Weather & Climate Weather & Climate Forecasts and its Forecasts and its

ApplicationsApplications

K K SinghK K SinghHead, Agromet ServicesHead, Agromet Services

Talk Outline

Observing Weather Predicting Weather & Climate Applications & Services Future Plan

Incremental use of Met InformationImproved Quality of Information

Scientific and technical advances Numerical modelling and data assimilation

Improved Capacity & Need of User Increased awareness of need to act Value of evidence-based decision making Greater capacity to access information Greater capacity to use information in decision

making Ongoing resource pressures and accountability

Global environmental change conciousness Response to climate and natural disasters

What IMD DoesProduce Weather and Climate

Forecasts and Warnings- To Protect Life and Property

- To Enhance the National Economy

Also provide Data and Products:

This problem has three parts . . .

Analyze: Current state of atmosphere

Forecast: What’s going to happen?

Communicate: Forecast/warning dissemination

Meteorological information is becoming more accurate for applications the economy and business decisions

Observing Weather

The skill improvement in weather forecasts has mainly come from…

Enhanced understanding of earth's atmosphere

Better observing systems Better communication systems Better analytical techniques Improved numerical models Faster computers Skilled manpower Better dissemination systems

Observe to Define Initial State• International cooperation in exchanging

meteorological observations• End to end connection across observing system,

Telecom system, data processing system and forecasting system

• Integration – space and in situ• Observe once

• use many times & forever• Use for many applications

Observing System Nos.

Doppler Weather Radars (DWRs) 16Automatic Weather Systems (AWS) 675Automatic Rain Gauges (ARG) 1206Surface Observatories  559Aviation Current Wx Observatories 71High Wind Speed Recording Stations 14Hydrometeorological Observatories 701Non-Departmental Rain Gauge   3540Upper Air Radiosonde Observatories 39Pilot Balloon Observatories 62

Type of Observatory Nos.Non-Departmental Glaciological Observatories  - Snowgauges 21- Ordinary Raingauges 10- Seasonal  Snow Poles 6Agrometeorological Observatories 219Evaporation Stations 222Soil Moisture Recording Stations 49Dew-fall Recording Stations 80Evapotranspiration Stations 39Surface Ozone Stations 10Column Ozone (Dobson Spectrophotometer) 2Aerosol Measurement (Skyradiometer) 12Verical Ozone Profile (Sonde) 3Radiation Stations 45Global Atmospheric Watch 11Indian Voluntary Observing Fleet 203

INSAT-3D

Spectral Band

Wave length (µm)

Ground Resolution

Visible 0.55-0.75 1 km

SWIR 1.55-1.70 1 km

MIR 3.80-4.00 4km

WV 6.50-7.10 8km

TIR1 10.2-11.3 4km

TIR2 11.5-12.5 4km

INSAT-3D Satellite Imager Channel Specification

Global Data Dissemination Centre

Predicting Weather

Satellite Observations

Sat. Met Division, IMD (Deployed by Department

of Space)

Aircraft Reports

Ship Reports

Ocean Buoys data(Deployed by Dept. of Ocean Development)

Global Data

Data-flow at Three Hourly Intervals on 24x7 Mode

Regional Telecom Hub (RTH)

DelhiNational Weather Forecasting Centre PuneWeather Central

IMD, Delhi

LAFS NWP forecasts

Regional Centres – 6

State LevelMet.

Centres

Airport Met.

Offices

Cen

tral / S

tate

Govt/ M

ed

ia/

Pub

licCommunication

Analyses & Forecasting

Dissemination

Observations

Data ported to NCMRWF for

medium range weather forecasts

Upper-Air Observations

(62 PB stations + 39 RS/RW)

Surface Observations

Manned (559) + AWS (725) +ARG (1046)

Operational NWP System Medium Range Forecast > GFS T-574/L64 with GDAS ( 00 & 12 UTC) > MME based District Level Forecasts Short Range Forecast > WRF (ARW) VAR at 27 km and 9 km > HWRF > MME based cyclone track prediction > Polar WRF for Antarctica Nowcast and Very Short Range Forecast > Hourly venue specific forecast- WRF (3 km) > ARPS with assimilation of DWR > Nowcast System with assimilation of DWR

Operational Weather Forecasts• Weather Bulletins: All India, Regional, State level• District Level Forecasts • Cyclone prediction• Aviation Forecast• Hydromet Forecast• Marine Forecast• City Forecast• Tourism Forecast• High Way Forecast• Forecast for Antarctica • Air Quality Forecast • Now-cast: Hourly venue specific forecast• Extended Range Forecast• Seasonal Forecast

DISTRICT LEVEL FORECAST

Generation of district level weather forecast (DLWF)

The same was started since June 2008

Parameters: Rainfall Max and Min temperatureTotal cloud cover Surface Relative humidity Surface Wind

New Imitative: GFS 07 DAYS (WEEKLY) CUMULATIVE SUB-DIV. RAINFALL FORECAST

Forecast Observed

GFS All India daily mean rainfall for monitoring active/weak spell

New Initiative:

Generating all India Mean rainfall along with observed normal for monitoring Weak and active spells during monsoon periods.

EXTENDED RANGE WEATHER FORECAST

(NATIONAL MONSOON MISSION)

ARPS at 9 km resolution with assimilation of data from multiple DWRs

http://202.54.31.51/fdp2/arps_form_s.php

Prediction Skills

CC: 7 DAY CUM RAIN: MONSOON 2011

0.3

0.4

0.5

0.6

0.7

0.8

0.9

CENTRALINDIA

NW INDIA NE INDIA EASTINDIA

SP INDIA WESTCOASTINDIA

ALLINDIA

CC

T382

T574

Domain mean correlation coefficient (CC) of weekly (seven days) cumulative observed and forecasts for day-1 to day-5 of rainfall for GFS T382 and T574 over different homogeneous regions of India during monsoon 2011

Domain mean correlation coefficient

Verification of local rainfall forecast (24 hours)

DAY WISE SKILL SCORE VALUE FOR OBSERVED VS VALUE ADDED R/F

74

76

78

80

82

84

86

88

90

92

CHB DJG MLD NAD E.MDP W.MDP

SK

ILL

SC

OR

E I

N P

ER

CE

NT

AG

E

day1

day2

day3

day4

day5

West BengalQualitative verification of Rainfall Forecast 2013

Scores  2008-10 2011-13% improvementIn 2011-13 from

2008-10

FAR 0.47 0.21 -56%MR 0.55 0.30 -45%

BIAS 0.82 0.95 Near NormalPOD 0.45 0.70 56%

C-NON 0.89 0.92 4%PC 0.76 0.87 14%

HSS 0.34 0.63 86%CSI 0.32 0.56 78%

Heavy rainfall warning improvement in last 3 year

Cyclone ForecastingLocation and intensity estimation Direction and speed of movementTrack forecastingIntensity forecastTime and point of landfall Maximum sustained Gale Force Wind forecastRainfall forecastStorm surge forecastDamage expected and action suggested

CyclogenesisPrediction

TrackPrediction

IntensityPrediction

Rapid Intensification

Decay after Landfall

Decay Model

RI-Index

SCIP Model

Multimodel Ensemble(MME)

Genesis Potential Parameter(GPP)

STEP-I

STEP-II

STEP-III

STEP-IV

STEP-V

NWP based Objective Cyclone Prediction System

Track forecast error (km)

Trend in improvement in track forecast (km/Year) during 2003-12

12 hr- 5.1 km per year24 hr- 7.2 km per year

Mean landfall point forecast error (km)

Mean landfall time forecast error (hr)

Average (2008-12)24 hr- 91 km, 48 hr- 96 km 72 hr- 135 km

Average (2008-12)24 hr- 5.5 hrs48 hr- 7.3 hrs 72 hr- 1.2 hrs

Trend in improvement in Landfall forecast during 2003-12

Landfall point12 hr- 16 km per year24 hr- 33 km per year

Landfall Time12 hr- 0.5hr per year24 hr-0.0hr per year

Forecast Performance during 2013

TRIGGERING FOR WATER MANAGEMENT

The full reservoir level of Hirakud Dam is 630 ft.

DGM IMD ADVISED ON 9TH October to Hirakud Dam authorities

through MHA to release water in view of potential threat due to

cyclone

Due to release water level came down to 621 ft. on 11th October.

As the released water was increasing over the plain area of coastal

Odisha, DGM, IMD further advised to stop releasing water on 11 th

October

As a result the reservoir was well managed

Due to extremely heavy rain over Mahandi catchment the reservoir

level increased from 621ft on 11th to 629ft after the cyclone

As it was within the full capacity, it did not worsen the flood

situation in Mahanadi

38

April

June

All India June – September Rainfall

Update for All India June – September Rainfall

All India Monthly(July & August) Rainfall

June – September Rainfall for Four Geographical Regions

In addition, Forecast for Date of Monsoon Onset over Kerala in May

Month of Forecast Issue

All India Second Half of SeasonAugust - September Rainfall

All India MonthlySeptember Rainfall

July

August

All India

Geographical Regions

Long Range Forecast

11-Sep-12

Probabilistic Forecast Based on 5- Parameter Ensemble Forecasting system

Category CategoryClimatol.

Probability %Forecast

Probability %

Deficient <90% 16 10

Below Normal 90-96% 17 27

Normal 96%-104% 33 46

Above Normal 104%-110% 16 14

Excess >110% 17 03

Performance of Operational Forecast (Empirical Model) for All India Seasonal Rainfall (1988-2012):

During 7 years error was ≥ 10% with highest during 2002 (20%) and 1994 (18%). Error during 2009 was 15%.

Average Abs Error of Op. forecasts (1988-2012) =7.95% (1993-2002)= 9.3% of LPA & 2003-2012=6.6% of LPA).

During 1993-2002, the forecast was within the ±8% of actual values during 6 years. with forecast within ±4% of actual values during 2 years.

During 2003-2012, the forecast was within the ±8% of actual values during 7 years. with forecast within ±4% of actual values during 5 years.

Apr 21, 2023

PCR model for the Forecasting date of Monsoon onset over Kerala

Model Model error= 4 error= 4 daysdays

No Name of Predictor Period C.C (1975- 2000)

1 Zonal Wind at 200hpa over Indonesian Region 16th -30th Apr 0.48

2 OLR Over South China Sea 16th- 30thApr 0.40

3 Pre-Monsoon Rainfall Peak DatePre-monsoon

April-May0.48

4 Minimum Surface air Tem. over NW India 1st -15th May -0.37

5 Zonal Wind at 925hpa over Equatorial South Indian Ocean 1st -15th May 0.52

6 OLR Over Southwest Pacific 1st -15th May -0.53

YearActual

Onset DateForecast

Onset Date

2005 7th June 10th June

2006 26th May 30th May

2007 28th May 24th May

2008 31st May 29th May

2009 23rd May 26th May

2010 31st May 30th May

2011 29th May 31st May

2012 5th Jun 1st Jun

2013 1st Jun 3rd Jun

Performance of the PCR Model for Monsoon Onset over Kerala

-12

-8

-4

0

4

8

12

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

Year

Mo

ns

oo

n O

ns

et

Ov

er

Ke

rala

(D

iffe

ren

ce

fro

m t

he

No

rma

l Da

te)

Actual MOK Forecast

Apr 21, 2023

Applications & Services

Major Services to different Sectors

In the Service of Nation since 1875

•Real time rainfall monitoring•Reservoir Management• Input or Flood Forecasting & Drought Monitoring•Design storm projects (hydraulic structures)•Rainfall statistics (rainfall normal & extremes)•Rainfall climatology

HYDROMETEOROLOGICAL SERVICES

Preparation of value added medium range

forecast at district level Tuesday

Friday

NWP productsState Met Centre (SAMC)

Issuing State Level Composite Bulletin

Value addition

Agromet Field Units(AMFUs)

Dissemination of Agromet Advisory through Multi-Channel Dissemination System

Parameters Rainfall, Wind speed and

direction, Maximum temperature, Relative humidity, Minimum temperature, Cloud cover

Agromet Advisory

11.4 million farmersReceiving SMS

• Conducting State Level Meeting• Completed meetings in 6 States

in 2012

Issuing District (635) AgroMet Bulletin in 13 languages (http://imdagrimet.gov.in)

• Conducting Farmer Awareness Programme

• Completed at 106 stations

Also Brochures for Awareness were completed for 14 languages

From Composite State Level Bulletin, Agrimet Division, IMD preparing National AAS bulletin

Organised different training programmes.Established feedback mechanism

Economic benefits from savings in farm inputs.Increased farm productivity

Farmer Portal

Dissemination of Agromet Advisory1. Mass Mode All India radio, Television, Print Media

2. Outreach at Village level Ministry of IT Internet based Village Connectivity Web Pages: IMD, SAUs, ICAR Web Pages Mobile Phones (SMS & IVRS) through Public & private agencies “Kisan SMS”, a portal for farmers under www.farmer.gov.in 8.9 million farmers Kisan Call Centres

3. Human face for advisory dissemination KVK (ICAR): Training + interaction DAO (SDA): Coordinate Farm inputs with Line Dept. in

rhythm of weather forecast NGOs & other intermediary groups, Awareness Programme

Automation of AAS bulletin preparation

IMD in collaboration with Department of Agriculture & Cooperation (DAC) automated the process of AAS bulletin preparation by 130 AMFUs through Kisan portal (farmer.gov.in).

In addition, Regional Meteorological Centres (RMCs) / Meteorological Centres (MCs) of IMD also upload the moderated forecast in the portal for their respective States.

Agromet Field Units (AMFUs) immediately access the forecast and use it for the preparation of Agromet Advisories.

Transfer of data from Disc to the server of Agriculture Ministry, New Delhi.

Other Proposed ICT Initiatives Interactive portals (in regional languages) Multimodel Support: Audio, Video, Image, Text Multi Platform Backend: Web based and frontend: Mobile interface

Domain: Agriculture, Horticulture, Livestock and Fisheries Multi Linkages: Agri Experts, Knowledge Institutions (SAU/ ICAR

Institutes), Service Providers (Financial / input etc.),Personalized Information in appropriate mode, Farm and Farmer Database including soil, water, nutrients, GIS parameters etc.

ICT based agricultural information dissemination models: esagu, e aqua, Deal, Agrosense, Integrated Agri Services Program (IASP)

Media Lab Asia : An Interactive Information Dissemination System (IIDS): Using Web, IVRS and Mobile technology: through Krishi Vigyan Kendras of ICAR and Common Service Centres of NeGP

AAS BULLETIN BASED ON

EXTENDED RANGE WEATHER

FORECAST

IMD in Collaboration with Indian Institute of Tropical Meteorology, Pune started on a pilot mode experimental Agromet Advisory bulletin.

The ERFS bulletin has mainly three components:

i.Realized rainfall for the preceding two weeks.ii.Rainfall forecast of 4 pentads (5 days each). iii.Broad Agromet Advisories based on the realized and forecasted rainfall along with crop status for six homogeneous regions viz. South India, West India, Central India, East India, North India and Northeast India

NATIONAL AGROMET ADVISORY BULLETIN FOR

PREPAREDNESS BASED ON MONTHLY

RAINFALL FORECAST FOR JUNE 2015

Prepared byEarth System Science Organisation

India Meteorological DepartmentIndian Institute of Tropical Meteorology,

PuneMonthly Rainfall Forecast for June 2015

Monthly Rainfall Forecast for June 2015

Agromet Advisories

for preparedness for land preparation and sowing

of kharif crops

AAS BULLETIN

BASED SEASONAL

WEATHER FORECAST

Agromet Advisories for Preparedness under Kharif

Crop Campaignbased on Seasonal Rainfall

Forecast  prepared by

 Earth System Science Organisation

India Meteorological Department

&Indian Institute of Tropical

Meteorology, PuneOperational Seasonal Rainfall Forecast for Monsoon 2015

Advisory Based on operational and experimental rainfall forecast

Status of Surface Soil Moisture from Passive Microwave Radiometer,

AMSR-2

Waterlogged

Lo

w

Mo

de

rate

Hig

h

Ve

ry h

igh

Status of Surface Soil Moisture from SMOS

Input data required by this model are •Rainfall•Actual evapotranspiration estimated from potential evapotranspiration and •Soil water content, and •Available water storage capacity.

Simple Bucket Model method

Sowing Suitability using INSAT and AMSR-2 data

Probably sown area

Conducive area for sowing

Permanent agricultural area

The maps shows the sown area and area conducive for sowing. Sowing Suitability of crops during kharif season is initiated using the satellite data (AMSR-2 Soil moisture content INSAT 3A CCD NDVI). 

Initiatives with ISRO

Change in agricultural vigorfrom long-term mean

No

+ve

-ve

Status of Agricultural Vigor from INSAT 3A

The agriculture vigour over India is compared with its long term-mean using INSAT 3A CCD NDVI. Positive change in agricultural vigour as compared to long-term mean is observed in major agricultural patches of India till the end of the week of 1st July 2015.

Status of Agricultural Vigor from INSAT 3 A

Satellite based products for Operational Agrometeorology• In season monitoring of crop

area• LST PRODUCT FROM Kalpana

1 VHRR• Daily Surface Insolation product

from Kalpana 1 VHRR• Surface Soil wetness index

(SWI)• Evapotranspiration using

surface energy balance for irrigation scheduling

• Monthly estimates of PET from VHRR insolation and WRF forecast

• Delineation of alarm zones to alert farmers

Economic Assessment by NCAP on IAAS estimated 10-25% economic benefit obtained by the farmers.

Potential economic benefit estimated by NCAER, Rs.50,000 crores per year (used by 24% farmers).

Extrapolation can rise to Rs.211,000 crores if the entire farming community were to apply Agromet information to their agricultural activity.

Economic Impact of IAAS

Future Plans Improving Observations

Sattelite, Radars, AWS/ARG, SG, LDR, GPS-Sonde, MRR, MR, WP, Aircraft, Drop-sonde, UAV etc

Improving Data Assimilation and Models Integrated R&D

Monsoon Mission, Mountain Met, Severe Weather Improving Forecast

Block level Forecast System Extended Range Forecast Seasonal Forecast (RCC)

Better Service Delivery & information dissemination Aviation Services Agro-Meteorological Services HydroMet etc. etc.

Thank youThank you