MFO 2: Generation of New Knowledge and Technologies


In research and development. . . . . .

Important research projects aimed at strengthening the operational services of PAGASA were pursued and completed, notably the following:


Flood Hazard and Vulnerability Maps of Butuan

The output of the project will provide a better understanding and appreciation of the degree of floodings brought about by tropical cyclones and other weather-related events. The map would be useful to local government units in developing more sustainable operations for hazard mitigation and also for future reference for policy and decision-makers in the affected community.




Quezon City Integrated Flood Hazard Mapping in San Juan River Basin

The study resulted on the identification of areas prone to flooding. It also showed that areas with a high probability of periodic flooding are located at the confluence and adjacent to San Juan River and its tributaries. The major factor triggering flooding is weather related. It is caused by high intensity or long duration rainfall. The map will also serve as reference for developing strategies for flood mitigation by policy makers and planners as well as community members.




Enhancement of Climate Information and Prediction Services for Agriculture and Water Resources

The study used percentile rank in evaluating occurrences of drought and the seasonal variability of rainfall during ENSO condition. Results showed that the impacts of ENSO on rainfall vary from year to year and from season to season. It also showed that the chance of getting rainfall in the lower percentile rank ( 1st -3rd deciles) is generally increased in an El Nino episode whether it is strong, weak or moderate during the JFM, AMJ, OND season. Likewise, the chance of receiving rainfall in the upper percentile (8th – 10th decile) is increased during the a La Nina (cold) episode for the JFM, AMJ and OND season. However, during a non-ENSO episode there is no distinct rainfall pattern observed in most part of the Philippines.



Tornado Occurrences in the Philippines

The study utilized the historical event of tornado occurrences covering the period 1994 to 2003. The results show that tornadoes are short-lived (less than 1-minute) and mostly occurred late in the afternoon between 3:00PM – 5:30PM, the time of maximum convection in the tropics. It also shows that there is a very small correlation between the presence of tropical cyclone and tornado occurrences. Lastly, among the three (3) big island in the country, Mindanao is most frequented by tornadoes (70.3%) followed by Visayas (17.2%) and Luzon (12.5%).



Synoptic-Statistical Method of Rainfall forecasting During Southwest Monsoon at Science Garden

The study was focused on forecasting rainfall through statistical analysis of parameters like the presence or absence of tropical cyclones. Two stations were used in the study: Science Garden and Laoag stations. Laoag was chosen because of its nearness to the activity of Southwest (SW) monsoon season. Results show a forecast efficiency of 56% for a five-year independent forecast data set.




Enhancement and Strengthening of Marine Forecasting and Warning Services in the Philippines

The main achievements of the project were upgrading of equipment at the marine forecasting and laboratory and support offices; training of port meteorological officers; and conduct of seminars and workshops for coastal radio operators, ship owners and seafares. These allowed a better understanding of marine weather observation/transmission works and forecasting/warning interpretations. In line with the broader interest in the region, new and high technologies for ocean forecasting were introduced, modified and tailored for home application such as storm surge and wave models.



Subjective Analysis of Tropical Cyclone Originating from the South China Sea

In this research, a 22-year period (1979-2000) of tropical cyclone data set was studied. Out of 428 tropical cyclones in the PAR, only 22 originated from the South China Sea. The South China Sea was subdivided into areas in terms of the point of origin, intensity and month of occurrence of tropical cyclones. The different characteristics, like “looping”, of the tropical cyclones and the weather systems affecting their movement were investigated. Majority of the tracks of the tropical cyclone did not show any unusual characteristics, except for one that entered and exited out of the PAR in a “looping” motion. The damages that these tropical cyclones brought in the eastern part of the country were further induced or aggravated by the Southwest monsoon and El Niño events.




Storm Rainfall Simulation Using Radar

Series of experiments were conducted to demonstrate the effect of moving storm rainfall over a catchment such as the Angat basin. Parameters of the Neyman-Scott stochastic, space-time rainfall model are derived using the radar data of a storm event and from observed data. Selected parameters were optimized by the application of the Newton-Raphson iterative Non-Linear Least Squares and the Fletcher-Reeves Conjugate Gradient methods. Rainfall fields were generated with specified storm origin/directions and speed. There were significant variations in the rainfall patterns at a given speed and different directions. The outputs were presented in maps, graphs and tables to aid in the analyses and evaluations.




Verification of Nomogram Rainfall Forecasting Technique (NRCP PL-31)

In Metro Manila the nomograms/maps x-y-z were used to verify that there is a strong relationship between the forecasts and the observed rainfall. The study showed that as the number of month increases, the more the forecasts is related to the observed rainfall. Between the two nomograms with forecasts rainfall, the average and standard deviation of the forecast difference of the K-Index stability has less rainfall value than the Total-totals stability.



Development of GIS-based Statistical Rainfall Data and Information System for the Philippines and Updating of Climate Classification

Advances in technology have made possible the design, development and implementation of a GIS-based Climate Database Management System at PAGASA which has been facilitating the enhanced PAGASA Climate Information System. To support and sustain the enhanced capabilities at PAGASA, three main R&D activities had been implemented. A GIS-based statistical rainfall data and information system was developed to generate updated rainfall statistics. These were plotted and analyzed with the use of the GIS-based rain model. From these isohyetal (rainfall) maps, three important outputs were estimated, namely: i) the rainfall statistics for every municipality, province and administrative region in the country; ii) maximal daily rainfall for return periods of 2, 5, 10, 25, 50 and 100 years, respectively: and iii) probability levels of monthly and decadal rainfall values in 49 selected stations. The Modified Coronas climate classification was also updated. These data and information could then be used as forecasting and decision tools, and inputs for planning and for various other applications.

Trends of extreme daily temperatures and rainfall were assessed. Results of the assessment indicate that there are increasing trends of both hot days and warm nights, with the latter having a stronger rate. On the other hand, number of cool days and of cold nights have decreased. These trends have spatial coherence with most countries in the Asia Pacific region (Manton et al, 2001; Griffiths et al, 2002; Salinger et al, 2001). Extreme climate events are increasingly being seen to impact adversely on humans, ecosystems and national economies in the region. A knowledge of trends of these events would therefore be a tool for disaster preparedness and planning.

Longer high-quality records are essential for better understanding of climate variability and projected impacts. Through understanding the past, the future could be predicted with less uncertainty so that a data rescue was also attempted.




Vegetation and Soil Moisture Mapping Using MERIS, ASAR and MWR Data from ENVISAT

The results of the study showed that the ASAR images are capable of distinguishing the various stages of rice growth. The brightness values ranged from very low values farm land preparation/transplanting and increases up to the maturity stage. MERIS data was not very useful in monitoring rice growing areas due to coarse resolution and small sizes of rice fields at various stages of growth. The output would be very useful to decision makers as well as planners in the agricultural and water resources sectors.