Evaluation of multiple gridded precipitation datasets using gauge observations over Indonesia during the Asian-Australian monsoon period

Abstract

Gridded precipitation datasets are widely available from satellite observations and reanalysis model outputs. However, its performance in specific regions in the world may vary and depends on several factors, such as grid data spatial resolution, rainfall estimation algorithms, geographical location, elevation and regional climate conditions. This study aims to report on 13 gridded precipitation datasets' performance over Indonesia through direct comparisons with rain gauge measurements at various time scales over a 12-year period (2001-2012). The results show that, at daily timescales, the MERRA2 and CPC outperformed other datasets but tended to underestimate the rain gauge data in Indonesia, followed by GPCC. However, MERRA2 has smaller variation and bias than CPC. On monthly and annually timescales, CPC was found to be the best-performing dataset, followed by MERRA2, GPM-IMERG, GPCC and TRMM (TMPA), while JRA55 registered the worst performance at all timescales, followed by ERA-Interim. The performance of all datasets was better during JJA and SON than during DJF and MAM. The best performances were found in the southern (S) region of Indonesia, while the worst were in the northeast (NE) region for all months and datasets. The best performances during DJF (Asian Winter Monsoon) and JJA/SON (Australian Winter Monsoon) were found in the northwest (NW) and southern (S) regions, respectively. Most datasets overestimate the rain gauge data over Indonesia, except for GSMaP, MERRA2, CPC and CMORPH.