Jori J. Loiz
The variations of tropical cyclone activity in the Northwest Pacific, particularly in the Philippine Area of Responsibility (PAR), are greatly influenced by an atmospheric and oceanographic phenomenon called El Niño-Southern Oscillation (ENSO), which occurs every 2 to 9 years. This phenomenon affects the Philippine economy since it is mainly agriculturally-based. Agriculture is dependent on rainfall which is contributed largely by tropical cyclones that enter or originate in the PAR.
This study is an attempt to determine the effects of El Niño, particularly the 1997/1998 event, on the tropical cyclone activity in the PAR. NCEP/NCAR reanalyzed charts of mid-tropospheric humidity, upper-level divergence, outgoing longwave radiation (OLR) anomaly, sea surface temperature (SST) anomaly and wind vectors in 850- and 200-hpa are used in the study. These parameters are mentioned by Gray (1977) as essential factors in tropical cyclone formation.
Reduction of tropical cyclone formation and activity is observed at the height of the occurrence of ENSO. Also, the opposite is observed when the cold episode, which is called La Niña, starts to affect the region.
Vicente B. Malano
A numerical/spectral wave model for the prediction of waves over shallow water has been developed. It is based on the balance equation of energy spectrum in spherical coordinate system applied over a rectangular basin. The effects of varying the grid spacing, bathymetry as well as the wave frequency are examined by neglecting the source and sink functions. The wave heights generated by the different wind intensities and directions are likewise investigated in this study. Results of the different experimentations show that the wave heights generated are found reasonable. The waves are well distributed. Predicted Significant Wave Heights Over Manila Bay are sufficiently realistic.
Francis A. Araniador
This study aims to use the National Center for Atmospheric Research (NCAR) 5th Generation Mesoscale Model (MM5) in the prediction of rainfall associated with tropical cyclones in the Philippines, using a reasonably powerful SGI Origin 2000 supercomputer. The models extracted 24-hr accumulated rainfall forecast data are compared with the observed 24-hr accumulated rainfall recorded from the synoptic stations. MM5 product in graphical form is also compared with satellite pictures of the cloud field. Using contingency tables, the individual scores such as skill score, threat score, bias, Probability of Detection (POD), the number hits are computed in categorical classes. The preliminary evaluation showed that the threat Score (TS) for No Rainfall category ranges from 0.12-0.6, 0.12-0.6 for Light Rainfall category and 0.13-0.35 for Moderate category which is an indication of better forecast compared to the work of Junker, NW et al. (1995) whose threat score values range from 0.07-0.14. There was a high Threat Score and probability of Detection for rainfall occurrence category compare with Non-rainfall Occurrence category. An average skill score of 0.11 using 2x2 contingency table was high enough compared with an average skill score of 0.07 for a 16 category frequency distribution contingency table. Using all the cases involved the overall skill score is 0.18. Rainfall occurrence for Non-tropical cyclone related events has a high probability of detection, threat score, bias and skill score compared with the rainfall occurrence for tropical cyclone related events. The difference between predicted and observed rainfall was analyzed and resulted into a more negative rainfall value in most cases with an indication of under prediction while positive RR values for the rest of the cases. In general, the model has the ability to forecast rainfall associated with tropical cyclone in categorical classes so that there is better Skill Score for light RR category compared with other categories.
Salvador S. Olinares
An assessment of mitigation program activities for natural disasters of PAGASA-DOST in the Cordillera Administrative Region for the year 2001.
Herman L. Ngohayon
Remotely sensed data and observations were obtained from the low-altitude satellites and from the readily available high-altitude geostationary satellites. The capabilities of the Tropical Rain Measuring Mission-Microwave Imager (TRMM-TMI) and the Defense Meteorological Satellite Program-Special Sensor Microwave Imager (DMSP-SSMI) were assessed. Imageries generated by these sensors were utilized. Reliability of these imageries are of paramount importance to data-sparse Northwestern Pacific Ocean, Philippine Sea and the South China Sea where most of the tropical cyclones that caused enormous damages and casualties to the Philippines have originated. The imageries were mostly taken from the Naval Research Laboratory, Monterey through their website via Internet. Brightness temperature values were obtained from the composited satellite imageries of intense tropical cyclones that had entered the Philippine Area from 1998 to 2001. The brightness temperature corresponds to cold cloud tops where deep and intense convection was observed. Similarly, these imageries easily depicted the tropical cyclone eye or center and delineated the location of the eyewall and the spiral cloud bands that correspond to the location of strong winds experienced at the Earth's surface. Likewise, the sea surface temperature observed at the surface, elevation and latitude-longitude was taken and labeled as synoptic predictors. Excellent results were obtained when remotely sensed data and synoptic observations were correlated with the maximum winds (VMAX) and the minimum sea level pressure (MSLP). It revealed high potentials of the low altitude polar orbiting satellites. When utilizing a single independent variable that is from the TMI 85H Tbano (0-2), the root mean square error (RMSE) was 13.21 kph. By employing a number of related predictors with the multiple linear regression analysis, the RMSE was pegged at 12.14 kms. a reduction of 8.8%. When test measures were applied, the TMI 85H Tb ano(0-2) emerged to be more superior from among the other satellite sensors. Finally, when combining remotely sensed (satellite) data and synoptic observations results were found to be comparable and even better. The coefficients, error characteristics and tests performances when applied to MSLP as a measure of TC intensity has a RMSE of 6.13 hPa better than 8.34 hPa which was obtained by Velden in his 1997 study.