The Role of PAGASA in Disaster Mitigation

Christopher F. Perez

2017 ACTS Workshop on Extreme Weather Forecast and Water

Resource Management

Hanoi, VietnamSeptember 26-27, 2017

Tropical Storm AMANG(Mekkhala), Jan. 14-19 20151st Tropical Cyclone in 2015, during Papal Visit in Tacloban

Forecast 6hrly Actual hrly

Critical decision point (8PM Jan. 16 – 4AM Jan 17): Critical Analyses made

4- 5 AM 17 Jan –started to recurve

12MN to 8AM 17 Jan – closely observing/ monitoring the track of TS Amang

• Starting 8PM, Jan 16, TS Amang unexpectedly shifted directions from northwest to southwest raising the possibility of directly hitting Tacloban.

• At 3-4AM Jan17,we observed the slowing down of movement of Amang.• At 4-5 am TS Amang started to recurve westward a significant development indicating

it would follow a northwesterly track as earlier predicted by PAGASA.

Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAGASA)

• Mission: Protecting lives, properties and livelihoodsthrough timely, accurate and reliable weather-related information and services.

• as the National Meteorological and HydrologicalServices (NMHS) of the Philippines shall be the“authoritative” voice in providing the warningagainst weather hazards for public safety.

OFFICE OF THE ADMINISTRATOR3 Deputy Administrators• Administration & Engineering Services• Operations & Services• Research & Development

Administrative Division

Financial, Planning and Management

Division

Engineering and Technical Services

Division

Weather DivisionClimatology and

AgrometeorologyDivision

Research & Development and Training Division

Hydro-Meteorology Division

PAGASA Regional Services Divisions

(5)

Field Stations

National Capital Region

Northern Luzon

Southern Luzon

Visayas

MindanaoSynoptic Observation Network

Flood Forecasting Warning Centers

Agromet Observation Network

Radar Network

Upper-Air Observation Network

AWS Network

Rainfall Station Network

PAGASA ORGANIZATIONAL

CHART

An average of 19 - 22 tropical cyclones enter /develop inside the Philippine Area of Responsibility (PAR) every year, about 8 – 9 make landfall.

0.50.3 0.3 0.4

0.9

1.5

3.4 3.4 3.1

2.7

2.3

1.4

0

1

2

3

4

5

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

Monthly Average Tropical Cyclone

Occurrences within the PAR

Consolidated tropical cyclone track within the PAR for the period 1951 – 2000.

TCWS

LEAD

TIME *

(hrs)

WINDS (KPH) IMPACTS OF THE WIND

#1 36 30 - 60

No damage to low risk

structure to very light

damage

#2 24 61-120 Light to moderate damage

#3 18 121-170 Moderate to heavy damage

#4 12 171-220 Heavy to very heavy damage

#5 12more than

220

Very heavy to widespread

damage

Tropical Cyclone Warning System

Tropical Cyclone Warning Signals (TCWS)

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

Twitter: @dost_pagasawww.facebook.com/PAGASA.DOST.GOV.PH

Mode of Dissemination

FOR ANY EARLY WARNING SYSTEM TO SUCCEED, SEVERAL COMPONENTS ARE NECESSARY:

• Technology to detect and monitor the hazard;

• Communication systems to alert the public;

• Local leaders trained to make the right decisions;

• A public that is educated to react appropriately to warnings; and

• Response protocols — such as evacuation plans —prepared and rehearsed well in advance of the threat.

All these elements must work well,both individually and in harmony.

Failure in any one of these elementscan mean failure of the whole earlywarning system.

MERANTI Strongest typhoon at landfall over

any part of the Philippines in 2016

A REVISIT

First bulletin

issued by

PAGASA

11/0000 UTC

Entered PAR

Became Typhoon

11/0600 UTC

Reached Peak

Intensity

13/1200 UTC

Landfall over

Itbayat island

13/1700 UTC

Left PAR

Last bulletin issued

by PAGASA

14/0600 UTC

TRACK OF TYPHOON MERANTI (1718)

11/0000 UTC TO 14/0600 UTC

Meranti underwent

rapid intensification

over the Philippine

Sea before reaching

Luzon strait

RI T+12H (≥ +20 kt)

RI T+24H (≥ +30 kt)

RI T+36H (≥ +40 kt)

RI T+48H (≥ +50 kt)

RI definition based on

Kaplan et al. (2010)

LANDFALL

Doppler Weather

Radar Loop

Central Weather

Bureau, Taiwan

ITBAYAT

98132 Itbayat

BASCO

98134

CALAYAN

98133

APARRI

98232

HENGCHUN

59559

TAIDONG

59562

PAGASA-DOST Aparri Doppler Weather Radar

13 September 2016, 1500 UTC to 1900 UTC

ITBAYAT

98132

BASCO

98134

HENGCHUN

59559

CALAYAN

98133

APARRI

98232

Data rendered

unusable

beyond

13/1630 UTC

Last usable data

13/ 1630 UTC:

STN: 915.0 hPa

MSL: 927.9 hPa

12

AM

6

AM

12

PM

6

PM

MICROBAROGRAM

98132 Itbayat

METEOGRAM

98134 BASCO

Lowest pressure:

927.3 hPa

(1630 UTC)

Highest

observed wind

NNE, 40 m/s

(1600 UTC)

NOTE:

• Microbarograph data from Itbayat (98132) alone could have been used

to determine actual (near-peak or peak) intensity of Typhoon Meranti in

terms of mean sea level pressure since the eye passed over the island.

However, last usable data was 30 minutes before landfall or when the

center fix was around 10 km from the station. Inferring that the

central pressure was around 920 hPa given the last usable data doesn’t

make sense since the barograph tracing suggests that the pressure

was still rapidly dropping.

• Basco (98134) was able to capture the v-like feature on the

microbarograph before it ceased transmitting data (the stations was

able to observe pressure data before, during and after the passage of

the core). However, the center fix was still at least 25 km from the

station during the entire passage (to put into perspective, radius of

maximum winds (RMW) was 22 km based on JTWC best track data).

QUESTION

What was the actual intensity (near-peak or

peak) of Typhoon Meranti in terms of MSLP

based on ground observations from these 2

stations and from other stations in the periphery

of the tropical cyclone?

SOLUTION

Use the typhoon pressure profile model H80

that best fits observation data from 0300 to 1800

UTC 13 September from 6 stations in Southern

Taiwan – Extreme Northern Luzon area.

𝑷 𝒓 = 𝑷𝒄 + ∆𝑷𝒆−𝑹𝑴𝑾𝒓

𝑩

∆𝑷 = 𝑷𝒆𝒏𝒗 − 𝑷𝒄(Holland 1980, Holland 2008)

𝑷𝒆𝒏𝒗 = 𝑷𝑶𝑪𝑰 + 𝟐(Courtney and Knaff 2009)

ASSUMPTION

• B parameter limited from 1.0 to 2.5 (Holland 1980) at 0.5 intervals.

• Possible values of central pressure range from 850 to 925 hPa at 5 hPa intervals.

• Meranti is assumed to have symmetric, circular pressure field during the period used.

• Environmental Pressure (Penv) = 1009 hPa and RMW = 22 km (JTWC best track data).

• Pressure profile did not change significantly from 0300 to 1800 UTC 13 September

• Pressure data from all 6 stations are reliable

• Given that Meranti was undergoing an eyewall replacement cycle, RMW still co-located in

the inner eyewall.

Hourly Satellite and Radar Fixes

of Typhoon Meranti

0300 – 1800 UTC 13 September

Taidong

22.750°N, 121.150°E

Hengchun

22.000°N, 120.750°E

Itbayat

20.767°N, 121.833°E

Basco

20.450°N, 121.970°E

Calayan

19.263°N, 121.470°E

Aparri

18.358°N, 121.637°E

2 stations within the core

4 stations in the periphery

MSLP Observations from Synoptic Stations in

Southern Taiwan and Extreme Northern Luzon

0300 – 1800 UTC 13 September

74 observation data from

0300 UTC to 1800 UTC

Philippines: Hourly

Taiwan: 3-Hourly

RMSE OF VARIOUS H80 PRESSURE MODELS

(VARYING B PARAMETER AND CENTRAL

PRESSURE)

0300 – 1800 UTC 13 September

Possible H80 models:

Model Equation RMSD (hPa)

𝑃 𝑟 = 895 + 114𝑒−22𝑟

1

5.518415958

𝑃 𝑟 = 896 + 113𝑒−22𝑟

1

5.49152158

𝑃 𝑟 = 897 + 112𝑒−22𝑟

1

5.472818199

𝑃 𝑟 = 898 + 111𝑒−22𝑟

1

5.462389954

𝑷 𝒓 = 𝟖𝟗𝟗 + 𝟏𝟏𝟎𝒆−𝟐𝟐𝒓

𝟏

5.460284258

𝑃 𝑟 = 900 + 109𝑒−22𝑟

1

5.466510728

Central Pressure: 895 to 900 hPa

Environmental Pressure: 1009 hPa

Radius of Maximum Winds: 22 km

FINDINGS

• Based on MSLP observation from 6 synoptic stations in Southern Taiwan

and Extreme Northern Luzon, the H80 model that best describes the

pressure profile of Typhoon Meranti near landfall (following

aforementioned assumptions) suggests that the central pressure of

Meranti falls between 895 and 900 hPa, possibly 899 hPa. This

represents the near-peak or peak intensity of Meranti.

• To put the obtained value into perspective, JMA and JTWC puts the

lowest central pressure of Meranti at 890 and 887 hPa, respectively

• However, it was also noted that H80 models using 895 to 900 hPa as

central pressure and 1.0 as Holland B parameter yields lower MSLP over

radial distances above 150 km when compared with observation data.

Nevertheless, these models yielded the best pressure profile when

compared against observation following the assumptions stated earlier.

SOME NOTES

• Mean wind and gust observations were not used in determining the

landfall intensity of Typhoon Meranti due to doubts on the reliability of

instrument readings under such wind exposure. Both Itbayat and Basco

stations reported damaged wind sensors in the aftermath of the passage,

which puts into question the reliability of observed wind while the stations

were within the eyewall of the Typhoon.

• Perform similar analysis on other intense landfalling tropical cyclones

during the 2016 season (i.e. Super Typhoon Haima / Lawin and Typhoon

Nock-ten / Nina) in order to verify if Meranti was indeed the strongest

tropical cyclone to make landfall in any part of the Philippines in 2016.

Nevertheless, the findings on this report puts Meranti as one of the

strongest to make landfall in 2016 and possibly since modern PAGASA

records began in 1950s.

REFERENCES

Courtney, J., and J.A. Knaff, 2009: Adapting the Knaff and Zehr Wind-Pressure

Relationship for operational use in Tropical Cyclone Warning Centres. Australian

Meteorological and Oceanographic Journal, 58:3, 167-179.

Holland, G.J., 1980: An Analytic Model of the Wind and Pressure Profiles in

Hurricanes. Mon. Wea. Rev., 108, 1212–1218, https://doi.org/10.1175/1520-

0493(1980)108<1212:AAMOTW>2.0.CO;2

Holland, G., 2008: A Revised Hurricane Pressure–Wind Model. Mon. Wea. Rev., 136,

3432–3445, https://doi.org/10.1175/2008MWR2395.1

Kaplan, J., M. DeMaria, and J.A. Knaff, 2010: A Revised Tropical Cyclone Rapid

Intensification Index for the Atlantic and Eastern North Pacific Basins. Wea.

Forecasting, 25, 220–241, https://doi.org/10.1175/2009WAF2222280.1

EXTERNAL DATASET

• Best Track Data for 2016 from Japan Meteorological Agency (JMA) and Joint

Typhoon Warning Center (JTWC)

• Weather Radar Composite from Central Weather Bureau (CWB)

• Inset satellite images from Naval Research Laboratory (NRL)

Thank you for

your attention.