The Role of PAGASA in Disaster Mitigation - APEC Typhoon - Christopher Per… · The Role of PAGASA...
Transcript of The Role of PAGASA in Disaster Mitigation - APEC Typhoon - Christopher Per… · The Role of PAGASA...
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.