Validation of high-resolution gridded rainfall datasets for climate applications in the Philippines

Abstract

Gridded rainfall products could augment the shortage of available rainfall data in archipelagic countries like the Philippines, where weather stations are still sparsely distributed especially over its remote and less-developed islands. However, these products need to be validated first using ground measurements to determine their ability to represent properties of local rainfall. This study compares four high-resolution, gridded datasets—APHRODITEv1101, CHIRPSv2, TRMM 3B42v7, and PERSIANN-CDR—with respect to 49 synoptic weather stations over the Philippines from 1998 to 2005. The performance of these datasets was assessed in terms of bias, distribution, and different statistical error metrics and skill scores across time scales and climate types. Results show that all the datasets were able to capture the basic climatology and to varying extents, spatial patterns of Philippine rainfall. TRMM 3B42v7 has the least overall average monthly bias and most closely resembles the rainfall distribution observed at weather stations, especially dry days and torrential rain days for the whole Philippines. APHRODITEv1101 performs best in terms of error metrics and skill scores but displays consistent underestimates. CHIRPSv2, on the other hand, best captures the seasonal rainfall peaks in the different climate types in the Philippines but is prone to larger errors. Last, PERSIANN-CDR shows generally poor metrics and rainfall distributions, in comparison to the other datasets. These key findings are used to identify possible research applications in the Philippines that are best suited for each dataset.