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BAGYO NA NAMAN, O KAY HIRAP NG BUHAY,                        Filipino Version
BAGYO! BAGYO! BAGYO! Na naman muli.          
by Jose Ramon G. Albert, Ph.D. 1

BAGYO NA NAMAN O KAY HIRAP NG BUHAY BAGYO! BAGYO! BAGYO! Na naman muliHazards of nature such as tropical cyclones, floods, droughts, storm surges (tidal waves), landslides, earthquakes, volcanic hazards, tornadoes and tsunamis, are physical forces that may transform into disasters when they occur in populated areas. Disasters2 are not natural, i.e., they are all man-made, in the sense that natural hazards will not become disasters if the population is not exposed to these hazards, and if we can focus on reducing the vulnerability and risk of people from the impacts of hazards.  Even where disasters have natural triggers that cannot be prevented, their impact can generally be greatly reduced by understanding who within the populace are vulnerable and then acting to reduce this vulnerability, before the hazard of nature becomes a disaster.

Earthquakes and climate disasters are regular phenomena in the Philippines.  In fact, the World Risk Report 20123 categorized the Philippines as the third most disaster-prone country in the world, following the small island Pacific nations of Vanuatu and Tonga, mainly due to high exposure to natural calamities.  With the regularity of the occurrence of storms in the country, the words of the Christmas song “Pasko na naman” :  “Pasko na naman, O Kay Tulin ng Araw… Paskong nagdaan, tila ba kung kailan lang .…Pasko! Pasko! Pasko na naman muli” can easily be changed to “Bagyo na naman .… “  From 1948 to 2011, the annual average frequency of tropical cyclones that entered the Philippine Area of Responsibility (PAR) is 19 (Table 1).

Typhoon Pablo (international name Bopha) is the 16th tropical cyclone that entered PAR this year.  Typhoon Pablo hit Mindanao with its brutal maximum sustained winds that reached 185 kph and a 500 kilometer wide rain band.  The country’s weather bureau, the Philippine Atmospheric Geophysical and Astronomical Services Administration (PAGASA) considers it as a super typhoon, the strongest storm to hit Mindanao in two decades and for the second consecutive December a tropical cyclone battered Mindanao. While the frequency of tropical cyclones has not changed considerably in the country, the characteristics of these hazards have changed:

Bagyo, patuloy ang pagbayo

From 1948 to 2011, a total of 1,234 tropical cyclones have entered PAR. Of these:  270 are tropical depressions, 354 are tropical storms and 610 are considered typhoons. (Table 3)  Typhoon Uring (international name Thelma) which occurred in 1991 and was registered with highest wind speed of only 95 kph (a tropical storm TC category) was the deadliest (killing 5,101 people) and very costly (causing 1.045 billion pesos worth of damage to property). (Table 4)

For the last 5 years, i.e., 2008 to 2012, the Philippines was always in the top three countries with the highest number of natural disasters (Center for Research on the Epidemiology of Disasters, CRED, Annual Disaster Statistical Review)4.  The most frequent of these disasters were hydrometeorological (storms, floods and wet mass movement) ones.

 

Changing Climate Changing Patterns

The Intergovernmental Panel on Climate Change (IPCC), in their four comprehensive assessments found that global average surface temperature has increased over the past one and half centuries, and that this global warming cannot be attributed solely to natural variability. The 2007 IPCC report suggested that this temperature has increased by 0.76°C in the 150 year period and that this climate change is largely a result of human induced greenhouse gas (GHG) emissions.  A special IPCC report (2012) tightens the link between human-induced climate change and extreme weather and climate events.

 

There are those who suggest that these changes in the nature of hazards is partly a result of human induced climate change. Thus, our delegation to the recent Climate Change meeting in Doha used emotional language to help convince the world to make the necessary actions to limit GHG emissions. Unfortunately, some countries which have the biggest GHG emissions are not willing to commit to limiting their GHG emissions.  There are also some of us who think that business as usual can continue without consequences: definitive policies on population management and risk reduction, for instance, have not been extensively developed.  As a victim of Ondoy when I used to live in Provident Village, I cannot understand why villages were allowed to be established in areas that are at risk of regular occurrences of hazards. We have to look into the disaster statistics, and recognize that we can’t continue to keep on mopping the floor without closing the tap that causes the floors to get wet. We have to commit to change, dear friends, and we have to act with urgency!  As Sister Stella L. once said “Kung di tayo kikilos, sino pa? Kung di ngayon, kalian pa?

Let us look at what these numbers are saying.  Let us also go beyond the numbers and do something now lest we experience for ourselves the dire consequences of disasters and catastrophic events brought about not only by nature but by our actions (or lack of the proper responses).  As the saying goes, “Sa ngit-ngit ng kalikasan, lintik lang ang walang ganti.”

 

 

________________________________

1 Secretary General of the National Statistical Coordination Board (NSCB). The NSCB, a statistical agency functionally attached to the National Economic and Development Authority (NEDA), is the highest policy making and coordinating body on statistical matters in the Philippines. Immediately prior to his appointment at NSCB, Dr. Albert was a Senior Research Fellow at the Philippine Institute for Development Studies, a policy think tank attached to NEDA. Dr. Albert finished summa cum laude with a Bachelor of Science degree in Applied Mathematics from the De La Salle University in 1988. He completed a Master of Science in Statistics from the State University of New York at Stony Brook in 1989 and a Ph.D. in Statistics from the same university in 1993. He is an Adjunct Faculty of the Asian Institute of Management. He is also a past President of the Philippine Statistical Association, a Fellow of the Social Weather Stations, and an Elected Regular Member of the National Research Council of the Philippines.

This article was co-written by Mr. Edward Eugenio P. Lopez-Dee, Statistical Coordination Officer VI of the NSCB. This article was translated in Filipino by Mr. Ruben V. Litan of NSCB. The authors thank Mr. Genesis G. Cuizon, Ms. Ma. Libertie V. Masculino, and Mr. Dennis E. San Diego, SCO I, Statistical Coordination Officer (SCO) IV, and Artist/Illustrator of the NSCB, respectively, for the assistance in the preparation of the article. The views expressed in the article are those of the authors and do not necessarily reflect those of the NSCB and its Technical Staff.

2 The Center for Research on the Epidemiology of Disasters (CRED) defines a disaster as “a situation or event which overwhelms local capacity, necessitating a request to a national or international level for external assistance; an unforeseen and often sudden event that causes great damage, destruction and human suffering”.

3 Beck, Michael W., Christine C. Shepard, Jörn Birkmann, Jakob Rhyner, Torsten Welle, Maximilian Witting, Jan Wolfertz, Jens Martens, Katja Maurer, Peter Mucke, and Katrin Radtke. World Risk Report 2012. Alliance Development Works

4 CRED has been active for more than 35 years in the fields of international disaster and conflict health studies, with research and training activities linking relief, rehabilitation and development. It was established in Brussels in 1973 at the School of Public Health of the Catholic University of Louvain (UCL) as a non-profit institution with international status under Belgian law. In 1980, CRED became a World Health Organization (WHO) collaborating centre as part of WHO’s Global Program for Emergency Preparedness and Response. Since then, CRED has increased its international network substantially and collaborates closely with numerous UN agencies, inter-governmental and governmental institutions, non–governmental organizations, research institutes and universities. One of the publication of CRED is the Annual Disaster Statistical Review.

5 Can be accessed at http://www.emdat.be/

6 Thomas, V., Albert, J. R and Perez, R. 2012. Climate – Related Disasters in Asia and the Pacific. A working paper, September 2012.

 



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Table 1:Annual Frequency of Tropical Cyclone
in the Philippine Area of Responsibility (PAR)
1948 - 2011

Year Number of Tropical Cyclone Ratio
(Landed/
Total)
Rank
Total Landed/
Crossed
1948 20 11 0.5500 27
1949 22 9 0.4091 16
1950 15 5 0.3333 51
1951 13 8 0.6154 59
1952 27 16 0.5926 3
1953 18 10 0.5556 38
1954 18 9 0.5000 38
1955 15 4 0.2667 51
1956 25 12 0.4800 5
1957 15 9 0.6000 51
1958 17 4 0.2353 41
1959 19 7 0.3684 32
1960 19 8 0.4211 32
1961 23 8 0.3478 10
1962 21 7 0.3333 20
1963 16 6 0.3750 47
1964 31 15 0.4839 2
1965 21 7 0.3333 20
1966 23 13 0.5652 10
1967 21 9 0.4286 20
1968 15 6 0.4000 51
1969 15 5 0.3333 51
1970 21 13 0.6190 20
1971 27 16 0.5926 3
1972 17 6 0.3529 41
1973 12 9 0.7500 62
1974 23 13 0.5652 10
1975 15 6 0.4000 51
1976 22 5 0.2273 16
1977 19 10 0.5263 32
1978 25 10 0.4000 5
1979 22 13 0.5909 16
1980 23 16 0.6957 10
1981 23 8 0.3478 10
1982 21 9 0.4286 20
1983 23 10 0.4348 10
1984 20 8 0.4000 27
1985 17 8 0.4706 41
1986 21 11 0.5238 20
1987 16 7 0.4375 47
1988 20 9 0.4500 27
1989 19 9 0.4737 32
1990 20 6 0.3000 27
1991 19 11 0.5789 32
1992 15 4 0.2667 51
1993 32 19 0.5938 1
1994 25 9 0.3600 5
1995 16 10 0.6250 47
1996 17 10 0.5882 41
1997 14 4 0.2857 58
1998 11 6 0.5455 63
1999 16 7 0.4375 47
2000 18 10 0.5556 38
2001 17 10 0.5882 41
2002 13 6 0.4615 59
2003 25 12 0.4800 5
2004 25 10 0.4000 5
2005 17 7 0.4118 41
2006 20 9 0.4500 27
2007 13 4 0.3077 59
2008 21 11 0.5238 20
2009 22 11 0.5000 16
2010 11 2 0.1818 63
2011 19 8 0.4211 32
         
Average 19 9 0.4593  

Sources: PAGASA Website for 1948 to 2006; www.typhoon2000.com for 2007

 

Table 2: Greatest 24-Hr. Rainfall during the Passage of Tropical Cyclones:
1951 - 2010

Tropical Cyclone Name Station Greatest 24-HR Rainfall (MM) Date of Occurrence

Duration

TY Feria Baguio 1,085.8 07/04/01 Jul 02 - Jul 05
Ty Iliang Baguio 994.6 10/14/98 Oct 10 - Oct 16
TY Trining Baguio 979.4 10/17/67 Oct 14 - Oct 19
TY Susan Baguio 781.4 10/11/74 Oct 09 - Oct 12
TY Trining Baguio 760.0 10/27/91 Oct 20 0 Oct 31
TY Ditang Baguio 730.3 05/15/80 May 10 -  May 20
TS Chedeng Dagupan 722.6 05/27/03 May 25 - May 29
TYGading Baguio 709.6 07/09/86 Jul 06 - Jul 10
TY Aring  Baguio 698.7 11/05/80 Nov 01 - Nov 07
TY Wening Baguio 678.8 10/28/74 Oct 25 - Oct 29
TD Sisang Alabat 673.0 12/27/75 Dec 26 - Dec 28
TY Nitang Baguio 649.7 09/28/68 Sep - 23 Oct 01
TY Didang Baguio 605.3 05/25/76 May 12 - May 27
TS Aring Masbate 603.5 12/04/76 Dec 02 - Dec 07
TY Reming Surigao 564.7 11/18/68 Nov 12 - Nov 22
TY Cora Baguio 546.6 11/17/53 Nov 12 - Nov 19
TY Osang Baguio 536.3 07/25/80 Jul 20 - Jul 26
TS Miding Baguio 534.2 08/23/78 Aug 20 - Aug 27

Source: Climate Data Section, Climatological and Agrometeorology, PAGASA, DOST

 

Table 3: Distribution of Tropical Cyclones by Category
in the Philippine Area of Responsibility (PAR):
1948 - 2011

Year January February March April May June July August September October November December Annual
TD TS TY TD TS TY TD TS TY TD TS TY TD TS TY TD TS TY TD TS TY TD TS TY TD TS TY TD TS TY TD TS TY TD TS TY TD TS TY Total
1948 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 1 0 0 1 0 3 0 2 0 0 4 1 1 1 0 2 10 4 6 20
1949 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 3 1 0 1 1 1 2 0 0 3 0 2 1 0 0 2 3 5 14 22
1950 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 2 0 0 0 1 1 1 0 0 2 1 0 0 2 0 0 1 2 7 5 14
1951 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 2 0 2 0 0 2 0 0 1 0 0 1 0 0 2 2 0 11 13
1952 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 2 0 1 1 0 0 3 1 2 1 0 1 3 0 0 4 1 2 2 4 7 16 27
1953 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 1 4 0 0 2 1 0 1 0 2 1 1 1 0 2 5 11 18
1954 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 2 2 2 0 0 2 1 0 2 0 0 3 0 1 0 3 4 11 18
1955 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 1 2 0 0 1 1 1 2 0 0 1 0 0 1 2 4 9 15
1956 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 2 1 1 0 1 3 1 0 4 0 0 1 1 0 4 2 0 1 6 3 16 25
1957 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 0 0 1 1 0 1 0 0 3 0 2 1 0 0 1 0 0 0 2 3 10 15
1958 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 0 1 2 1 0 2 0 0 2 2 0 1 0 0 0 3 1 13 17
1959 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 3 0 1 1 0 1 3 1 0 2 0 0 2 1 5 12 18
1960 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 1 0 0 2 1 2 3 0 1 0 0 0 3 0 0 0 0 0 2 2 5 12 19
1961 0 1 0 0 1 0 0 0 1 0 0 0 0 0 1 2 1 1 1 2 2 2 0 0 0 1 3 0 1 0 0 1 0 1 0 1 6 8 9 23
1962 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 1 0 3 1 1 4 2 0 2 0 0 1 0 0 3 0 0 0 4 4 13 21
1963 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 1 1 1 2 1 0 1 0 1 2 0 0 1 0 0 0 0 2 0 2 6 8 16
1964 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 4 1 4 1 2 2 0 1 4 0 1 2 0 2 1 1 0 1 7 8 15 30
1965 1 1 0 0 1 0 0 1 0 0 0 0 0 0 2 0 1 1 1 1 4 1 0 1 0 1 2 1 0 0 0 0 1 0 0 0 4 6 11 21
1966 0 0 0 0 0 0 0 0 0 0 0 1 1 0 2 0 0 1 3 2 2 0 0 1 0 1 2 1 1 0 0 2 0 1 0 1 6 6 10 22
1967 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 1 0 1 0 2 2 2 2 1 0 0 0 0 0 2 0 0 3 0 1 0 3 7 11 21
1968 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 2 1 0 0 3 0 0 1 0 0 3 0 0 0 0 5 10 15
1969 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 1 2 0 0 2 1 1 2 0 0 1 0 1 0 0 0 1 3 3 9 15
1970 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 1 1 0 1 1 1 2 1 2 1 0 2 2 1 0 1 1 0 0 6 6 9 21
1971 1 0 0 0 0 0 0 1 0 0 2 1 1 1 1 0 0 3 1 0 3 0 1 1 0 1 2 0 4 1 1 0 1 0 0 0 4 10 13 27
1972 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 1 1 1 0 1 3 1 0 1 0 0 0 0 1 0 0 1 9 2 6 17
1973 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 1 2 1 0 1 0 0 0 3 0 1 0 0 0 0 3 4 5 12
1974 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 1 2 1 1 3 0 1 1 0 0 1 4 0 2 0 1 1 0 4 12 7 23
1975 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 1 3 0 1 2 1 0 1 1 0 0 3 2 9 14
1976 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 0 1 0 1 3 0 2 1 2 1 1 0 0 0 0 0 2 1 2 0 6 6 10 22
1977 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 3 0 2 0 1 1 2 1 1 0 1 0 1 0 0 2 5 6 8 19
1978 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 2 0 0 0 1 3 3 1 3 2 1 1 0 3 1 0 1 1 0 0 10 7 8 25
1979 0 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 0 1 0 1 2 1 0 2 0 1 2 1 1 2 0 1 1 0 1 1 3 6 13 22
1980 0 0 0 1 0 0 0 1 0 1 0 0 1 1 1 1 1 0 1 0 3 2 0 1 0 0 2 0 1 1 2 0 1 0 1 0 9 5 9 23
1981 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 2 2 3 0 1 1 2 1 0 2 0 1 1 0 1 2 0 0 2 5 7 11 23
1982 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 2 2 1 0 0 4 0 2 2 1 0 1 0 0 0 0 1 1 3 6 11 20
1983 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 2 1 1 1 2 1 4 1 0 2 2 1 2 0 3 11 9 23
1984 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 3 2 2 1 0 0 2 0 2 0 0 3 0 0 1 6 4 9 19
1985 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 1 0 1 0 1 2 1 2 1 0 1 2 0 0 0 0 0 1 2 5 10 17
1986 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 1 1 0 1 2 0 0 2 0 0 1 1 2 1 0 2 1 0 0 3 2 7 12 21
1987 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 3 0 0 3 1 0 1 0 0 2 0 1 1 0 0 1 2 1 13 16
1988 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 2 1 2 0 1 0 0 0 0 3 0 1 1 4 0 0 2 0 1 0 3 7 10 20
1989 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 3 2 1 1 0 0 0 0 2 0 1 2 0 0 2 1 0 0 5 5 9 19
1990 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 1 0 2 0 2 0 0 3 0 0 0 4 0 0 1 1 0 1 0 1 0 4 8 8 20
1991 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 0 0 1 0 1 3 1 0 1 0 0 4 0 0 2 0 2 0 0 0 1 1 5 13 19
1992 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 2 1 2 0 1 0 0 0 3 0 0 2 0 0 0 3 4 9 16
1993 0 0 0 1 0 0 0 0 0 2 0 0 1 0 0 1 0 1 2 3 0 0 3 2 1 2 3 1 1 2 0 2 0 1 0 3 10 11 11 32
1994 0 1 0 0 0 0 0 0 0 0 0 1 1 0 1 1 0 1 1 3 2 1 0 3 2 1 0 0 0 3 0 0 1 0 0 1 6 5 13 24
1995 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 2 1 0 3 1 1 1 2 0 0 0 0 2 0 2 9 5 16
1996 0 0 0 0 1 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1 2 0 2 0 1 0 3 1 0 1 1 0 1 0 0 0 3 6 8 17
1997 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 2 0 1 1 1 1 0 0 0 0 0 1 0 1 1 0 0 1 4 4 6 14
1998 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 0 1 2 0 0 2 0 1 0 0 0 1 4 2 5 11
1999 1 0 0 1 0 0 0 0 0 1 1 0 0 0 0 1 0 1 0 1 1 0 2 0 1 1 0 0 1 1 0 2 0 0 0 0 5 8 3 16
2000 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 3 0 1 0 1 1 0 2 1 0 0 3 0 1 1 1 0 0 5 5 8 18
2001 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 1 0 1 0 2 2 1 0 0 0 2 0 1 0 0 1 1 1 0 1 0 6 7 4 17
2002 0 1 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 2 1 1 3 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 2 6 13
2003 0 0 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 1 2 1 1 1 2 3 2 1 1 1 1 1 0 1 1 1 0 0 8 8 9 25
2004 0 0 0 1 0 0 0 1 0 0 0 1 0 1 1 0 1 3 0 1 0 0 1 2 1 1 2 0 0 3 2 1 1 1 0 0 5 7 13 25
2005 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 1 2 0 1 1 0 1 2 0 2 1 0 0 2 0 0 1 0 0 11 1 5 17
2006 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 1 3 0 2 1 0 0 2 1 1 1 0 0 2 0 1 1 3 6 11 20
2007 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 2 0 1 2 0 1 1 0 0 3 0 0 0 0 3 10 13
2008 0 0 0 0 0 0 0 0 0 0 1 0 0 1 3 0 0 1 1 0 2 0 2 1 0 1 3 0 0 0 3 1 0 0 0 1 4 6 11 21
2009 1 0 0 1 0 0 0 0 0 1 0 0 0 0 2 0 1 0 1 3 0 0 0 1 1 3 0 0 0 4 2 0 0 0 1 0 7 8 7 22
2010 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 2 1 0 1 1 0 0 2 0 0 0 0 0 0 1 5 5 11
2011 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 3 0 2 1 3 0 0 1 0 2 2 0 1 0 0 0 0 0 1 0 3 9 7 19
                                                                                 
TOTAL 10 9 8 8 8 3 2 10 6 9 7 14 16 21 29 17 30 50 57 55 100 45 61 92 35 58 98 24 38 98 27 34 71 20 23 41 270 354 610 1,234

TD - Tropical Depression - maximum winds from 40 to 63 kph near the center
TS - Tropical Storm - Maximum winds from 64 to 117 kph near the center
TY - Typhoon - maximum winds of 118 kph or more near the center

Source: PAGASA & www.typhoon2000.com

 

Table 4: Worst Typhoons of the Philippines
(1947 - 2011)

Name Period of Occrrence Deaths Damages
in Billion Pesos
Highest Wind Speed in KPH (Place recorded) Areas most Affected
1 URING (Thelma) 1 November 2-7, 1991 5101* 1.045 95 (Tacloban) Leyte, Negros
2 ROSING (Angela) 2 October 30-
November 4, 1995
936 10.829 260 (Virac Radar) Bicol Region, CALABARZON, NCR
3 FRANK (Fengshen) 3 June 18-23, 2008 938** 13.321 172 (Roxas) Eastern-Western Visayas, Romblon, Marinduque, CALABARZON, NCR, C. Luzon
4 NITANG (Ike) August 31-
September 4, 1984
1363*** 4.1 220 (Surigao) Surigao, Bohol, Cebu, Negros
5 REMING (Durian) 4 November 26-December 1, 2006 754**** 5.086 320 (Virac) Bicol, CALABARZON, Marinduque, Mindoro
6 RUPING (Mike) November 10-14, 1990 748 10.846 220 (Cebu) Northern Mindanao, Visayas
7 SISANG (Nina) November 23-27, 1987 979 1.119 240 (Legazpi) Bicol, Marinduque, CALABARZON
8 SENING (Joan) 5 October 11-15, 1970 768 1.89 275 (Virac) Bicol, CALABARZON, NCR
9 PEPENG (Parma) 6 September 30-October 11, 2009 492 27.195 120 (PAGASA estimate at Cagayan) Northern Luzon, Cordillera
10 LOLENG (Babs) October 15-24, 1998 303 6.787 250 (Virac) Bicol, Central-Northern Luzon
11 AMY December 6-19, 1951 991 0.7 240 (Cebu) Visayas
12 UNDANG (Agnes) November 3-6, 1984 895 1.9 230 (Tacloban) Samar, Leyte, Panay
13 TRIX October 16-23, 1952 995 0.88 215 (Legazpi) Bicol Region
14 KADIANG (Flo) September 30-October 7, 1993 576 8.752 130 (over water) Northern-Central Luzon, Cordillera
15 ONDOY (Ketsana) 7 September 24-27, 2009 464 11.121 85 (PAGASA estimate at Aurora) NCR, CALABARZON, Central Luzon
16 ILIANG (Zeb) October 7-18, 1998 75 5.375 260 (Over water) Northern Luzon
17 UNSANG (Ruby) October 21-26, 1988 157@ 5.636 215 (Virac) Bicol, Central-Northern Luzon
18 HERMING (Betty) August 7-14, 1987 200 2.066 240 (Catarman) Northern Samar, Southern Bicol
19 KADING (Rita) October 25-27, 1978 444 1.9 185 (Virac) Central Luzon
20 SALING (Dot) October 15-20, 1985 118 2.133 240 (Daet) Northern Bicol, Central Luzon
21 SENDONG (Washi) December 16-18, 2011 1257 1.382 95 (Surigao del Sur) Region X,  Region IX, Bicol Region, Region VII, VI, CARAGA

LEGEND: 
CALABARZON - Cavite, Laguna, Batangas, Rizal, Quezon.
* - Official estimates death toll up to 8,000; missing persons were presumed dead, some maybe devoured by sharks at Ormoc Bay & Camotes Sea.
** - Includes those who perished in the sinking of M/V Princess Of The Stars and various fishing fleets in the Visayan Sea.
*** - Deaths of up to 3,000 with many bodies buried under mudslides at Surigao del Norte and southern Negros Occidental.
**** - Official estimates death toll of up to 1,200; many of those unrecovered were buried under tons of lahar from Mayon Volcano.
@ - Excluded are the 100+ people killed when M/V Doña Marilyn capsized at the coast of Masbate. 

1 - Only a Tropical Storm.
2 - The typhoon unusually maintained winds of at least 240 kph for 60 hours, most of it while over land.
3 - Had a very erratic movement causing numerous forecasting errors catching millions off-guard at its path. Induced monsoon rains spawned floods in Western and Central Mindanao.
4 - The most powerful typhoon ever recorded by PAGASA, registering a 320-kph wind gust at Virac Weather Station before the anemometer was damaged. It erased the old record of   275 kph, recorded during the passage of Super Typhoon SENING (Joan) in Oct 13, 1972 at the same station.
5 - A very large super typhoon with a radius covering the whole Philippines.
6 - Criss-crossed Northern Luzon making initial landfall at Cagayan, then looping back to landfall in Ilocos Norte, looped back again and entered Cagayan the second time.
7 - Brought record flooding in Antipolo, Cainta, Marikina, Quezon City, Manila, Pasig, and much of Metro Manila drowning hundreds, stranding millions.

over water – typhoon's estimated strongest winds were recorded while typhoon was still at sea but is closely approaching land.

Note: Damages registered in billions of Philippine Peso are not adjusted to current inflation rate.
Bold font indicate new entries.

Sources: http://www.typhoon2000.ph/stormstats/WorstPhilippineTyphoons.htm.
Date accessed: December 7, 2012

http://www.ndrrmc.gov.ph/attachments/article/358/Final%20Report%20re%20TS%20Sendong,%2015%20-%2018%20December%202011.pdf

 

Table 5: Natural Disasters in the Philippines from 1983 to 2012

  Number of Events Killed Total Affected Damages
('000 US$)
Drought Drought 6 8           5,547,442                        64,453
  Average per event   1.3               924,574                        10,742
Earthquake (seismic activity) Earthquake
(ground shaking)
13 2653           2,299,570                      388,925
  Average per event   204.1               176,890                        29,917
Epidemic Unspecified 1 1                       664  - 
  Average per event   1                       664  - 
  Bacterial Infectious Diseases 5 89                   4,287  - 
  Average per event   17.8                       857  - 
  Viral Infectious Diseases 8 1101               143,790  - 
  Average per event   137.6                 17,974  - 
Flood Unspecified 18 341 3,185,273 84,651
  Average per event   18.9               176,960                           4,703
  Flash flood 32 984 5,642,675 1,004,207
  Average per event   30.8               176,334                        31,382
  General Flood 45 539 6,028,676 116,408
  Average per event   12               133,971 2,587
  Storm surge/coastal flood 10 149 125,113 2,557
  Average per event   14.9                 12,511                              256
Total Flood                 105            2,013          14,981,737                  1,207,823
Insect infestation Unspecified 1 -                       200  - 
  Average per event   -                       200  - 
Mass movement dry Landslide 2 311  -   - 
  Average per event   155.5  -   - 
Mass movement wet Avalanche 1 6 1,200  
  Average per event   6                   1,200  - 
  Landslide 25 1886 313,501 33,281
  Average per event   75.4                 12,540 1,331
  Subsidence 1 287 2,838  
  Average per event   287                   2,838  - 
Total Mass Movement (wet)   27 1,892               317,539                       33,281
Storm Unspecified 20 371 3,107,969 110,274
  Average per event   18.6 155,399 5,514
  Local storm 4 9 24,704 5
  Average per event   2.3                   6,176 1
  Tropical cyclone 162 23901 96,443,152.00 5,827,998
  Average per event   147.5 595,328                        35,975
Storm Total   186 24,281 99,575,825                  5,938,277
Volcano Volcanic eruption 16 719           1,585,713                      216,282
  Average per event   44.9                 99,107                        13,518
Wildfire Forest fire 1 2                       300  - 
  Average per event   2                       300  - 

Source: "EM-DAT: The OFDA/CRED International Disaster Database: www.em-dat.net - Université Catholique de Louvain - Brussels - Belgium"

Created on: Dec-11-2012. - Data version: v12.07

 

Table 6: Table of Natural Disasters in Philippinesfrom 2003 to 2012

  Number of Events Killed Total Affected Damages
('000 US$)
Drought Drought 1 - - -
  Average per event   - - -
Earthquake (seismic activity) Earthquake (ground shaking) 3 113 320,697 8,990
  Average per event   37.7 106,899 2,997
Epidemic Bacterial Infectious Diseases 4 85 4,073  - 
  Average per event   21.3 1,018  - 
  Viral Infectious Diseases 3 772 130,729  - 
  Average per event   257.3 43,576  - 
Flood Unspecified 2 27 15,100  - 
  Average per event   13.5 7,550  - 
  Flash flood 23 205 3,280,230 266,484
  Average per event   8.9 142,619 11,586
  General flood 34 347 5,546,199 74,535
  Average per event   10.2 163,124 2,192
  Storm surge/coastal flood 2 11 50,034 2,520
  Average per event   5.5 25,017 1,260
Total Flood   59 563          8,876,463                      343,539
Mass movement wet Avalanche 1 6 1,200  
  Average per event   6 1,200  - 
  Landslide 11 1540 238,328 9,281
  Average per event   140 21,666 844
Total Mass movement wet   12          1,546              239,528                          9,281
Storm Unspecified 2 2 35,445 73
  Average per event   1 17,723 37
  Local storm 2 7 4,604 5
  Average per event   3.5 2,302 3
  Tropical cyclone 73 7930 44,569,481 2,703,213
  Average per event   108.6 610,541 37,030
Total Storm   77          7,939        44,609,530                  2,703,291
Volcano Volcanic eruption 6 - 153,114  - 
  Average per event   - 25,519  - 

Source: "EM-DAT: The OFDA/CRED International Disaster Database www.em-dat.net - Université Catholique de Louvain - Brussels - Belgium"

Created on: Dec-11-2012. - Data version: v12.07
*Events recorded in the CRED EM-DAT. First Event: Sep/1905, Last Entry: Jun/2012.
*Epidemics include:Bacterial Infectious Diseases(Cholera), Parasitic Infectious Diseases, Viral Infectious Diseases, Viral Infectious Diseases(Influenza), Viral Infectious Diseases(Dengue/dengue haemorrhagic fever), Viral Infectious Diseases(Dengue fever), --(Acute diarrhoeal syndrome), Viral Infectious Diseases(Acute respiratory syndrome (SARS)), Bacterial Infectious Diseases(Meningococcal disease), Viral Infectious Diseases(Dengue), Bacterial Infectious Diseases(Diarrhoea )

 

Figure 1. Observed Annual Mean Surface Temperature Anomalies
from 1951 - 2010 in the Philippines

fig1

NOTE: Data from PAG-ASA compiled by Manila Observatory for paper of Thomas, Albert, and Perez (2012). Climate –Related Disasters in Asia and the Pacific. A working paper, September 2012. 

 

Figure 2. Frequency of Heavy Rainfall Events in Luzon (1960–2010)

fig2

NOTE: Data from PAG-ASA compiled by Manila Observatory for paper of Thomas, Albert, and Perez (2012). Climate –Related Disasters in Asia and the Pacific. A working paper, September 2012. 

 

Figure 3. Mean annual total tropical cyclone frequency (1948 - 2003)

fig3

Source: Anglo, E. G., 2005: “Decadal change in tropical cyclone activity in the Western Pacific” , Manila Observatory

 

 

 

Posted: 14 December 2012

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