*Jason Pajimola Punay1, Menard Godden Bataller Boneo1, Dore Solet Relleve Enriquez1, Paul Ian Daen Manalo1, Janine Magayanes Montero1
(1.Bicol University)
Keywords:Diurnal variation, Seasonal variation, rainfall, Philippines
Previous studies on diurnal rainfall pattern focused on specific regions only; however, the entirety of the Philippines as an area of interest still needs to be accomplished. This study investigates the seasonal diurnal rainfall patterns in the Philippines across its four climate types (CTs), as classified by the Modified Corona Climate Classifications. The research covered a period of 11 years, classified days into TC (Tropical Cyclone) and Non-TC days, and utilized precipitation data from the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement. The results revealed that the general mean rainfall rate (MRR) is maximum in the afternoon (CT1, CT3, and CT4 at 1600 LST; CT2 at 1300 LST). All seasons resemble the general MRR diurnal pattern, regardless of CT, with December-January-February (DJF) season having the lowest peak. The spatiotemporal distributions of rainfall further reveal the important role of prevailing winds in enhancing the rainfall over the eastern and western coast of the Philippines during DJF and June-July-August, respectively. During transition seasons (March-April-May and September-October-November), higher MRR is located over mountainous regions suggesting a more active role of local process in rainfall formation. The spatiotemporal distribution of negative vertical integrated moisture flux convergence is similar to the distribution of MRR suggesting the influence of humidity and wind to the diurnal pattern. Moreover, convective available potential energy, solar insolation, and topography are some additional factors that may be attributed to the diurnal signal. Non-TC days show varied magnitude of rainfall rate and a more pronounced diurnal signal than TC days. Results from this study may be used by the Filipino community and sectors that are heavily dependent on precipitation occurrences such as disaster management and agriculture.