IMERG-E satellite rainfall estimation error decomposition for early warning use in several parts of Indonesia

Abstract

An early warning can be used with rainfall input from satellite estimation to prevent and reduce losses due to flood risk. IMERG-E satellite rainfall estimation has fast time latency and can be used for this purpose. We tried to separate systematic and random components of the error of IMERG-E rainfall estimation. An additive error model used for this decomposition assumes that the linear function can fit the relationship between satellite and references measurements. The references measurements are hourly hellman rain gauges in several parts of Indonesia. The result shows that more stations have dominant systematic components in JJA than in DJF seasons. In 1-hr temporal, the random components are more dominant (>50%) in almost all study areas. Systematic components are dominant at Padang Pariaman and Jembrana stations (>50%) for all periods. Coarse spatial aggregation (0.2° and 0.3°) increased systematic components and lowered temporal (3-hr and 6-hr) decrease systematic components throughout the study area. Dominant random components in almost the entire study area show IMERG-E challenging to correct, and caution is needed when used as input for early warning in most parts of Indonesia. Bias reduction IMERG-E in Indonesia needs to be developed considering different seasons and locations.