baños, Laguna, (b) Ilagan, Isabela, and

(c) Malaybalay, Bukidnon.

In assessing the impact of SCF, Dr. Lansigan

classified historical weather data into three categories:

“dry (El Niño) year,” “wet (La Niña) year,” and “average

(neutral) year.” He also generated synthetic weather

data for the crop yield—climate variability analysis

using applicable software to complete a 50-year

weather data series.

The CERES-maize model, an ecophysiological-

based crop simulation model for corn, was used to

simulate yields given varying climatic and cultural

conditions. Results showed that mean crop yields in the

three locations were significantly different during wet

and dry years. Simulated corn yields in Ilagan gave the

highest coefficient of variation (CV) of 35.2 percent

during average years, and 27.7 percent and 27.0 percent

during wet and dry years, respectively. Los Baños gave

the lowest CV at 17.7 percent during wet years, and 28.9

percent and 26.4 percent during dry and average years,

respectively. In Malaybalay, respective CVs for dry,

Dr. Lansigan succeeded in showing the effect of climate variabilityon corn productivity through yield variability and yielddifferences within and between locations...As a positive note, heended by stressing that the vulnerability of corn-growing areasmay be reduced given appropriate coping strategies.

37

average, and wet years were calculated at 22.4, 23.3, and

31.6 percent. Resulting figures also showed negligible

yield differences during wet season cropping and

appreciable changes during dry season cropping.

Dr. Lansigan succeeded in showing the effect of

climate variability on corn productivity through yield

variability and yield differences within and between

locations. Among the study sites, Ilagan, Isabela was found

to be the most vulnerable to climatic variability especially

during dry years, while Los Baños, Laguna proved to be

the least vulnerable. As a positive note, Dr. Lansigan ended

by stressing that the vulnerability of corn-growing areas

may be reduced given appropriate coping strategies. (SCF

Project Updates, December 2006)

SCF use and indigenous knowledgeamong corn farmers in Isabela

C orn farmers in Isabela,

Philippines hold both seasonal

climate forecast (SCF) and

indigenous forecasting means in high

regard. A survey done among corn

growers in the province showed that

seasonal climate information from both

traditional and scientific sources greatly

influenced farming decisions on

working capital, type of crop to plant,

and time of planting.

When asked on why SCF is

important, 96 percent of the

respondents answered that it aids in on-

farm decisionmaking as it allows

farmers to prepare for climatic events.

Many also recognized the role of climatic information in

deciding when to plant or commence the cropping

season.

At the same time, a long list of traditional forecasting

methods was also gathered from many of the interviewed

farmers. To predict the coming of rains, local folks looked

for a variety of signs ranging from the appearance of

heavenly bodies like the moon, stars, sun, and clouds;

behavior of local fauna like insects, birds, and farm animals;

and the performance of local flora like the flowering of

orchids and grasses, and fruiting of trees.

One third of the farmers also believed in

superstitions when commencing farm activities. Good

luck and bad luck beliefs influenced decisions on the

timing of and cultural approaches to certain farm

operations. Though not with scientific basis, these beliefs

and practices are part of the indigenous make-up of local

farmers and should be regarded when pushing for the

adoption of applicable technological interventions.

Interestingly, majority of farmers believed in the

reliability of indigenous weather forecasting means.

Among the respondents, only 25 percent voiced out that

such methods were unreliable.

The figures look good as the overall responses of

farmers reinforced the claim on the significance of

seasonal variability and climate forecast. However, enough

caution should be exercised when interpreting things.

Though many claimed to appreciate SCF, actual

application seemed to be not enough. The start of each

cropping season was still principally based on the coming

of rains and the traditional seasonal schedule. Among

those who acknowledged the influence of SCF on the

general timing of planting in farm operations, only 1

percent claimed actual application on the planting

Members of the PIDS-SCF Project Team meet with municipal agriculturists in Isabela.

38 SCF Folio

schedule for corn. This shortcoming made farmers

vulnerable to climatic variability as proven in 2005 when

many corn growers had to replant three times due to

El Niño/La Niña-induced drought and floodings.

The indigenous means of forecasting also focused

more on seasonal onset and day-to-day weather.

Reliable projections on seasonal variability like the

possible occurrence of drought and excessive rains

were few. Indigenous mitigating measures as well as

modern interventions against droughts and floodings

were also found wanting.

With scarce reliable indigenous knowledge on

climate forecasting, the task becomes the sole

responsibility of the country’s meteorological bureau.

Other support institutions should also do their part in

helping farmers cope up with seasonal challenges. Corn

farmers should not only be recipients of information

but should also be target clienteles for the transfer of

appropriate agricultural technologies.

What is truly promising in all these is the

continuous validation that climate and climate-related

information are of prime consideration to farmers. The

positive figures and responses mentioned above are

close to what researchers and development workers

have been advocating. This seeming match between

the ideals of farmers and change agents could help

offset the technology application gap and possibly

make the campaign on SCF use much easier.

Without putting down the importance of

indigenous practices and know-how, reliable seasonal

climate forecast remains the key to answering the riddle

of seasonal variability. A dependable seasonal advisory

would allow farmers to securely harness the goodness

of the changing seasons. (SCF Project Updates, March 2007)

Indigenous forecasting means in Matalomand Mahaplag, Leyte

When clouds in the east turn red at sunrise and narratrees start to bud; when gangis (dragonflies) and

tukbahaw (birds) call and nights turn cold, then rainfall

will not be so bold…

the behavior of plants and animals, appearance of stars,

color of the sky, and direction of the wind.

Among those identified as indigenous means of

forecasting a wetter season were: the falling of leaves

and flowering of narra trees, appearance of red sky

during sunset, presence of winds coming from the

northeast, and sighting of the Big Dipper constellation.

Some also believed in the impakta1 phenomenon,

which suggests that the conditions of the first 12 days

of the year represent the general conditions of their

corresponding month in the 12-month calendar year.

Farmers generally perceived such indigenous

means as dependable, with around 60 percent of them

believing that traditional forecasting methods were

reliable. Only 39 percent of the farmers claimed

otherwise.

The results of the study are interesting as they

give a glimpse of the psychology and rich culture of

This is neither an excerpt from a poetic piece nor an

introduction to a religious prophecy. Rather, it is an

enumeration of local indigenous indicators among corn

growers in Leyte province signifying that rainfall would

be scarce in the coming planting season.

In a farm and household survey conducted by Dr.

Canesio Predo and the Seasonal Climate Forecasts (SCF)

project team from Leyte State University, 125 corn

farmers from the municipalities of Matalom and

Mahaplag, Leyte were asked about their perception,

awareness, attitude, and indigenous knowledge on

forecasting and mitigating the effects of seasonal

climatic variability.

Farmers enumerated a list of traditional indicators

that are being used to project the overall theme of the

coming planting season. To predict the coming of rains,

many corn growers looked for a variety of signs such as

____________1 Impakta phenomenon occurs, i.e., if the first day of the year israining, the whole month of January will be rainy; if the secondday of the year is raining, then the month of February will be rainy;and so on until 12 days to complete the 12 months of the year.

39

local corn growers. In guiding farmers and infusing science

in their operations and on-farm decisionmaking, therefore,

awareness and enough vigilance of such beliefs should

be exercised. Indeed, much could be done to promote

productivity and minimize damages from climatic happenings

when knowledge of these local means is on hand.

Damages from climatic variability during the past

years were indeed immense, with 92 percent of the

respondents claiming that they had experienced losing

crops due to droughts, floods, and typhoons. The situation

is made worse as most of the farmers were pessimistic

about mitigating the adverse effects of these events. Still,

some corn growers claimed to have implemented

indigenous solutions like hilling-up, planting less, and

abandoning/fallowing the field.

A positive light is that more than 90 percent of the

farmers considered weather/climate as a major factor in

planning and crop production decisionmaking. Majority

claimed that advanced seasonal climate information

could aid in their production activities. This openness to

intervention, complemented with a rich blend of

experience and culture, could help jumpstart a wave of

development and increased productivity among the

country’s corn growers. (SCF Project Updates, March 2007)

Lunar-based agriculture: logic or folly?

For centuries, the mysterious magnificence of the

moon has inspired the human mind to wander

in search of tributes and tales. From the rising

and falling of the tides to countless folklores of charms

and night creatures, the moon has been a staple in many

scientific and literary discourses. The same level of interest

applies to the field of agriculture where many farmers

have designated the various phases and faces of the moon

as indicators for a successful cropping or an impending

disaster.

Present-day lunar enthusiasts have tried to put a

semblance of logic to the value of the moon in agriculture.

It is claimed that all water on earth, from seas and rivers

to underground sources, are affected by the moon’s

gravitational pull. As the moon gets bigger during its

waxing phase (1st to 2nd quarter), water is said to rise

and become more available for plant growth. During its

waning or decreasing phase (3rd to 4th quarter), the water

table is said to recede. Practitioners of the art therefore

recommend that crops that need more water should be

planted during the waxing phase while crops that thrive

in dry conditions should be planted during the waning

phase.

Some sense could be gleaned from the above

premise but prudence is best to be exercised. One should

realize that the lunar cycle is completed every 27.3 days,

with each of the waxing and waning phases lasting for

only a couple of weeks. A simple review of the physiology

of major economic crops like corn and rice would show

that a typical cropping season extends from 90–120 days.

Both the increasing and decreasing phases of the moon

are therefore repeated 3–4 times during the whole

cropping season. The problem of attribution then

becomes a concern.

An article published in the web quoted John

Teasdale, the director of the United States Department of

Agriculture’s (USDA) Agricultural Systems Laboratory in

Maryland, saying, “he is not aware of any research on lunar

influences in agriculture, but a simple hypothesis is that

lunar cycles could influence meteorological cycles which

in turn could influence crops.” Again, it seems reasonable

that if the moon is strong enough to influence ocean tides,

then it must in some way also affect the atmosphere.

Earth and Sky Communications, an internet-based

organization, explained the problem with this hypothesis

by focusing on science. They say that the combined gravity

of the sun and moon does pull both air and water as the

planet rotates, creating tides in both the earth’s oceans

and atmosphere. However, recorded levels of air tides are

very insignificant near the earth’s equator where tidal

effects are supposedly at their strongest. The tidal effect

increases air pressure by only a fraction of one percent,

too insignificant to impact local weather.

Though claims of significance are easily validated

through science, the moon’s romance with the farmers’

psyche has been ongoing for hundreds of generations.

Most ancient civilizations had their own versions of lunar

calendars where they based their cropping and

40 SCF Folio

agricultural cycles. In Asia alone, the Chinese, Japanese,

and Korean people have their respective traditional

moon-based calendars. The sociocultural connection

between the moon and the Asian people is indeed very

evident.

In the Philippines where traditional beliefs and

values are very much alive, the moon serves as

foundation for many indigenous agricultural practices.

A simple survey in the country’s corn-growing provinces

proved that farmers still give high regard to the stages

and characteristics of the moon when commencing

farm operations and interpreting climatic happenings.

Indeed, it is hard to put sense and exact value to

the relevance of the moon in agricultural operations.

But it is easy to see that the influence of this radiant

heavenly body on the psychology of agricultural

workers rivals its impact on the changing tides. This

knowledge is worth a lot when dealing with farmers

and pushing for agricultural reforms. (SCF Project

Updates, March 2007)

Lessons from the Lopez calendar

If the Chinese, Japanese, Thais, and Koreans have their traditional lunar-based agricultural calendars, the Filipinos have the KalendaryongTagalog or the Don Honorio Lopez calendar.

Written more than a century ago by Don Honorio Lopez, a native of Manila, Kalendaryong Tagalog chronicles the lunar cycle andmovements of the tides. It gives advice on a wide range of topics—from the most mundane like mannerisms and good conduct to the mostprofound like economic and political concerns. The publication is also a good record of religious events and other significant happeningsin the country and enumerates notable names within religious and social circles. Up until now, Filipino babies are being named after thesaints and personalities enumerated in the pamphlet.

Kalendaryong Tagalog was never just an ordinary calendar depicting the days and events of the year. Since its publication in 1898,the 40-page pamphlet instantly gained popularity and a lot of loyal following. For most part of the past century, Kalendaryong Tagalogserved as a bible for many rural farmers and fisherfolks. Not a few Filipino families allowed the publication to dictate their lives andactivities. There was a time when most rural farmers consulted the calendar on the best time to work the land and plant crops.

Perhaps the most notable accomplishment of Kalendaryong Tagalog is its longevity and impact on the local farming community. Atpresent, many farmers from Luzon to Mindanao still base their cropping decisions on the calendar. Regardless of climate forecasts, manycrop growers still religiously follow the recommended plowing and planting dates indicated in the publication.The situation is remarkable yet alarming at the same time. It seems unsound that farmers would prefer traditional ways over science,especially in an age where advancements in technology give man the ability to look at the inner workings of the atmosphere and forecastclimatic anomalies. The Filipino farmer needs to have a more reliable and systematic guide in his farm activities.

Through Kalendaryong Tagalog, Don Honorio Lopez addressed a legitimate societal need and succeeded in immortalizing hisname and ideas in the process. The challenge for present-day scientists and extension workers is to do the same and effectively imbed theculture of science among local farmers. A reliable science-based option would bring farmers to a more enlightened plane and boost theirproductivity to greater heights.

Are seasonal climate forecasts valuableto farmers in Central West NSW?Jason Crean, Kevin Parton,and Randall Jones*

C limate variability is a major source of

uncertainty to farmers in Australia. Recent

advances in the understanding and

predictability of interannual climatic variations have led

to renewed interest in the value of seasonal climate

forecasts (SCFs).

Past studies of the value of SCFs in Australia have

focused on the management of single crops rather than

farms and have tended to concentrate on the cropping-____________* Postgraduate research student, University of Sydney; Professor,Charles Sturt University; and Senior Research Scientist, NSWDepartment of Primary Industries, respectively.

41

dominated regions of northern New South Wales (NSW)

and southern Queensland.

One of our Australian case studies attempts to shed

light on whether SCFs are of practical value to mixed

farming systems typical of central and southern NSW. We

use a whole farm analysis to assess the value of SCFs to

improve decisions about crop and livestock mix as well

as the choice of crop fertilizer inputs at sowing.

ApproachIn order to have value, SCFs must lead to a different crop

and livestock mix or a different level of crop fertilizer

inputs. Value arises from decisions which either reduce

losses associated with expected adverse climatic

conditions or take advantage of expected good climatic

conditions.

A representative farm model for the Central West

region was used to assess the outcomes of decisions taken

with and without SCFs. The model captures some of the

whole farm interactions, resource limitations, and other

influences that may affect the value of SCFs. It uses

biological outputs from a crop simulation model to

determine the optimal area of crops and pasture to grow

and the optimal level of fertilizer to apply.

The Agricultural Production Systems Simulator

(APSIM) simulated crop yields for a period of 92 years,

under three starting levels of soil moisture and four

nitrogen application rates.

The climate forecast system assessed in this study is

referred to as the ‘SOI Phase’ system. The phases give

credence to both the absolute value of the SOI and its

rate of change. Seasons in the historical record are

categorized into one of five phases based on two

consecutive monthly values of the SOI. The five phases

are as follows:

Phase 1 - SOI consistently negative (SOI negative)

Phase 2 - SOI consistently positive (SOI positive)

Phase 3 - SOI rapidly falling (SOI falling)

Phase 4 - SOI rapidly rising (SOI rising)

Phase 5 - SOI neutral (SOI neutral)

Phases 1 and 3 identified in late autumn are

associated with below average rainfall in the following

winter and early spring period in eastern Australia while

Phases 2 and 4 are associated with above average rainfall.

Phase 5 is the neutral phase and is associated with

generally average rainfall conditions over the same period.

To estimate the value of an SCF, we rely only on the

observed influence of the SCF on rainfall probabilities and

its correlation with crop yields.

The ‘without SCF’ case (fixed management) is based

on a single farm strategy that performs best in an average

year over all climatic years. In contrast, the ‘with SCF’ case

(flexible management) implements the best farm strategy

for a given forecast type (phase) based on the subset of

years of that phase type. The overall value of SCF is found

by comparing farm profits between fixed and flexible

management over the 92-year simulation period.

FindingsAverage returnsFarm profits with and without the SCF

under different levels of soil moisture are

shown in Figure 1. Farm profits improve as

the starting level of soil moisture increases.

The difference between the bars indicates

the gain in farm profit from forecast use.

Using the SCF at the lowest, moderate, and

maximum level of soil moisture improves

farm returns by 11.6 percent, 7.9 percent,

and 0.2 percent, respectively.

The SCF is found to be of most value

under low levels of starting soil moisture.

Low levels of starting soil moisture mean

that crop yields are more dependent on

in-season rainfall and, hence, better

Figure 1. Average farm profit with and without seasonal climate forecasts (SOI Phase)

42 SCF Folio

correlated to growing season

rainfall. Forecasts of lower

rainfall lead to decisions to

plant smaller crop areas and

lower fertilizer rates whereas

forecasts of higher rainfall

lead to larger cropping areas

and higher fertilizer rates.

At the highest level of

soil moisture, we find

practically no value from

SCFs. The reason is that only

one of the forecast categories

(SOI negative) leads to a

different decision and the

outcomes of that decision are

only a minor improvement

over not using the forecast.

Variability of returnsAs well as considering the average value of using SCFs,

farmers might also be concerned with the variability in

farm returns. Farm returns over the 92 years with and

without the forecast are ranked from lowest to highest

in the form of cumulative distribution functions (Figure

2). The curves indicate the maximum level of profit

obtained at a given level of probability.

The use of the SCF reduces the probability of

incurring a farm loss from around 20 percent to almost

zero. Losses are avoided because a more conservative

crop and livestock mix is adopted when dry conditions

are forecast (SOI negative and SOI falling). The benefit

of reducing farm losses in dry years does, however, come

at some cost of lower farm profits when better than

predicted seasonal conditions arise. At 2/3 soil moisture,

farm returns become more stable under the SCF as both

gains and losses are limited.

While farm returns can be less variable when

following a SCF, this will not always be the case. Under

the 1/3 soil moisture case, returns were sometimes

found to be more variable as the representative farm

reacted to forecasts of higher seasonal rainfall (SOI

positive and SOI rising). This led to an increase in crop

area in those years when forecasts of higher season

rainfall were issued. This lifted returns when the

favorable seasons predicted occurred but also resulted

in losses when the season was dry despite the forecast.

On average, however, farmers were much better off with

the SCF as the gains exceeded the losses.

ConclusionsClimate forecasts are valuable to farmers in Central West

NSW with the extent of value dependent on the level

of soil moisture at planting. When starting soil moisture

is low, both the level of crop production and the level

of economic returns are more reliant on in-season

rainfall conditions. Consequently, an accurate forecast

of in-season rainfall is more valuable when these

conditions exist.

There is a complex interaction between SCFs and

farm decisionmaking. At different levels of soil moisture,

forecast categories vary in their influence over farm

decisions and change the distribution of returns. In the

2/3 soil moisture case, the SCF led to more stable returns

whereas returns in the 1/3 soil moisture case were

slightly more variable.

SCFs have the potential to either enhance or

moderate income variability. Individual farmers will

have different attitudes toward these outcomes

depending on their level of risk aversion.

The overall economic value of SCFs can be

dominated by the value associated with following just

one or two forecast categories within that system. A

message from this is that farmers need to be conscious

of when to apply and when best to disregard the

information provided by SCFs. (SCF Project Updates, June 2007)

Figure 2.Distribution of farm profit – with and without SCF (2/3 soil moisture)

43

The influence of ENSO on frost riskin eastern and southeastern Australia

Bronya Alexander and Peter Hayman*

F rost can cause large losses in the yield of

agricultural crops in many areas of the world,

including much of Australia’s agricultural

regions. Frosts usually occur from late autumn (May) to

spring (October) in the Southern Hemisphere. In Australia,

frosts typically occur when a region is under the influence

of a high pressure system. This creates clear skies and a

dry atmosphere, and often very little wind—conditions

that are conducive to frost formation. A drier atmosphere

at night allows more heat to escape from the ground,

causing the air near the ground to be cooler. Whereas, if

there is moisture in the atmosphere, it helps to absorb

the escaping heat, keeping it close to the ground and

reducing the chance of frost.

Southeastern Australia has a winter dominant rainfall

pattern, so crops such as wheat and barley are sown mid-

late autumn or early winter, and generally flower around

spring. A plant is very susceptible to frost at the time of

flowering, so in frost-prone areas, you want your crop to

flower after the frost-risky season. Later flowering can be

achieved by sowing the crop later. However, the later you

sow, the less yield you are likely to get. Therefore,

managing frost risk is a balancing act between the crop

flowering too early and suffering frost damage and the

yield penalty from moisture and heat stress of the crop

flowering too late in spring. Ideally, grain farmers would

aim for their wheat crop to flower immediately after the

last frost in spring, but this date is highly variable. Figure 1

shows typical sowing and flowering periods with respect

to rainfall and minimum temperature for a cropping town

in South Australia.

Impacts from the El Niño Southern Oscillation (ENSO)

are most commonly associated with rainfall. However,

ENSO is also associated with temperatures and therefore

may influence the frost risk in Australia. The increased

frequency of clear skies and high surface pressures often

associated with El Niño conditions in Australia generally

mean less clouds, less wind, colder nights, and therefore

potentially more frosts. The following study was done to

investigate the effect of ENSO on the frequency of frosts,

and also on the date of the last frost for a number of

stations in eastern and southeastern Australia.

DataThe minimum temperature data used in this analysis were

patched point data from the Bureau of Meteorology’s SILO

website. These daily data consist of original measurements

from a particular meteorological station along with

interpolated data used to fill any gaps in the record. Data

from 1900–2005 were analyzed for the following eight

stations across eastern and southeastern Australia:

Figure 1. Mean monthly rainfall and minimum temperature for Snowtown in South Australia, 1900–2006

Note: Average rainfall and minimum temperatures across a year at Snowtown, South Australia are shown above. Also shown areperiods of time when sowing, flowering, and frost risk are common.

____________* Project Officer and Principal Scientist on Climate Applications,respectively, both from the South Australia Research andDevelopment Institute (SARDI).

44 SCF Folio

Emerald and Goondiwindi (Queensland); Gunnedah,

Wagga Wagga, and Deniliquin (New South Wales);

Mildura and Nhill (Victoria); and Snowtown (South

Australia).

To classify years as El Niño or La Niña, we have used

a list provided by the Bureau of Meteorology (Table 1).

Any year that does not appear as El Niño or La Niña

between 1900 and 2005 in this list was classified as a

neutral year by the Bureau.

GraphsThree types of graphs were analyzed. Figure 2 shows

the probability of there being a particular number of

days of frost [minimum temperature less than 2 degrees

Celsius (C)] per year at Snowtown, South Australia,

throughout the historical record from 1900 to 2005. Also

shown are the probability curves for El Niño, La Niña or

neutral years, as well as the curve created from the last

20 years of data.

Figure 3 presents the latest date of a frost each

year at Snowtown, i.e., the probability that the last frost

each year has occurred by the given date. Again, the

probability curves for the three ENSO classifications are

shown as well as the last 20 years. The final set of graphs

analyzed were again looking at the latest date of frost,

except that this time, a frost was defined as getting a

minimum temperature less than 0 degrees C.

DiscussionFrom Figure 2, it can be seen that there are generally

more frost days in El Niño years at Snowtown compared

to La Niña years. For example, in a La Niña year, 50

percent of the time, there are over 14 frost days, whereas

in an El Niño year, 50 percent of the time, there are over

18 frost days. This distinction between the frequency

of frost in El Niño and La Niña years was apparent in all

the locations looked at in this study. It is interesting to

also note from Figure 2 that the number of frosts in the

last 20 years was less than the historical average.

However, this observation was not consistent across the

other sites analyzed, with many showing average frost

frequencies over the last 20 years and two sites showing

an increase in frequency.

Figure 3 displays the latest date of a frost each year

at Snowtown, revealing little distinction between El

Niño and La Niña years, particularly in the latest 30

El Niño La Niña

1902 19031905 19061911 19091913 19101914 19161919 19171925 19241940 19281941 19381946 19501952 19551953 19561959 19641965 19701969 19711972 19731977 19741982 19751987 19881991 19961993 1998199419972002

Table 1. El Niño and La Niñayears as defined by theAustralian Government Bureauof Meteorology

Figure 2.Probability distribution of the number of frost days (less than 2 degreesCelsius measured at Stevenson Screen height) at Snowtown, South Australia

Figure 3.Probability distribution of the latest date of frost (less than 2 degreesCelsius measured at Stevenson screen height) at Snowtown, South Australia

45

percent of frosts. Similarly, most of the other sites analyzed

did not show much distinction between El Niño and La

Niña in terms of the latest date of frost, particularly for

the last 20–30 percent of the years. Graphs showing the

latest date of frost, where a frost was defined as less than

zero degrees Celsius were also analyzed. Many locations

showed some distinction with the last frosts more likely

to occur in El Niño years, but most still showed little

distinction for the latest 20 percent of frosts. Figure 3 also

demonstrates the wide range in the last date of a frost

from year to year. For example, the last frost (<2C) at

Snowtown has occurred anywhere between late July to

mid-November during the last century, highlighting the

challenge farmers face in managing frost risk.

It is the timing of the latest frosts that are useful to

know because they often hit unexpectedly, but it seems

that ENSO does not influence this enough to be of much

use in terms of forecasting potential. (SCF Project Updates,

June 2007)

It is the timing of the latest frosts that are useful to knowbecause they often hit unexpectedly, but it seems that ENSOdoes not influence this enough to be of much use in terms offorecasting potential.

A dry spell cast in Luzon

J une and July are usually rainy months in the

Philippines and are part of the rainy season. But in

June and July this year, a dry spell hit the country,

especially in many parts of Northern and Central

Luzon. According to meteorologists, this dry spell that

occurred during the normally rainy season months was

not just a local event. It was part of the global

abnormalities in weather and climate patterns.

What caused the dry spell?A number of factors contributed to the occurrence of the

dry spell recently experienced.

One was the persistence of the

ridge of high pressure area

toward Luzon which is usually

associated with warm and rain-

less weather. This was

accompanied by the

displacement of the

intertropical convergence zone

(ITCZ) to the south, instead of

the usual across-the-country

location. Another factor which

compounded the condition

was the absence of tropical

cyclones or typhoons in the

month of June and the lower-

than-normal number of

typhoons in July. In fact, only

one typhoon (compared to the

average number of 4) entered the Philippines’ area of

responsibility during this month.

Figure 1 shows the rainfall distribution for the

months of June and July, indicating the below normal

levels felt in most parts of Luzon, including Metro Manila,

leading to the dry spell condition.

The damaging consequencesThe prolonged dry condition left farmlands parched and

the Angat Dam, one of the major water dams which

supplies 97 percent of the water needs of Metro Manila

Figure 1. Rainfall distribution for the months of June and July 2007

46 SCF Folio

and most of the irrigation

requirements of farms in

Bulacan and some areas in

Pampanga, with a below-

critical level of water supply.

Consequently, this led to a

scarcity in the domestic

water supply, especially in

Metro Manila, and crop

failures in many areas in

Central Luzon due to the

reduced irrigated areas.

Figure 2 shows the areas

badly hit by the dry spell. In

addition, the incidence of

fires and certain health

problems rose.

For the agricultural

sector, the prolonged dry

condition slowed down

productivity due to delays in planting and harvesting,

setting the farmers’ production outputs back by one to

two months. As a result, for the first half of 2007,

agricultural growth slowed down to 3.5 percent as

compared to the 5.4 percent growth recorded over the

same period in 2006. Corn shortages of about 1 million

metric tons were also recorded while rice production

losses of about 400,000 metric tons were estimated. In

sum, about PhP1.14 billion worth of agricultural

damages were estimated as a consequence of the dry

spell.

What were some of the responses?A number of mitigating measures were instituted by

various government agencies to help address the

adverse consequences of the dry spell.

On the supply side, directives on optimum water

allocation and utilization were issued by national water

resources agencies; water supply distribution was

Figure 2.Areas affected by dry spell

instituted; repair of dikes and other impounding

infrastructures was ordered; small water impounding

projects were adopted; and cloud seeding operations

in some areas in Metro Manila, Cagayan Valley, and

Central Luzon were undertaken, among others. On the

demand side, meanwhile, water conservation was

encouraged among the public; use of resistant crops

requiring less water and of early maturing varieties was

adopted; and energy conservation was observed in

various public offices.

In addition, other government bodies led by the

country’s national meteorological agency, the PAGASA,

and the Department of Science and Technology (DOST)

conducted an intensive information, education, and

communication (IEC) campaign for Dry Spell Vulnerable

Areas. The objective was to raise public awareness on

the effects of the dry spell and to build the capacity of

the local chief executives, the constituents, and the

media in communities under or vulnerable to said dry

spell condition to assess their current situation.

Hopefully, they will have a better understanding of the

weather and climate advisories issued by PAGASA, and

will be able to recommend and set up necessary

mitigation measures to address the impact of the dry

spell. The target areas of this IEC drive include 22

provinces in five regions of Luzon (Regions 1, 2, 3, 4, and

the Cordillera Administrative Region). (SCF Project

Updates, September 2007)

The objective of the IEC campaign for Dry Spell Vulnerable Areaswas to raise public awareness on the effects of the dry spell and tobuild the capacity of the local chief executives, the constituents, andthe media in communities under or vulnerable to said dry spellcondition to assess their current situation. Hopefully, they will havea better understanding of the weather and climate advisories issuedby PAGASA, and will be able to recommend and set up necessarymitigation measures to address the impact of the dry spell.

47

A model for valuing seasonal climate forecast

The losses and setbacks in agricultural production

experienced recently by many farms in Luzon due

to the dry spell that hit the country last June and

July raise the question on whether such losses could have

been reduced, if not totally prevented, had farmers

adjusted their production activities accordingly with

advanced information given them on the possible onset,

timing, and duration of the dry spell.

In the first place, too, do farmers and other

agricultural decisionmakers get advanced information or

climate forecasts regarding the coming of seasonal

climate phenomena like El Niño, La Niña, dry spell or wet

spell?

And how much is it worth to a farmer in terms of

“saved” or increased incomes/revenues if he indeed has

these seasonal climate forecasts (SCFs) and makes good

use of them?

In the joint Australian-Philippine project titled

“Bridging the gap between seasonal climate forecasts and

decisionmakers in agriculture” sponsored by the

Australian Centre for International Agricultural Research

(ACIAR), one of the objectives is to determine, through

case studies and surveys, if a farmer gets the right

information about the onset of seasonal climate

phenomena like the El Niño Southern Oscillation (ENSO)

phases (El Niño and La Niña) at the appropriate time and

if he does, whether or not he makes use of them and

incorporates them in his decisions affecting crop

production and choices.

Assuming that the farmer incorporates the

information in his decisionmaking, what economic value

does he gain, if any? With the additional information, does

he have more options to choose from? Does it give him

additional income? Does it reduce his potential losses vis-

à-vis a situation where he has no such information about

the onset of these climate occurrences?

In order to answer these questions, Dr. Canesio Predo

and Ms. Zyra May Holmes of the Visayas State University

(formerly Leyte State University) adopted

an economic valuation framework that

builds on the expected utility theory and

decision tree analysis but employs an

alternative approach in measuring and

estimating the value and utility of SCFs in

the context of farm level cropping

decisions. Predo and Holmes applied the

framework in their Philippine case study

areas for the seasonal climate forecasts

project in Bohol and Leyte.

The model, as seen in Figure 1, looks

at farming decisions under two scenarios,

namely: (a) without SCFs, and (b) with SCFs.

For both scenarios, crop simulation

models are required to be calibrated with

corn farming systems’ input parameters,

e.g., biophysical data, input requirements,

prices, etc. Simulation outputs are also

generated to come up with the crop

yields under various ENSO phases such as

Figure 1. Economic valuation framework used in the study

The losses and setbacks in agricultural production experiencedrecently by many farms in Luzon due to the dry spell that hitthe country last June and July raise the question on whethersuch losses could have been reduced, if not totally prevented,had farmers adjusted their production activities accordinglywith advanced information given them on the possible onset,timing, and duration of the dry spell.

48 SCF Folio

El Niño, La Niña, and neutral years as noted in Figure 1.

However, to generate crop yields under different ENSO

years, complete historical daily climate data such as

rainfall, solar radiation, minimum and maximum

temperatures, among others, are required.

Because these data are not, however, available (or

incomplete during the time of analysis) in the Philippine

case study areas, Predo and Holmes decided to employ

an alternative approach through the use of experts’

opinions/observations and farmers’ practices regarding

corn yields during dry years (El Niño), wet years (La Niña),

and normal years (neutral years). For each category of

ENSO years, farmers were asked to provide corn yield

estimates during good, average, and poor seasons.

Using these data, the stochastic decision tree

analysis within the framework of expected monetary

value or expected payoffs of the crop choice was

estimated and valued.

To see what the additional value of the information

to be provided by the forecasts or the SCFs (amount of

rainfall, timing of rainfall events, frequency of rainfall)

would be or what value any revision in a farmer’s prior

decision (when he had no forecasts) would be, the

RAINMAN international software package, developed

under a previous ACIAR project, was used to provide

the probability of a good, average, and poor season

based on the Southern Oscillation Index (SOI) system

of forecasts. The stochastic gross margin for the

outcome of each season was calculated using the

SIMETAR software to generate the cumulative

distribution function of the expected value of crop

choice for both “with SCF” and “without SCF” scenarios.

The value of the SCF is derived as the difference

between the expected value of choice with forecast and

the expected value of action without forecast.

With this model/framework, it would thus be

possible to calculate the value in peso terms for the

farmers regarding the use of climate forecasts in making

production decisions. (SCF Project Updates, September 2007)

Peso value of SCF use in Bohol Province

In an economic assessment of seasonal climate forecast (SCF) use in corn production decisions of farmers in BoholProvince as conducted by Ms. Zyra May Holmes and Dr. Canesio Predo of the Visayas State University (VSU), the authorscalculated the economic value of using SCF for corn cropping system to be around PhP51.22/ha/season. This is based onthe summary statistics of simulated results showing that the stochastic net returns of cropping choice without SCF rangedfrom PhP2,084.47 to PhP2,837.63/ha/season with a mean of PhP2,439.31/ha/season. With SCF forecast, the stochasticnet returns ranged from PhP2,119.24 to PhP2,934.21/ha/season with a mean of PhP2,490.53/ha/season.

While the amount may be considered too minimal for individual smallholder corn farmers to change their croppingdecision, the figure, however, is significant enough if the total corn-producing area of Bohol Province is to be considered.

The authors made the calculations using the economic valuation model that they adopted (see feature on the Model).

Valuing SCF use for corn farmers in Leyte

Using the same model as the one they used in their case study in Bohol Province, Ms. Zyra May Holmes and Dr. CanesioPredo of the Visayas State University (VSU) estimated the economic value of using SCFs in corn farming areas in Mahaplagand Matalom municipalities in Leyte Province to be PhP119/ha/season. A forecast was found to be valuable in decidingwhen to plant corn. A forecast has value if the “with forecast “ scenario leads to different decisions and improved outcomesover those in the “without forecast” scenario. In the Leyte case study sites, the authors found that there was indeed valueas shown in their resulting estimates.

To see what the additional value of the information to be providedby the forecasts or the SCFs would be or what value any revisionin a farmer’s prior decision would be, the RAINMAN internationalsoftware package, developed under a previous ACIAR project,was used to provide the probability of a good, average, and poorseason based on the Southern Oscillation Index (SOI) system offorecasts...With this model/framework, it would thus be possibleto calculate the value in peso terms for the farmers regarding theuse of climate forecasts in making production decisions.

49

And on rice crop...

Nueva Ecija farmers favor SCF over traditionalforecasting methods

Although they were aware of some indigenous

forecasting methods, most of the rice farmers

in two municipalities of Nueva Ecija have faith

only in the seasonal climate forecasts (SCFs) provided by

PAGASA.

This was the result of a survey conducted by PhilRice

researchers among 120 farmers in Talugtug and Lupao,

Nueva Ecija. The farmers served as participants in the

study that aims to assess the potential farm-level value of

SCF for rice-based farming systems in Central Luzon,

Philippines.

Both of the study sites are rainfed, flood plain

belonging to the upper vega. Rice farmers plant only

during the wet season and some farmers use

supplementary irrigation sourced from deep well, small

farm reservoir, and shallow tube wells.

Random sampling was used to identify respondents

based on the list of samples taken from the municipalities’

Agriculture Offices. Of the 120 respondents, 60 were taken

from each of the two municipalities.

Most of the respondents were male (83%), married

(89%), and with an average age of 50 years. Their average

number of years in rice farming was 25.

Ninety-six percent of the farmers considered climate

in their farm planning and decisionmaking. They also

opined that early climate forecasts would help in their

decisionmaking. However, the result of the survey also

shows that most of the farmers do not have mitigation

measures and risk-coping mechanisms in times of calamity.

More than half of the respondents (74%) said that

they were satisfied with the climate-related information

that they have been receiving. As to the sufficiency and

correctness of the information they received, 66 percent

claimed that they received sufficient information while

47 percent said that the climate-related information that

they received was correct.

Farmers also said that most of the climate advisories

that they received were on typhoons and El Niño, with

their main sources of information coming from radio and

television. (SCF Project Updates, September 2007)

Looking for options amidst seasonalclimate variability

T he vulnerability of agriculture to the

unpredictability of nature is an age-old riddle,

which has left even the wisest of men without

answers. In most cases, people are given no other recourse

but to adapt to environmental happenings and make do

with what they have. In the Philippines where agricultural

production represents a major source of livelihood for

many rural people, the pressure to do better amidst

seasonal climatic variability is immense.

Scholars claim that climatic variability has great

socioeconomic consequences and would worsen the

disparity between the rich and poor. With more than 90

percent of local agricultural workers classified as

smallholders, many could not afford a failed season of

cropping. Measures to address this concern should

therefore be multidimensional—tackling both physical

and welfare issues. Safeguarding the livelihood and

interests of local farmers entails concrete action in the

social, economic, and political fronts.

A major cause of the climatic variability and

catastrophes being experienced in the country is the El

Niño Southern Oscillation (ENSO) phenomenon. ENSO

shows its destructive face through two major phases: the

El Niño or warm event and the La Niña or cold event. El

50 SCF Folio

Niño conditions generally lead to drier seasons due to

suppressed tropical cyclone activity and weak monsoon

characterized by delayed onset, dry periods, and short

monsoon season. In contrast, La Niña is characterized

by above normal rainfall and longer rainy seasons.

The destructive power of ENSO was clearly

documented during the 1997–1998 El Niño/La Niña

episode when a total of PhP7.6 billion in rice and corn

production losses were incurred. Greenpeace (2007)

also estimated that from 1975 to 2002 alone,

intensifying tropical cyclones in the Philippines have

caused an average yearly damage to property of PhP4.5

billion with agricultural damages reaching as high as

PhP3 billion. The organization further claimed that the

Philippines, like the rest of the region, would likely

continue to experience extreme climatic variability as

manifestation of the impact of climate change.

Nature’s challenges are daunting for everyone

concerned. Farmers with their meager resources and

traditional ways have been trying to adapt and survive.

National and local governments, nongovernment

organizations (NGOs), and other institutional bodies/

stakeholders are doing their part but further

consolidation of efforts is needed. Among the measures

that the Philippine government has come up with to

assist farmers in the face of seasonal climate variability

are price stabilization measures, typhoon and/or

drought relief, livestock and feed subsidies, farm input

subsidies, agricultural credit, and subsidized crop

insurance schemes.

Indeed, the identified problems and issues due to

climatic variability also present opportunities for

interventions. But most important to consider

in any development effort is the suitability of the

intervention to the needs and situation of the

target population. Not a few development

initiatives have failed because of mismatch

between the help offered and what was

required in the field. The best way to proceed

then is to do situational analysis and extract from

the target clientele the types and kinds of

assistance that are needed and preferred.

Decades of agricultural support, risk

mitigation, and relief efforts have resulted to

some degree of success, but a more lasting and

sustainable solution is yet to come. Studies done

under the ACIAR-funded project “Bridging the

gap between seasonal climate forecasts (SCFs)

and decisionmakers in agriculture” characterized the

target farmer populace and put value to SCFs and other

possible interventions. Surveys among rice and corn

farmers in key producing municipalities made it

apparent that the sector still needs much assistance.

General farm productivity needs to be improved, farms

are still very vulnerable to damages brought about by

floods, drought, and typhoons, and many farmers are

up to their necks in debt. There are a number of possible

entry points for development interventions that the

surveys identified. Among the most preferred by

farmers are provision of better climate information,

accessible credit, crop insurance, and special assistance

programs.

Individually, farmers could decide to work with a

number of on-farm mitigating measures like proper

timing of planting, use of appropriate crops and crop

varieties, and establishment of on-farm supplementary

irrigation systems, among others. The range of

applicable tools, however, is usually subject to the

availability of information and resources and their

openness to interventions.

A lot could be done to alleviate the plight of

smallholder farmers and help increase their capacity to

cope with shocks and environmental stresses. The

specific interventions, though administered individually,

should complement, justify, and strengthen each other.

Ultimately, the smallholder farmer should end up with

appropriate tools and increased capacity to better deal

with the challenges offered by seasonal climate

variability. (SCF Project Updates, December 2007)

51

Security against climate variabilitythrough agricultural insurance

Experts agree that agricultural insurance is one of

the best ways to address the adverse impacts of

seasonal climatic variability and secure the welfare

of smallholder farmers. Designed to protect agricultural

producers against loss due to natural calamities, pests, and

other risks, agricultural insurance has a lot of potential

benefits especially in the Philippines where climatic and

other environmental uncertainties are of great concern.

Agricultural insurance in the country is implemented

and managed by the Philippine Crop Insurance

Corporation (PCIC). Although the government subsidizes

insurance for rice and corn, the PCIC operates as a business

corporation and does not receive any budget from the

government for its administrative operations.

Rice and corn insurance constitute about 84 percent

of PCIC’s total business. From 1981 to 2007, the program

was able to serve a total of 3,468,155 farmers, insuring a

total sum of PhP31 billion. Total gross premiums received

during the period exceeded indemnities paid at a ratio

of 1.27:1. Earlier, however, the PCIC had a rough time

during its first decade of operation when damage claims

consistently surpassed premium collections from 1983 to

1989. The program had its highest accomplishment

during the early part of the 1990s when it reached its peak

coverage at 336,000 farmers.

Seasonal climate variability proved to be the top

source of uncertainty for rice and corn farmers. Overall,

typhoons and floods were the major causes of production

damage for rice while drought was the number one cause

of loss for corn. Claims on rice insurance from typhoon

and flooding totaled PhP1.050 billion from 1981 to 2007.

Claims on corn insurance caused by drought amounted

to PhP258 million from 1982 to 2007.

The PCIC attributes an aggregate amount of PhP1.7

billion in rice and corn crop insurance claims to damages

from typhoons/floods and droughts. This figure

represents 66 percent of the total indemnity paid by PCIC

for all insured commodities covering all causes since the

start of its operation. This effectively describes the impact

of seasonal climate variability on crop insurance

operations and agricultural productivity as a whole.

Bridging SCF with agricultural insurance use could

possibly soften the damage figures.

While agricultural insurance has earned its place in

the government’s risk management portfolio, program

implementation is greatly hampered by a number of

concerns. In the Philippines and in many parts of the

developing world, harnessing the potential benefits from

the scheme is constrained by operational and

sustainability issues.

In a recent PIDS-led survey conducted in Isabela,

Philippines, for instance, it was found that formal lending

institutions and crop insurance were virtually nonexistent

in select farming communities. Insurance service is also

inadequate in many other key agricultural production

areas. Data from the PCIC showed that program coverage

drastically declined after reaching its peak in 1991. By year

2001, the number of covered farmers leveled off just

below the 50,000 mark. PCIC closed the year 2006 with

barely 36,000 farmers covered.

Estacio and Mordeno (2001) attributed the decline

in insured farmers to the contraction of the self-financed

market program and the shrinking of directed credit

programs which automatically availed of insurance

coverage. PCIC also claimed that with the borrowing

farmers dominating the traditional lines, the

decreasing trend on crop insurance coverage greatly

reflected the lending performance of formal lenders,

particularly the Land Bank of the Philippines (LBP)

which accounted for 77 percent of its clients.

As it is right now, agricultural credit and

agricultural insurance are intertwined. If the

insurance program is not allowed by law to impose

Table 1. Cumulative insurance coverage and claims paid for riceand corn from 1981 to 2007

Insurance Insurance Coverage Claims PaidLines No. of Farmers/ Sum Insured No. of Farmers/ Claims Paid

Policies Written (PM) Policies Paid (PM)

Rice 3,010,929 26,437.23 845,812 1,960.54Corn 457,226 5,011.11 189,548 611.22

TOTAL 3,468,155 31,448 1,035,360 2,572

Source: PCIC 2007

52 SCF Folio

commercially competitive rates and profit from

smallholder farmers, then the program has no choice

but to stick close to formal lenders and avail of subsidies.

But still, the market for borrowing farmers is big enough

for PCIC to create waves and generate significant

impact. The program just has to find creative ways to

expand its share of the market.

International development organizations have

been claiming that traditional crop insurance schemes

like the one in the Philippines are plagued with inherent

problems. The common ones are problems in

information asymmetry, adverse selection, moral hazard,

and high administrative and

transaction costs. Information

asymmetry refers to the unequal

information available to insurers and

clients; adverse selection refers to

the noninclination of low-risk

farmers to buy insurance; moral

hazard relates to a farmer’s

inclination not to do enough to

avoid or minimize loss; and high

administrative and transaction costs

refer to the huge expense in

marketing, calculating, and

collecting individual premiums and paying claims.

If the agricultural insurance program is to survive

and become operationally sustainable, it will have to

operate as an economically viable unit. Efforts must be

made to streamline the program’s operation and install

a more aggressive marketing component. It may be

wise to explore emerging innovative insurance

schemes like index-based and market-based insurance

products. Ultimately, the PCIC and the Philippine

agricultural insurance program must go after its

mandated target market with more efficiency and

determination. (SCF Project Updates, December 2007)

Augmenting resources of smallholderfarmers through agricultural credit

Lack of capital limits most smallholder farmers

from achieving greater farm productivity. The

presence of formal and informal lenders in the

rural financial scene serves a critical purpose and

ensures that farmers are able to meet their operational

and household needs.

Formal lenders include commercial banks, thrift

and development banks, rural banks, and credit

guarantee institutions. Informal lenders, on the other

hand, include traditional moneylenders and credit

organizations/groupings.

On the part of the government, the Agricultural

Credit Policy Council (ACPC) oversees agricultural credit

and helps develop and implement strategies and

policies designed to increase and sustain the flow of

credit to agriculture and fisheries, improve the viability

of farmers and fisherfolk, and support agriculture

modernization, food security, and poverty alleviation.

Government banks like the Land Bank of the Philippines

(LBP) and the Development Bank of the Philippines

(DBP) are also key players in rural credit. LBP is the most

active bank in agricultural credit while DBP also

provides credit to agriculture and small and medium-

scale industries. QUEDANCOR or the Quedan and Rural

Credit Guarantee Corporation, a semigovernment

entity, also supports farmers and rural enterprises and

is tasked to accelerate the flow of investments and

credit resources into the countryside.

While government and private banks have been

providing agricultural credit, informal lenders have

53

been dominating the

rural lending scene for

decades. Data from the

Bangko Sentral ng

Pilipinas (BSP) prove

that majority of farmers

go to informal lenders

for their credit needs

and although informal

lending decreased by 16 percent from 1996 to 2002, its

hold on the credit market is still formidable at 60 percent.

The risk averseness of formal banks when it comes to

targeting clients makes it hard for them to fully venture

into the rural financial market.

Seasonal climate variability, aside from increasing

risks in agricultural operations, further decreases the

attractiveness of farmers to formal lenders. Extreme

climate/weather events like floods, droughts, and

typhoons could easily destroy a season’s crop and erode

whatever financial capacity farmers have. Available figures

on damages to agriculture from extreme climatic events

are staggering. With local and international

meteorological organizations predicting that the

occurrence of ENSO and other extreme climatic events

would be more frequent and intense, the future does not

seem to be more attractive to formal bank ventures. In

contrast, informal lenders are able to capitalize on these

events since they are still able to earn through collateral

substitution even when farmers’ crops fail.

The small presence of formal banks/creditors in the

rural scene has opened up opportunities for informal

entities to grow and fill in this void. The ability of informal

lenders to adapt to local requirements sets them apart

from their formal counterparts. High transaction costs as

well as high loan risk impair the ability of formal banks to

operate cost-effectively under a rural set-up. Their rigid

credit requirements also do not go well with the rural

setting. If formal

institutions are to

regain a substantial

portion of the credit

market, they will have to

adopt some flexibility.

One way of doing

this is to accept

substitute collaterals.

Informal lenders have long been exploiting this

alternative by accepting pawning of cultivation rights,

required sale of output to trader-lenders, joint liability or

having a guarantor to back up the loan, mutual guarantee

by group members, interlinked contracts, and

government guarantee (Llanto 2004). In short, formal

institutions need to evolve if they are to fare well in the

rural credit market.

Another possible workable arrangement is shown

in the government’s attempts to partner with informal

lenders in rural credit delivery. QUEDANCOR, for instance,

has tapped traders and millers with access to traditional

banking as credit intermediaries. Guarantees were given

to these traders and millers who, after obtaining bank

loans, provided credit to their small farmer clients in turn.

The LBP was also motivated to use NGOs and cooperatives

as credit intermediaries to deliver credit to numerous

small borrowers. Practical arrangements like these should

be considered more seriously to take advantage of the

strengths of the informal lending sector.

A promising development is the present popularity

of alternative lending schemes like microcredit.

Microfinance institutions (MFIs) may charge market-

oriented interest rates, enabling them to recover costs and

allowing their operations to get a semblance of

sustainability. NGOs have also pioneered the use of

lending techniques that draw inspiration from the

informal moneylenders like the use of third party

guarantees, timely processing and quick release of loans,

and lending without requiring traditional collateral,

among others (Llanto 2004).

In sum, more efforts must be exerted by concerned

parties to make the operation of formal institutions in the

countryside more attractive and viable. Alternative

modalities like microfinancing present great potential in

bringing better credit service to the countryside. (SCF

Project Updates, December 2007)

Seasonal climate variability, aside from increasing risks inagricultural operations, further decreases the attractiveness offarmers to formal lenders. Extreme climate/weather events likefloods, droughts, and typhoons could easily destroy a season’scrop and erode whatever financial capacity farmers have...Incontrast, informal lenders are able to capitalize on these eventssince they are still able to earn through collateral substitutioneven when farmers’ crops fail.

Table 1. Borrowing by major source of loans, 1996–2002

Source 1996–1997 1999–2000 2001–2002

All borrowers 100.0 100.0 100.0Formal institutions 24.0 28.6 34.4Informal lenders 76.0 61.3 60.3Formal and informal lenders 5.3

Source: ACPC 2002

54 SCF Folio

Addressing farmers’ needs throughother special development programs

The importance of rice and corn to the economy

and welfare of many Filipinos as well as the

immense challenge in improving productivity

justifies government intervention through special

programs.

A snapshot of the rice and corn industries shows

both promise and despair. With an average annual

national production of 11.20 million tons (MT) for rice

and 5.25 MT for corn, the Philippines incurs yearly

production deficits of 1.5 MT and 1.33 MT for rice and

corn, respectively (PCARRD 2005, Lantican 2004, BAS

2006). The country fills this supply gap through

appropriate importation from neighboring countries.

Farmers and industry people could cash in on the

unmet demand through greater productivity and more

efficient trade.

A little over 4 million hectares are planted to rice

while another 2.5 million hectares are planted to corn.

Lantican (2004) estimated that for the Philippines to be

self-sufficient in its grain requirements, productivity for

both crops should be raised to at least 3.80T/ha. Salazar

(2003), on the other hand, deduced that given an annual

population growth rate of 2.2 percent and an estimated

rice consumption of 105 kg per person per year, the

country will need to produce 21 MT of rice in 2025 and

34 MT in 2050 to feed about 123 million and 203 million

people, respectively.

Adequate farm inputs and irrigation water are

necessary if greater productivity and higher areas

planted to crops, especially rice, are to be targeted. This

is very much true for rice where increased yield would

entail proper irrigation support. Corn, on the other hand,

could survive in less developed agricultural lands and

thrive exclusively on rainfall. Better corn productivity,

however, could be had if water during the crop’s critical

growth stages could be assured.

Various types of assistance are being offered by

the government to rice and corn farmers. For example,

subsidies on seeds and other inputs, irrigation

development, credit facilitation, crop insurance, farm-

to-market roads, capacity building through technical

assistance, training and extension, postharvest

development, and price support, among others, are

being made available by government to farmers.

Among these interventions, seed subsidy during

calamities and irrigation development were mentioned

by interviewed farmers as most needed and relevant

in coping with seasonal climate variability.

To help small farmers meet the high cost of inputs,

the government, through the Department of

Agriculture (DA), implements programs that subsidize

the price of hybrid and inbred seeds for rice; and hybrid

and open pollinated varieties for corn. The seeds are

provided during regular season to increase farm

productivity, and at times during postcalamity relief to

aid in the rehabilitation and replanting of damaged

farms. Two umbrella programs within the DA, the

Ginintuang Masaganang Ani (GMA) Rice Program and

the GMA Corn Program cover the implementation of

the seed subsidy programs.

Input subsidies such as provision of seeds for rice

and corn farmers are of big help to many. However, the

cost-effectiveness of this intervention must be studied

more carefully. Billions have already been incurred by

the government in providing highly subsidized hybrid

and inbred seeds, without the benefit of seeing

dramatic productivity improvements and social

benefits. Provision of seeds as part of relief assistance

to areas damaged by drought/flood/typhoon, though,

is commendable and necessary especially for

subsistence farmers.

For irrigation support, the National Irrigation

Administration (NIA) operated and maintained national

irrigation systems (NIS) servicing around 972,692 ha in

the year 2005. This consisted of 496,242 ha for wet crops

and 476,450 ha for dry crops. The total irrigated area by

Communal Irrigation Systems (CIS) totaled 558,598 ha

comprising of 291,891 ha during wet season and

266,707 ha during the dry season. All in all, NIA (2006)

estimated that the total irrigated area in both wet and

dry seasons for NIS and CIS is 1,531,290 ha.

As of 2007, the Bureau of Soils and Water

Management (BSWM) also reported the construction

of a total of 1,399 small water impounding projects

55

(SWIPs), 22,282 small farm reservoirs (SFRs) and 30,728

shallow tubewells (STWs). These are classified as small-

scale irrigation systems, with each structure servicing only

limited farm areas. Average service areas for the systems

are 55 ha for SWIP, 1–2 ha for SFR, and 3–5 ha for STW.

Though relatively limited in coverage, small scale irrigation

systems have lower investment cost per hectare, and most

could be developed by private persons or entities.

As mitigating measure against climatic aberration

like droughts and floods, irrigation facilities serve both as

water reservoir and drainage. There are, however,

limitations. During times of drought, for instance, the

service areas of NIA-administered systems are drastically

cut. The tail-end portion of serviced farms often

experience water shortages during prolonged dry spells

or sometimes even during regular dry season. The

situation entails the use of supplementary water sources

such as on-farm reservoirs or other small-scale irrigation

systems.

Agronomists agree that irrigation support for rice is

necessary if greater productivity is to be desired. However,

the cost involved in establishing, rehabilitiating, and

managing irrigation systems is staggering. PCARRD (2005)

estimated that the cost of just rehabilitating existing

irrigation facilities is about P100,000 to P150,000 per

hectare with an operation cost of P2,000–3,000 per

hectare per year. As most irrigation facilities in the country

service only rice, it may be wise to look into diversification,

specifically into the possibility of providing irrigation to

more high-value crops/commodities. Another option is

the establishment of small-scale irrigation systems, which

cost much less per hectare as compared to national and

communal irrigation systems.

The need to help rice and corn farmers is ever

pressing, especially given problems on seasonal climate

variability. Government programs on input subsidy and

irrigation support serve a very good purpose but

prudence should also be exercised in ensuring the cost-

effectiveness and sustainability of any development

intervention. (SCF Project Updates, December 2007)

The need to help rice and corn farmers is ever pressing,especially given problems on seasonal climate variability.Government programs on input subsidy and irrigationsupport serve a very good purpose but prudence should alsobe exercised in ensuring the cost-effectiveness andsustainability of any development intervention.

Evolution of the 2007–2008 La Niñaepisode and the climate scenario

In July 2007, signs of an evolving La Niña episode

were already confirmed which later developed into

a full-blown La Niña, albeit a weak one, in September

2007. This then reached its maximum strength in February

2008. By May 2008, though, transition from this cold event

to a neutral condition began to be observed and this

month—June—the La Niña episode is expected to end.

Developments that unfoldedThe onset of La Niña toward the last quarter of last year

brought to an end the June–July 2007 dry spell condition

experienced in Regions 1, 2, Cordillera Administrative

Region (CAR), National Capital Region (NCR), and Central

Luzon (see story on the 2007 dry spell in Luzon in the SCF

Project Updates issue of September 2007). With it came a

significant increase in rainfall volume as three tropical

cyclones immediately entered the Philippines’ area of

responsibility (PAR) in August 2007, followed by another

rainy month in September with the coming of another

three cyclones, namely, Falcon, Goring, and Hanna. These

disturbances, especially Hanna which crossed the country,

brought heavy rains, widespread flooding, and landslides

over Western Visayas and some areas of Luzon. This was

the time when the southwest monsoon was active.

As the transition period from the southwest to the

northeast monsoon season took place in October, the

presence of the ridge of high pressure area persisted over

Luzon, signifying generally good weather with below

normal rainfall condition for the area. Unfortunately, for

the other parts of the country like the Visayas and some

56 SCF Folio

areas in southern Mindanao, this was not the case as

they experienced above normal rainfall, bringing in

floods and landslides in certain places. The La Niña

gathered moderate strength and from November to

December 2007, affected the country’s climate through

the enhanced northeast monsoon by bringing in three

tropical cyclones that crossed the country and

thereupon causing widespread rains and landslides in

most areas of Luzon, some areas of the Bicol region, and

southern Mindanao.

La Niña conditions intensified in January 2008 and

as earlier mentioned, reached maximum strength last

February. The cold event enhanced the northeast

monsoon activity which in turn brought massive

flooding and landslides over most areas of the Visayas,

Bicol region, and Mindanao due to the week-long rains.

In Borongan, Eastern Samar, the historical record of

“highest 24-hour rainfall” of 298.5 mm registered on

February 10, 1939 was surpassed, setting a new record

for the country on February 14, 2008 at 371.4 mm. No

tropical cyclones, however, developed or entered the

PAR during the period.

Signs of a weakening of the cold event were

observed by March, after La Niña reached its peak in

February, as manifested by the warming in the eastern

equatorial Pacific Ocean.

In the meantime, the period from mid-March to

June normally represents the warmest months of the

year. The hot condition is usually seen as a precursor to

thunderstorm activity. The northeast monsoon season

came to an end in late March and the transition to the

southwest monsoon season took place in April. By mid-

April, the first tropical storm for 2008—Ambo—entered

the country.

The “official” onset of the rainy season associated

with the southwest monsoon, though, began in the

middle of May 2008, with the passage of tropical storm

Cosme which developed in the South China Sea. Cosme

was not supposed to touch land in the country but its

movement toward an exit to the northwest was blocked

by the presence of the ridge of high pressure area

whose axis extended north of the Philippines toward

Southern China and Thailand. And with the

simultaneous development of typhoon Dindo in the

northeastern section of Luzon, Cosme’s movement was

pulled and propelled by Dindo toward the northeastern

direction. The interaction of these two tropical cyclones

thereupon caused Cosme to make a landfall in western

Pangasinan and to cross the country as it raced toward

northeastern Luzon, causing massive destruction to

properties, agriculture, fisheries, and infrastructures

along the path that it crossed due to its torrential rains

and strong winds. As reported by the National Disaster

Coordinating Council (NDCC), overall damages reached

more than PhP180 million, particularly in Regions 1, 3,

and the Cordillera Administrative Region (CAR).

Two more tropical cyclones entered the country

in May, making a total of four and setting the highest

record of typhoons for the month since 1948. Above

normal rainfall in most parts of the country, especially

over the Visayas and parts of Northern Luzon, was

experienced.

Just recently this month (June), typhoon Frank

wrought havoc to lives, properties, infrastructures,

agriculture, fisheries, and the maritime industry in the

Philippines worth billions of pesos as massive flooding,

flashfloods, landslides, and storm surges took place in

several provinces, especially in Western Visayas, where

they have been declared to be under a state of calamity

even several weeks after the onslaught of the typhoon.

Table 1 summarizes the number of tropical

cyclones that entered the PAR in the first half of 2008

and indicates how many crossed the country.

The La Niña event is seen to come to an end this

June. On the whole, its impact was particularly felt in

the Visayas area and some areas in Mindanao as

manifested by the rainfall conditions during the event.

Table 1. Summary of tropical cyclones in the Philippines,January–June 2008

Month Tropical Tropical Typhoon CrossedDepression Storm the Country

JanuaryFebruaryMarchApril 1 1May 2 2 1June 1 1

Total 3 3 3

Source: PAGASA

57

What to expect in the next two monthsFor July 2008, the western part of Luzon, except the Ilocos

region, will likely experience below normal rainfall

condition. Ditto with the southern part of Bicol, provinces

of Leyte, Masbate, and northern Cebu. Meanwhile, above

Figure 1. Rainfall outlook, July–August 2008 normal rainfall is expected

over Cagayan Valley, as the

rest of the country will

likely receive near normal

rainfall.

The August forecast

seems to veer toward near

normal to below normal

rainfall conditions over

Luzon, including most

parts of Eastern Visayas. For

Central and Western

Visayas as well as most

parts of Mindanao, the

likely scenario will be near

normal rainfall condition.

Western Mindanao,

however, is expected to

have the opposite

condition as above normal

rainfall condition is forecast to prevail there in August.

Figure 1 shows the rainfall outlook for the country

for the months of July and August 2008. (SCF Project

Updates, June 2008)

SCFs in monetary terms: How muchis their worth to farmers?In Isabela: marginal, individually but significant, on the whole

As part of the ACIAR-funded project “Bridging

the gap between seasonal climate forecasts

(SCFs) and decisionmakers in agriculture,” a

simulation study was carried out in selected sites in the

province of Isabela, with the aim of developing an

approach to valuing the contribution of SCFs in

decisionmaking under conditions of climate uncertainty.

The study was conducted in Angadanan and

Echague, the top two corn-producing municipalities of

Isabela province. From the two municipalities, three

barangays were chosen based on their land types—river/

flood plain, broad plain, and hilly/rolling. The agroclimatic

condition, which mainly determines the timing and

number of cropping a rainfed farmer can have in a year, is

dry to moist for Echague and moist for Angadangan. The

traditional corn planting seasons in Echague and

Angadangan are April to June for the wet season cropping

and October to December for the dry season cropping.

Each cropping season lasts approximately 120 days or 4

months.

Historic climatic data (1951–2006) of Tuguegarao,1

which include daily values of solar radiation (MJ/m2-day),

____________1 Unfortunately, solar radiation data from Isabela are unavailable.The nearest weather station, with similar climatic conditions asIsabela, is in Tuguegarao.

58 SCF Folio

daily maximum and minimum air temperature (C), and

daily rainfall (mm), were collected from PAGASA while

crop management practices of farmers were gathered

using the Decision Support System for Agrotechnology

Transfer (DSSAT) program. The DSSAT program is an

approach developed for the purpose of helping provide

a more precise SCF and simulates outcomes of corn

yield.

Said program allows the simulation of different

corn varieties and cropping systems, targeting issues

such as climate variability, crop rotations, and

management alternatives in generating corn yields. In

terms of corn varieties, the only local hybrid variety

available in the DSSAT program is the Pioneer corn

variety. Thus, even if the survey conducted by the

project team did not actually use such variety, corn

yields for the areas using the DSSAT were simulated

based on this variety for both the wet and dry seasons.

Yields were also simulated under different climate

variability conditions, viz, for El Niño (poor year), La Niña

(good year), and Neutral (neutral year) scenarios. The

amount of rainfall is an important variable that greatly

influences corn production. In view of this, having an

accurate forecast is potentially of value to the farmers

inasmuch as it could help them decide whether to grow

their corn now or to delay it for the next cropping

opportunity. Meanwhile, the simulated long-term corn

yields generated from the DSSAT were then used to

calculate farmers’ income. Income was calculated by

multiplying the simulated corn yield by the price of corn,

a variable gathered from the responses during the

interview process.

For the study, with the use of weather data from

Tuguegarao, corn yield was simulated using DSSAT for

the period 1950 to 2006. The crop parameters used

were within the observed values reported in the survey,

implying that crop growth and development were

simulated realistically. Hence, the simulation provides

confidence that the DSSAT is able to capture the

sensitivity of corn productivity to climate over a long

time series.

To be able to evaluate the monetary value of SCF

information, the expected gross margin of each Pioneer

corn variety was calculated at various climatic

conditions (Table 1). Corn is very susceptible to climate

variations due to the plant’s requirement for water for

cell elongation and its inability to delay vegetative

growth. Therefore, there is always the danger of yield

loss regardless of the timing of planting. The amount of

yield loss that occurs during climate variations depends

on what growth stage the corn is in and how severe

the climate conditions may become. Highest yields will

be obtained only where environmental conditions are

favorable at all stages of growth.

Based on the results, it was found that during the

wet season, the good years (La Niña) yielded

PhP31,378/ha on average; more than the yield for

neutral years at PhP26,903/ha. On the other hand, the

neutral years yielded more (PhP29,626/ha) than the

good years (PhP29,067/ha) during the dry season.

Hence, the Pioneer variety is estimated to have higher

gross margin during the dry season across different

climatic variabilities.

The value of SCF information can be computed as

the difference between the gross margins of those with

and without SCF scenarios. Chances of farmers who

were not using SCF to attain higher gross margin might

be lower than those who were using the forecast. Such

value difference calculated was found to be PhP221/

ha/season. While this figure could be considered very

marginal for the individual subsistence farmers whose

landholdings average only about 3.56 hectares,

translating this amount to the total land area planted

to corn in the Philippines (2.6 million hectares as of

2007) would, however, redound to a substantial amount

and thereupon be of great significance for Philippine

agriculture. Because of this, it would be of critical

importance for decisionmakers/policymakers in

agriculture to greatly improve the access of farmers to

SCF information as well as to make such information

affordable and efficiently available to corn farmers.

Table 1. Expected gross margin (PhP/ha/season)of Pioneer corn variety at various climaticvariabilities during wet and dry season

Season/Climate Good Neutral Poor

Wet 31,378 26,903 26,704Dry 29,067 29,626 28,958

59

In Cebu: use of SCF gives higher income to corn farmers

Recently, a survey conducted by the Visayas State

University in connection with the ACIAR-funded

project “Bridging the gap between seasonal

climate forecasts (SCFs) and decisionmakers in agriculture”

shows that almost all of the SCF-user respondents

considered climate in their production decisions. In fact,

they considered SCF as having a medium to high

significance in terms of value or contribution to their

farming enterprise. The main reason cited by farmers is

that climate plays a major role in corn production.

The study also indicates that both users and

nonusers of SCF received adequate information about

weather/climate. However, a higher proportion of SCF-

user respondents reported receiving more accurate

information about climate.

Using SCF innovation in corn production has indeed

provided monetary benefits to corn farmers in Cebu. The

study shows that the mean gross margin during the first

season for SCF users was about PhP4,290/ha. This is

comparatively higher than the mean gross margin of

nonusers of SCF (PhP3,080/ha). Computed as the

difference of gross margin between users and nonusers

of SCF, the economic value of using SCF was found to be

PhP1,210/ha. For the second cropping, the mean gross

margin obtained by SCF users was about PhP7,867/ha

while nonusers of SCF realized only PhP3,080/ha, which

indicates that the economic value of using SCF in corn

production decision is about PhP4,787/ha. Findings of this

study imply that there is economic incentive for farmers

to use farming innovation such as SCF in corn production.

(SCF Project Updates, June 2008)

The challenge of using seasonal climateforecasts for decisionmaking:proposed frameworks

S easonal climate forecasting based on the

interaction of the ocean and atmosphere has

been regarded by experts as one of the premier

advances in the field of atmospheric sciences in the 20th

century; yet its use in decisionmaking is greatly hampered

by communication and application issues.

In their paper titled “Frameworks for using seasonal

climate forecasts for decisionmaking,” Peter Hayman,

Kevin Parton, Bronya Alexander, and Canesio Predo1

explored some ideas on how information on probabilistic

forecasts can be used in agricultural decisionmaking.

The authors recognized that majority of users find it

difficult to comprehend and use forecasts when they are

presented as probabilities. Many people, when faced with

uncertainty, rely on mental shortcuts which sometimes

lead to biases that impair the decisionmaking process.

An accurate categorical forecast that fits the logic of

IF, THEN, ELSE has been the more appreciated format by

decisionmakers. An example of this reasoning is, ‘IF the

season ahead is going to be a drought, THEN reduce

inputs, ELSE continue as normal.’

It is common for intermediaries such as agronomists

to state that farmers need a categorical forecast because

in the end, they need to make a decision. The media is

also more inclined to sending out categorical statements.

Forecasts for El Niño or La Niña episodes, for instance, are

respectively simplified to forecasts for drought or

____________1 Principal Scientist, South Australian Research and DevelopmentInstitute (SARDI); Professor of Economics, Charles Sturt University;Project Officer, SARDI; and Assistant Professor, Visayas StateUniversity, respectively.

60 SCF Folio

excessive rains rather than to a more qualified

statement of increased chances of the events occurring.

Implied in these inclinations is the notion that

probabilistic forecasts cannot be used in

decisionmaking. This notion, however, needs to be

corrected because it is not true. Notwithstanding

difficulties in communication, a forecast should be

presented as a probability because it is the honest way

of doing it. As an expert puts it, the atmosphere is a

complex chaotic fluid, and although patterns of ocean

temperatures ‘nudge’ this chaos in certain directions,

there will always be a significant proportion of

unexplained variation. Hence, the challenge is how to

communicate and use in decisionmaking skillful but

uncertain forecasts that are best represented as shifts

in climatological probability distributions.

Probabilistic forecasts also ensure that risk

management is not hindered. A farmer who

misunderstands SCF as a categorical forecast may be

led to devise poorer risk management strategies

compared to a situation where he did not hear of the

forecast at all. A crop grower may plan for a wide range

of outcomes in the absence of a forecast. But if only

one outcome is in his mind, then the planning exercise

will definitely be narrower.

An imposing challenge therefore is how to use

uncertain information for decisionmaking. The use of

decision analysis was mentioned as an approach that

provides a logical framework for a decisionmaker to

formulate preferences, assess uncertainty, and make

judgments. There has been a tradition in agricultural

science to talk the language of choice-consequence.

For example, if you put on x units of nitrogen, you will

get a yield of y. A more forward-looking language is that

of choice-chance-consequences. This means that if

you put on x units of nitrogen, depending on the season

type, you will get a yield of either y1, y

2, or y

3.

A good example (Figure 1) is the use of decision

tree analysis in determining the level of fertilizer inputs

given uncertain forecasts. Decision tree analysis is a

technique to aid decisionmakers in identifying the

outcomes for each decision alternative. It involves

assessing the probabilities associated with each

outcome, assigning payoffs, and keeping the sequence

of outcomes and decisions in the proper chronological

order. Because the decision tree reflects choices,

probabilities, and consequences, it thereupon

effectively illustrates how uncertain forecasts might be

used to change fertilizer decisions.

The figure shows how forecasts can influence the

decision of N fertilizer rates application. For instance,

during the season with a

poor, average, and good

outcome, about 20, 60, and

100 units, respectively, of N

fertilizer will be applied.

Given this information and

knowing the expected

season from the seasonal

climate forecast, the farmer

can therefore decide on the

level of fertilizer application.

Results from the figure

show that if the forecast is

neutral, the farmer is better

off when he will apply 100

units than 20 units and even

60 units of N fertilizer.

However, if he will apply 100

Figure 1. Decision tree analysis showing gross margins for different fertilizer rates and seasontypes, and probability weighted value for each of the three fertilizer rates

...The notion that probabilistic forecasts cannot be used indecisionmaking is not true. Notwithstanding difficulties incommunication, a forecast should be presented as aprobability because it is the honest way of doing it...Thechallenge is how to communicate and use in decisionmakingskillful but uncertain forecasts that are best represented asshifts in climatological probability distributions.

61

units of N fertilizer based on good outcome season but

the actual season turns out to be poor, the farmer will

incur a loss or negative gross margin. Similarly, if he is

expecting a poor season outcome by applying 20 units

of N fertilizer but a good season has actually occurred,

then he has missed the opportunity for a bigger gross margin.

In the paper, the authors also present a fresher and

more fun way of looking at decision analysis through

‘Wonder Bean,’ an innovative game about choosing the

right crop to plant given SCF and seasonal climate

variability. The game features spinning probability disks

in a simple Excel®-based spreadsheet where participants

decide on the area of a farm to plant to a higher-return

but higher-risk crop vis-à-vis the area to leave to a lower-

return but lower-risk crop.

Although the enumerated applications with

spinning probability disks, decision trees and crop choice

games are not intended for regular decision support

systems, they are nonetheless useful in organizing ideas

and engaging decisionmakers. A step toward bridging the

gap between climate science and decisionmaking, no

matter how small, is after all a step toward better

managing the risks from seasonal climate variability. (SCF

Project Updates, September 2008)

Choosing risk-efficient planting schedulesfor corn: the Matalom, Leyte case

One of the most important decisions affecting crop

production in rainfed areas is the timing of

planting. A farmer may select a planting schedule

in such a way that the cropping period would be less risky,

avoiding or minimizing the impact of projected

destructive seasonal climatic events within the growing

season. This is now made more possible with recent

developments in atmospheric science, particularly on

seasonal climate forecasting (SCF).

Remberto Patindol, Canesio Predo, and Rosalina de

Guzman1 explored this possibility of shifting cropping

schedules from traditional dates to fit forecast seasonal

climatic events in a rainfed area in Matalom, Leyte,

Philippines. In a study titled “Risk-efficient planting

schedules for corn in Matalom, Leyte,” they looked into

historical weather data and information about past

occurrences of the different El Niño Southern Oscillation

(ENSO) phases to see if these can be used in selecting the

best cropping schedules.

Local farmers usually follow traditional planting

schedules under the assumption that the conditions

during a particular planting period are repeated over the

years. Thus, it would not be uncommon to observe farmers

in a given locality, for example, to plant corn in the first

week of May and repeat this schedule over the years. This

practice, however, makes local farming prone to damages

because farmers usually do not use SCF and account for

seasonal climate variability especially during El Niño and

La Niña events.

The authors thus identified risk-efficient planting

schedules for corn using stochastic dominance analysis

of simulated yields given ENSO forecasts for different

cropping periods. The method requires the use of

probability distributions of corn yields for different

planting schedules. Given the absence of historical data

and lack of time for conducting multiyear experiments,

corn yields for the different planting scenarios were

generated through the use of a simulation modelling

software. The model utilized actual and synthetic data to

reflect the variability associated with the different ENSO

phases.

Inputs in the yield simulation modelling included

actual and generated weather data from the nearest

____________1 Associate Professor and Assistant Professor at the Visayas StateUniversity, and Assistant Head, Climate Information, Monitoring, andPrediction Services Center of the Philippine Atmospheric,Geophysical, and Astronomical Services Administration (PAGASA),respectively.

62 SCF Folio

weather station, soil characteristics of the site, crop-

specific parameters, and common cultural practices in

corn production. The method of stochastic dominance

analysis was then applied on the probability

distributions of the simulated yields using two criteria:

first-degree stochastic dominance and stochastic

dominance with respect to a function, with three levels

of risk aversion.

The process led to the identification of risk-

efficient strategies for each stochastic dominance

criterion and the most preferred schedule within each

season, given the ENSO episode during the cropping

period. These schedules could be used as guide by

farmers in the site if PAGASA could provide a forecast

about the ENSO episode in the next cropping period.

Likewise, the study was able to identify the risk-efficient

and most preferred schedules within every season

without considering the ENSO episode during the

cropping period. The schedules identified in this

manner can be used by the farmers in the site if no

forecast is available (represented as All Years in Tables 1

and 2).

The study successfully demonstrated in principle

that stochastic dominance analysis can be applied to

identify risk-efficient schedules under the different

ENSO episodes using probability distributions of

simulated yields. It also showed that stochastic

dominance analysis is sensitive in the sense that it can

still provide a ranking of the strategies even with

relatively small differences in the mean values. This

implies that the method could be a good alternative

when comparing outcomes of different strategies.

The ultimate question would be on how to make

the outputs of the study relevant to local farmers.

Considering that the actual schedules followed by

farmers in the site differed from the risk-efficient

schedules identified in the study, the authors expressed

the need for a more detailed enquiry. For one, the

research did not incorporate all factors that may have

some influence in a farmer’s choice of planting

schedule. In the absence of relevant explanations for

farmers’ actual choices, dissemination of information

pertaining to risk-efficient planting schedules was

thereupon advised. (SCF Project Updates, September 2008)

Table 2. Summary of the simulated yields (kg/ha)for the most preferred planting schedulesduring the second season

Schedule Rank Mean Standard MinimumDeviation

La NiñaDecember, week 4 1 2,540.11 198.21 2,290.00December, week 1 2 2,527.78 173.09 2,204.00December, week 2 3 2,466.11 151.57 2,244.00December, week 3 4 2,443.33 167.73 2,246.00August, week 1 5 2,400.90 125.48 2,179.00

El NiñoDecember, week 1 1 2,602.82 178.54 2,351.00September, week 2 2 2,413.30 74.83 2,308.00September, week 3 3 2,452.80 125.61 2,229.00December, week 2 4 2,547.55 228.52 2,192.00December, week 4 5 2,451.82 169.58 2,171.00

NeutralDecember, week 1 1 2,518.14 153.80 2,253.00September, week 1 2 2,370.71 90.14 2,237.00December, week 2 3 2,502.36 208.62 2,133.00August, week 4 4 2,374.23 134.37 2,211.00October, week 3 5 2,377.54 153.52 2,141.00

All YearsDecember, week 1 1 2,548.09 166.53 2,204.00December, week 2 2 2,507.38 198.87 2,133.00December, week 4 3 2,500.85 223.84 2,099.00December, week 3 4 2,449.21 185.02 2,056.00August, week 3 5 2,339.91 152.89 2,102.00

Table 1. Summary of the simulated yields (kg/ha)for the most preferred planting schedulesduring the first season

Schedule Rank Mean Standard MinimumDeviation

La NiñaJune, week 3 1 2,591.29 133.27 2,419.00June, week 1 2 2,510.14 113.07 2,377.00April, week 4 3 2,476.67 78.56 2,371.00June, week 4 4 2,500.00 143.18 2,347.00June, week 2 5 2,528.57 135.76 2,286.00

El NiñoJune, week 1 1 2,510.22 109.44 2,372.00June, week 2 2 2,490.78 151.16 2,052.00May, week 3 3 2,404.60 95.09 2,264.00June, week 4 4 2,411.00 113.70 2,221.00July, week 3 5 2,416.45 158.50 2,084.00

NeutralJuly, week 1 1 2,418.73 145.71 2,141.00July, week 2 2 2,468.87 159.31 2,087.00July, week 3 3 2,417.80 152.50 2,081.00May, week 3 4 2,378.94 147.06 2,152.00June, week 3 5 2,397.11 184.20 2,093.00

All YearsMay, week 3 1 2,412.88 135.53 2,152.00July, week 3 2 2,416.68 141.33 2,081.00June, week 3 3 2,455.71 191.45 2,066.00June, week 4 4 2,414.85 163.40 2,050.00May, week 4 5 2,403.53 158.53 2,066.00

63

Determining corn farmers’ decisionsbased on SCFs

Gian Carlo M. Borines, Rotacio S. Gravoso,Canesio D. Predo*

The advent of the anomalous weather and climate

conditions aggravated by global warming has

underscored the need to disseminate climate

information to guide farmers in their farm decisions.

Advance climate information, like the seasonal climate

forecast (SCF), helps farmers decide which land to use for

a particular crop, chart out production schedules, and

devise commercialization strategies—decisions that are

normally made by farmers long before the sowing season

starts. Experiences from other countries show that the risk

of production losses due to anomalous climatic conditions

can be mitigated if farmers are aware of and use SCF.

In the Philippines, the project, “Bridging the gap

between seasonal climate forecasts and decisionmakers

in agriculture,” funded by the Australian Centre for

International Agricultural Research (ACIAR), has shown the

possibility for farmers to improve their income if they use

SCF. Thus, the project intends to actively disseminate and

encourage farmers to incorporate SCF into their farming

practices.

Central to the use and application of climate

information is the decisionmaking by farmers. Based on

existing literature, in dealing with uncertain climate

information, farmers engage themselves in description-

and experience-based modes of decisionmaking,

thereupon increasing the risks of possible losses. This

study was therefore conducted to find out how farmers

will decide if they are presented with probabilistic climate

forecasts.

MethodsThis study was conducted in Brgy. Miglamin, Brgy. Laguitas,

and Brgy. Magsaysay in Malaybalay City, Bukidnon

Province in consultation with the Department of

Agriculture in Malaybalay City.

A focus group discussion (FGD) was conducted to

gather the background on the farmers’ exposure, access

and use of SCF. To find out about the farmers’

decisionmaking based on uncertain information, two

decisionmaking workshops were conducted. In each

workshop, farmer participants were made to assume five

varying hypothetic assumptions wherein they have

experienced unfavorable cropping seasons in the past

three consecutive years (March–June, 2005–2007). The

participants were then presented with a climate forecast

(in video) developed specifically for this study (Table 1).

Subsequently, farmers were asked to make decisions or

courses of action for the next cropping season based on

the forecast (Table 2). A total of 30 farmers participated in

the two workshops.

Highlights of resultsExposure and access to SCF informationData showed that farmers in this study were aware of SCFs

and climate information. Farmers, especially those who

are planting in big areas of land or are producing crops

on a large scale, pay visits to the PAGASA station in

Malaybalay or the Department of Agriculture (DA) office

to consult on what the climate would be like before they

begin to plant and what crops would be best to plant.

Information obtained from these consultations is used to

schedule the time of planting and to decide on which

crop to plant.

Not all farmers in Malaybalay, however, are able to

go to the city proper to inquire about the climatic

conditions. Thus, PAGASA and the DA hold seminars and

fora about the climate in areas surrounding the province.

Likewise, staff from the PAGASA station are invited

occasionally to air climate forecasts and issues over the

local radio station.

Evaluation of SCF informationFarmers reported that they get climate forecasts from the

radio or television through the national stations. In

general, they felt that climate forecasts are helpful.

However, to be more useful, they suggested some

changes. These suggestions include: 1) avoid the use of

____________* Staff and faculty, Visayas State University.

64 SCF Folio

Table 1. Forecasts given to farmers

Hypothetic Assumption and Forecast Detailed Description of Event

Wet season for March–June, 2005–07; Farmers were told to assume that hypothetically, they experienced aforecast with dry season for March-June 2008 rainy season for the last cropping season for three consecutive years.

They were then given a dry season forecast for the incoming croppingseason. Farmers were then allowed to make decisions for their farms,bearing the knowledge that forecasts are not always 100 percentaccurate.

Dry season for March–June, 2005–07; Farmers were told to assume that hypothetically, they experiencedforecast with dry season for March–June 2008 drought for the last cropping season for three consecutive years. They

were then given a dry season forecast for the incoming croppingseason. Farmers are then allowed to make decisions for their farms,bearing the knowledge that forecasts are not always 100 percentaccurate.

Wet season for March–June, 2005–07; Farmers were told to assume that hypothetically, they experienced aforecast with wet season for March–June 2008 rainy season for the last cropping season for three consecutive years.

They were then given another wet season forecast for the incomingcropping season. Farmers are then allowed to make decisions for theirfarms, bearing the knowledge that forecasts are not always 100percent accurate.

Average season for March–June, 2005–07; Farmers were told to assume that hypothetically, they experiencedforecast with dry season for March–June 2008 normal amount of rainfall for the last cropping season for three

consecutive years. They were then given a dry season forecast for theincoming cropping season. Farmers are then allowed to makedecisions for their farms, bearing the knowledge that forecasts are notalways 100 percent accurate.

Average season for March–June 2005–07; Farmers were told to assume that hypothetically, they experiencedforecast with La Niña for March–June 2008 normal amount of rainfall for the last cropping season for three

consecutive years. They were then given a La Niña forecast for theincoming cropping season. Farmers are then allowed to makedecisions for their farms, bearing the knowledge that forecasts are notalways 100 percent accurate.

scientific terms, 2) downscale the forecast to their

locality, and 3) forecasters should “tell the truth.” The

third suggestion emanated from their experience of a

forecast of an unsuitable cropping season that did not

come true. This resulted in an opportunity missed for

the farmers to plant their crops. For farmers like them

who rely on their ability to produce crops for sustenance

of their households, missing an opportunity to plant

crops may result in their inability to feed their respective

families.

The farmers also said that they use SCF in deciding

farm activities. However, some of them likewise said that

they just predict the climate by themselves and do not

rely on SCFs provided by PAGASA. “Mo tan-aw tan-aw

na lang ko og sakto ba kaha ipamugas ang panahon,

ug sakto unya mo pugas pud ako mga silingan, aw mo

pugas pud ko” (I just observe the climate, if my

neighbors sow, I also sow), a farmer reported. Farmers

also said that if they feel that a forecast will not

materialize, they just ignore it, “Mo sugal na lang mi”

(To some extent, we just gamble). By this statement,

farmers mean that they are prepared to face the

possibility of a cropping failure due to planting in an

unfavorable climate condition.

Farmers in Malaybalay had a hard time trying to

understand the complex terms used in climate forecasts

such as monsoons, intertropical convergence zone

(ITCZ) and low- pressure areas. Because of this, farmers

are unable to completely comprehend the information.

Farmers’ decisions based on probabilisticclimate forecastsFor the various forecasts given them during the

decisionmaking workshops, the following decisions

came out (refer also to Table 2):

Wet cropping season experience and dry forecast.

For this situation, farmers said that they would cultivate

only a small portion of their land to minimize cost for

the labor of land preparation. They also said that if the

dry season comes, they would plant crops resistant to

drought (i.e., sugarcane, cassava, banana, and other

similar crops) or short-season crops like sweet potato,

65

mongo, soybeans, cowpeas, and other leguminous plants

so that before the dry season comes, they would have

had finished harvesting. They added that they would leave

the silage of their crops to fertilize the land. They

maintained that they would plant in small quantities to

minimize production cost for what they expect to be a

low yield due to the dry climate.

Dry cropping season experience and dry forecast.

Under this situation, the decisions made by the

respondents were more for sustaining their households

and not for income. They reasoned that by the fourth year

of a drought, they would have run out of savings for their

families. Participants said that they would find alternative

livelihood or other means of earning an income. One of

the alternative sources of income they mentioned was to

work as hired laborers in sugarcane plantations. They

claimed that sugarcane is a drought-resistant crop; hence,

sugarcane plantations will continue to operate even

during drought.

Some farmers said that they would find other work

in Malaybalay. Other farmers said that they would practice

handicraft making as an alternative source of income. As

an immediate source of food, participants said that they

would venture into backyard gardening. They claimed

that it is easier to maintain crops when grown in small

numbers. For these backyard gardens, they would use

their used water at home to water their crops. Farmers

said that they would also raise farm animals like chicken,

goats, pigs, and cows for additional income.

Wet cropping season experience and wet forecast.

For this situation, participants said that they would still

plant corn but will use the native or the “bisaya” variety.

They claimed that the native variety is cheaper and grows

well both in wet and dry seasons compared to the hybrid

varieties. Other than corn, they would also plant other

crops in the sides of their farm as a source of additional

income.

Average cropping season experience and dry

forecast. Farmers’ decisions in this situation are similar to

the decisions they have made in the wet forecast. Farmers

said that they would cultivate corn in a small portion of

their land. According to them, they will not hire laborers

to cultivate their land. Instead, their family members will

help, from land preparation to planting until harvesting.

If the dry season comes, a small number of farmers said

that they would plant crops that are resistant to drought

such as banana, sugarcane, rubber, and cassava. They

maintained that they would be planting in smaller

quantities.

Average season experience and La Niña forecast. For

this situation, farmers were asked to assume that they

have experienced an average climate for the cropping

season for three consecutive years in the past and were

then given a La Niña forecast for the present cropping

Table 2. Farmers’ responses to SCFs

Experiential Data Analytical Data Farmers’ Decisions(Hypothetic Assumption) (Climate Forecast)

Wet cropping season for Dry season Prepare a small portion of their land to minimize spending. If the drythree years season comes, plant crops which are resistant to drought or short-

season crops. Plant in small quantities to avoid too much input for anexpected below-average output.

Dry cropping season Dry season Find other means of earning income. Practise backyard gardening tofor three years have an immediate source of food for their family. Raise farm

animals such as chickens, goats, cows, and pigs to have alternativesources of income. Look for work in Malaybalay. Switch from corn tomore drought-tolerant crops (high risk option).

Wet cropping season Wet season Still plant corn, and plant other crops in the periphery to earnfor three years additional income. There would be very little (or no) changes in their

farming practices because of the rainy climate for the croppingseason.

Average cropping season Dry season Prepare a small portion of their land. Farmers and their families willfor three years cultivate their land to minimize cost in land preparation. If the dry

season comes, plant crops which are resistant to drought. Plant insmall quantities.

Average cropping season La Niña Plant crops that grow even with too much water or use corn varietiesfor three years that thrive under a wet climate condition.

66 SCF Folio

season. In response,

farmers said that they

would plant crops that are

water-tolerant or use corn

varieties that thrive even

under wet conditions.

However, farmers in

Bukidnon rarely cultivate

rice because according to

them, the area is not

suitable for rice

production. Farmers stated

that even with a La Niña

forecast, they need to plant

crops or else they will have

nothing to spend for the

education of their children

and for their day-to-day

sustenance.

ImplicationsDespite the popularity of

SCFs among farmers in Malaybalay, the value of this

information is not maximized because farmers just

ignore them. According to them, they have several

experiences where forecasts did not materialize. There

is, therefore, a need to implement an intensive

educational campaign to explain to farmers about the

probabilistic nature of the SCF and to teach them on

how to make use of these forecasts wisely.

This study found that farmers apply indigenous

climate forecasting in their farming practices. For

example, to decide when to sow, they observe what

they call “planting by the moon,” that is, they sow during

full moon. According to them, a full moon ensures them

of a good harvest. While, according to farmers, there is

no scientific explanation for this practice that they know

of as yet, they have nonetheless observed that “planting

by the moon” has been bringing them good harvests

and profits. Considering this finding, it is suggested that

agencies mandated to provide climate advisory to

farmers should look for ways to integrate farmers’

indigenous forecasting system in their efforts to

encourage farmers to use seasonal climate forecasts.

Despite the popularity of SCF in Malaybalay, farmers often ignore these information becauseaccording to them, the forecast did not come true. In this photo, farmers watch an SCF invideo during a decisionmaking workshop. They will plan their farming activities for the nextseason based on the forecasts.

Judging from the outputs generated during the

decisionmaking workshops, farmers’ coping

mechanisms for extreme climate will enable them to

earn income that will sustain their respective families’

needs. The problem, however, is that in extremely

unfavorable cropping conditions, their only choice is to

work as menial laborers in factories, department stores,

and other industries in Malaybalay City. Since climate

change is inevitable, research and development

agencies are called on to start technology development

works that will help farmers mitigate the impacts of or

make farmers adapt to the climate change.

Finally, findings in this study showing that farmers

find it hard to appreciate and understand climate

forecasts suggest the need for academic institutions to

integrate climate reporting in their curricular programs.

To date, contents of communication programs usually

relegate this topic to the background. Hence, this is one

area that may be seriously considered to help in the

communication and understanding of seasonal climate

forecasts and their probabilistic nature. (SCF Project

Updates, December 2008)

67

Australia

Dr. Peter HaymanSouth Australian Research and Development Institute

Prof. Kevin PartonCharles Sturt University

Dr. John MullenNew South Wales Department of Primary Industries

Mr. Jason CreanNew South Wales Department of Primary Industries

Ms. Bronya AlexanderSouth Australian Research and Development Institute

Philippines

Philippine Institute for Development Studies

Dr. Celia M. Reyes

Ms. Jennifer P. T. Liguton

Mr. Sonny N. Domingo

Mr. Christian D. Mina

Ms. Kathrina G. Gonzales

Visayas State University

Dr. Canesio D. PredoNational Abaca Research Center /Department of Economics

Dr. Rotacio S. GravosoDepartment of Development Communication

Dr. Remberto A. PatindolCollege of Arts and Sciences

Ms. Eva L. MonteNational Abaca Research Center

Philippine Atmospheric, Geophysical and AstronomicalServices Administration

Dr. Flaviana D. HilarioClimatology and Agrometeorology Division

Ms. Edna L. JuanilloClimatology and Agrometeorology Division

Ms. Rosalina G. De GuzmanClimatology and Agrometeorology Division

Ms. Daisy F. OrtegaClimate Information Monitoring and Prediction Services Center

Philippine Rice Research Institute

Dr. Eduardo Jimmy P. QuilangAgronomy and Soils Division

Dr. Constancio Asis, Jr.Agronomy and Soils Division

Ms. Rowena G. ManaliliSocioeconomic Division

Mr. Jovino De DiosAgronomy and Soils Division

Ms. Guadalupe RedondoSocioeconomic Division

Mr. Roy F. TabalnoSocioeconomic Division

Project Team

Sources

SCF Project Updates (various issues beginning June 2005 up toDecember 2008). This is the official newsletter of the SCFproject. It started as a newsletter published on a semestralbasis but beginning 2007, it appeared on a quarterly basis.

Economic Issue of the Day (various issues). This explainsconcepts related to economic matters and relates the conceptsto everyday activities and how they may apply to daily lives.

Design and layout byJane C. Alcantara

68 SCF Folio

ImplementingAgenciesBridging the gap between seasonal

climate forecasts and decisionmakersin agriculture

Australian Government

Australian Centre for InternationalAgricultural Research

A project funded by