Indices and Early Warning Systems in the Philippines

Flaviana D. Hilario, Ph.D.Weather Services Chief

Climatology and Agrometeorology Division PAGASA/DOST

Holiday Inn Downtown, Lincoln, Nebraska, USA, 8-11 December 2009

IMPACTS OF ENSO and NONIMPACTS OF ENSO and NON--ENSO ON ENSO ON PHILIPPINE ANNUAL RAINFALLPHILIPPINE ANNUAL RAINFALL

REDRED colored years arecolored years are EL NINOEL NINO years, years,

Legend: Potential Legend: Potential Areas Under Areas Under Severe drought Severe drought impactsimpactsDrought impacts Drought impacts with major losseswith major losses

Moderate drought Moderate drought impactsimpacts

Near normal to Near normal to above normal above normal conditionconditionWay above normal Way above normal conditioncondition

Flood damageFlood damage

Severe flood Severe flood damagedamage

BLUEBLUE colored years are colored years are LA NINALA NINA yearsyearsand and BLACKBLACK colored years are colored years are NON_ENSONON_ENSO yearsyears

Drought Events Areas Affected Damages

1. 1982-1983

Oct. 1982 – March 1983

Apr. 1983 – Sept. 1983

Western and Central Luzon, Southern TagalogProvinces, Northern Visayas, Bohol and Western MindanaoModerate to severe drought affected most of Luzon, Negros Occidental and Iloilo

6.4 x 105 mt of rice and corn; insurance claims amounted to P38 M; hydropower generation loss was P 316 M

2. 1986-1987

Oct. 1986 – March 1987

Apr. 1987 – Sept. 1987

Severe drought affected Bicol Region, Southern Negros, Cebu, and Western Mindanao; Severe drought affected mainland of Luzon, Central Visayas and Western Mindanao

Estimated agricultural damages of P 47 M

Estimated hydro-energy generation loss was P 671 M

3. 1989-1990

Oct. 1989 – March 1990

Drought affected Cagayan Valley, PanayIsland, Guimaras, Palawan and Southern Mindanao; Affected rice and corn area totaled 283,562 hectares; major multipurpose water reservoirs reduced inflow

Estimated 5 x 105 mt of rice and corn production losses; hydropower generation loss of P 348 M; 10% cutback in water production in Metro Manila

4. 1991-1992 Severe drought affected Manila, Central and Western Visayas and Cagayan Valley; affected agricultural area of 461,800 hectares

P 4.09 Billion agricultural losses; 20 % shortfall in Metro Manila water supply

5. 1997-1998 About 70 % of the Philippines experienced severe drought; about 292,000 hectares of rice and corn area completely damaged

622,106 mt of rice production loss and 565,240 mt of corn amounting to P 3 B; water shortages; forest fires and human health impacts

List of Drought Events in the Philippines During the Period 1982-1998

• Percent of Normal (monthly rainfall)

•Generalized Monsoon Index (GMI)

• Crop Condition Assessment

Yield Moisture Index (YMI)Moisture Availability Index (MAI)

• helps determines the performance of the rains during the season

• serves as a good indicator of potential irrigation supplies.

•The GMI for southwest monsoon (GMIsw) is defined as:GMIsw = wiPi = w6P6 + w7P7 + w8P8 + w9P9

where: w = weight coefficient of ith monthly rainfall for the seasonP = rainfall amount in the ith month

•The GMI for northeast monsoon (GMIne) is defined as:

GMIne = wiPi = w10P10 + w11P11 + w12P12 + w1P1where: w = weight coefficient of ith monthly rainfall for the season

P = rainfall amount in the ith month

• a simple index that can assess agroclimatic crop conditions

• the data required in the computation of YMI – 1) crop calendar information, 2) crop coefficient 3) monthly rainfall data

•it is defined as:

YMI = kiPiwhere: i = indicates the crop stage (1 = planting/transplanting,

2 = vegetative, 3 = flowering, 4 = maturity)

k = is the appropriate crop coefficient for the ith crop stage of growthP = is the rainfall during the ith crop stage

Interpretation of YMI

Percentile Rank Interpretation

81 - 100 Potential for flood damage41 - 80 Near normal to above normal

crop condition21 - 40 Moderate drought impact with

reduced yield 11 - 20 Drought impact with major

yield losses 0 - 10 Severe drought impact with crop failure

and potential food shortages

Perc e ntile R a nk o f G M Isw for Iba

0

10

20

30

40

50

60

70

80

90

100

1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999

ye ar

% R

ank

% rank

Rainfall in Percentile Rank OND

CRITERIA For Rainfall Deficit

CRITICAL – 1 to 2 months of < or =40%from the normal

DROUGHT – 3 consecutive months of< or =40% from the normal

OR 5 consecutive months of below

normal (41%-80%) rainfall condition

MODERATE - 1 to 2 months below normal (41%-80%) rainfall condition

DRY SPELL - 3 consecutive months of below normal(41%-80%) rainfall condition

PERCENTAGE RAINFALL CONDITION

< 40%

41% - 80%

81% - 120%

> 120 %

below normal

near normal

above normal

way below normal

PERCENTAGE RAINFALL CONDITION

< 40%

41% - 80%

81% - 120%

> 120 %

PERCENTAGE RAINFALL CONDITION

< 40%

41% - 80%

81% - 120%

> 120 %

below normal

near normal

above normal

way below normal

Actual Rainfall Analysis in Percent of Normal (May to Nov 2009)

A c t u a l R a i n f a l l A n a l y s i s i n P e r c e n t o f N o r m a l ( S e p t e m b e r t o N o v e m b e r 2 0 0 9 )P R O V I N C E % N S e p % N O c t % N N o v P R O V I N C E % N S e p % N O c t % N N o v

C O R D I L L E R A A D M I N I S T R A T I V E R E G I O N ( C A R ) R E G I O N V I ( W E S T E R N V I S A Y A S )A B R A 1 2 5 . 8 5 4 8 . 9 6 3 . 5 A K L A N 9 2 . 6 6 8 . 2 7 3 . 7

B E N G U E T 1 0 4 . 1 5 6 0 . 5 3 8 . 3 A N T I Q U E 1 0 0 . 4 8 0 . 0 5 6 . 3I F U G A O 1 2 8 . 0 3 8 8 . 7 9 5 . 1 C A P I Z 6 5 . 6 7 3 . 1 7 9 . 5

K A L I N G A 1 4 5 . 8 3 6 0 . 4 8 1 . 6 G U I M A R A S 1 2 3 . 1 9 7 . 7 3 4 . 0A P A Y A O 1 3 1 . 4 3 5 2 . 3 5 9 . 6 I L O I L O 9 1 . 7 8 4 . 1 5 7 . 6

M O U N T A I N P R O V I N C E 1 3 4 . 8 4 3 9 . 3 8 4 . 1 N E G R O S O C C I D E N T A L 1 1 6 . 7 8 5 . 4 5 3 . 0R E G I O N I

I L O C O S N O R T E 9 7 . 6 5 3 2 . 9 6 0 . 5 R E G I O N V I I ( C E N T R A L V I S A Y A S )I L O C O S S U R 1 2 8 . 3 6 7 7 . 0 3 7 . 7 B O H O L 5 8 . 3 1 8 . 8 1 4 5 . 2

L A U N I O N 1 1 5 . 5 6 8 8 . 8 2 4 . 4 C E B U 8 3 . 7 4 8 . 4 9 2 . 3P A N G A S I N A N 1 5 0 . 8 3 5 1 . 0 6 . 8 N E G R O S O R I E N T A L 1 0 6 . 9 8 3 . 6 5 8 . 8

R E G I O N I I S I Q U I J O R 7 2 . 8 5 6 . 7 1 0 0 . 2B A T A N E S 6 5 . 8 1 2 8 . 2 2 1 . 8 R E G I O N V I I I ( E A S T E R N V I S A Y A S )C A G A Y A N 1 5 4 . 8 1 5 7 . 4 5 9 . 8 B I L I R A N 8 0 . 8 6 7 . 5 7 7 . 0

I S A B E L A 1 4 8 . 6 1 1 8 . 4 1 1 2 . 2 E A S T E R N S A M A R 4 9 . 2 5 3 . 5 9 9 . 8N U E V A V I Z C A Y A 1 0 9 . 8 2 8 0 . 5 6 3 . 2 L E Y T E 9 7 . 3 5 1 . 9 1 0 2 . 9

Q U I R I N O 1 1 8 . 7 1 5 0 . 3 9 1 . 7 N O R T H E R N S A M A R 5 6 . 5 5 1 . 4 7 2 . 5R E G I O N I I I ( C E N T R A L L U Z O N ) W E S T E R N S A M A R ) 5 9 . 6 6 4 . 7 8 1 . 3

B A T A A N 2 3 6 . 4 7 7 . 7 2 2 . 1 S O U T H E R N L E Y T E 9 2 . 5 3 6 . 7 1 3 5 . 5B U L A C A N 2 1 1 . 1 1 0 1 . 8 3 3 . 5 R E G I O N I X ( Z A M B O A N G A P E N I N S U L A )

N U E V A E C I J A 1 4 3 . 8 1 7 2 . 9 3 1 . 0 Z A M B O A N G A D E L N O R T E 1 4 2 . 6 7 0 . 6 1 0 1 . 5P A M P A N G A 2 1 8 . 7 1 1 0 . 1 2 6 . 1 Z A M B O A N G A D E L S U R 1 5 7 . 9 7 5 . 5 9 6 . 2

T A R L A C 1 8 9 . 3 1 7 5 . 8 1 4 . 3Z A M B A L E S 2 1 7 . 5 1 4 5 . 1 7 . 9 R E G I O N X ( N O R T H E R N M I N D A N A O )

A U R O R A 1 2 0 . 2 9 6 . 3 5 8 . 2 B U K I D N O N 1 0 8 . 9 8 0 . 6 1 0 1 . 7N A T I O N A L C A P I T A L R E G I O N C A M I G U I N 6 3 . 2 2 7 . 8 1 2 7 . 5

M E T R O M A N I L A 2 5 5 . 3 8 4 . 5 5 6 . 0 L A N A O D E L N O R T E 9 4 . 6 7 2 . 4 8 6 . 3R E G I O N I V - A ( C A L A B A R Z O N ) M I S A M I S O C C I D E N T A L 8 9 . 4 6 0 . 4 1 0 7 . 9

B A T A N G A S 1 9 1 . 4 7 3 . 3 3 5 . 5 M I S A M I S O R I E N T A L 7 7 . 3 4 5 . 5 1 1 5 . 7C A V I T E 2 4 1 . 2 7 0 . 6 2 9 . 4 R E G I O N X I ( D A V A O R E G I O N )

L A G U N A 2 0 3 . 1 9 1 . 5 4 5 . 4R I Z A L 2 2 4 . 1 8 1 . 4 3 3 . 2 D A V A O 1 1 2 . 3 8 4 . 6 1 4 3 . 3

Q U E Z O N 1 4 0 . 0 8 2 . 4 5 4 . 7 D A V A O D E L S U R 8 5 . 8 5 6 . 6 7 2 . 7R E G I O N I V - B ( M I M A R O P A ) D A V A O O R I E N T A L 4 1 . 7 4 1 . 7 1 2 0 . 7

M A R I N D U Q U E 1 3 7 . 8 7 4 . 8 5 6 . 0 R E G I O N X I I ( S O C C S K S A R G E N )O C C I D E N T A L M I N D O R O 1 8 5 . 0 6 0 . 9 2 8 . 0 S O U T H C O T A B A T O 1 2 5 . 8 5 8 . 4 5 4 . 6

O R I E N T A L M I N D O R O 1 6 2 . 3 5 5 . 7 3 7 . 2 C O T A B A T O 1 3 1 . 6 8 8 . 3 8 7 . 0R O M B L O N 1 5 5 . 1 5 2 . 0 5 1 . 1 S A R A N G A N I 1 0 2 . 1 4 3 . 5 4 5 . 8P A L A W A N 1 1 1 . 4 8 7 . 4 1 7 . 1 S U L T A N K U D A R A T 1 4 9 . 6 7 4 . 5 7 1 . 9

R E G I O N V ( B I C O L ) R E G I O N X I I I - C A R A G AA L B A Y 9 9 . 8 1 2 1 . 0 4 6 . 1 A G U S A N D E L N O R T E 4 5 . 3 3 6 . 8 2 0 8 . 1

C A M A R I N E S N O R T E 1 3 9 . 0 9 2 . 0 6 5 . 5 A G U S A N D E L S U R 7 8 . 2 7 4 . 5 1 8 4 . 4C A M A R I N E S S U R 1 2 1 . 4 1 2 8 . 1 5 7 . 6 S U R I G A O D E L N O R T E 7 2 . 9 3 5 . 1 1 7 5 . 7

C A T A N D U A N E S 6 9 . 0 9 6 . 4 5 6 . 3 S U R I G A O D E L S U R 5 8 . 9 6 8 . 4 2 1 2 . 1M A S B A T E 1 0 4 . 6 7 0 . 8 3 2 . 3 A R M M

S O R S O G O N 8 6 . 3 9 0 . 1 4 8 . 7 B A S I L A N 2 2 8 . 6 7 8 . 0 8 5 . 6M A G U I N D A N A O 1 6 9 . 5 9 3 . 0 8 8 . 2

L A N A O D E L S U R 1 0 4 . 0 8 3 . 1 6 7 . 2S U L U 2 2 9 . 8 7 8 . 9 7 5 . 8

Actual Rainfall Analysis in Percent of Normal (Sept. to Nov. 2009)

Schematic Diagram of NEEWMSSchematic Diagram of NEEWMSDATA BASES

HISTORICAL NORMALS EPISODIC EVENTS

INFORMATION FROM OTHER SOURCES

ANALYSIS/ASSESSMENT METHODOLOGIES AND

PROCEDURES

NEAR REAL-TIME METEOROLOGICAL DATA

CLIMATE UPDATES AND FORECASTS/DROUGHT ADVISORIES/POTENTIAL IMPACT ASSESSMENT

END USERS1. Inter-Agency Committee on Water Crisis Management2. National Disaster Coordinating Council3. Inter-Agency Technical Working Group on Cereals and Feed

Grains4. El Niño National Action Team5. Media6. General Public and other End-Users