Statistics of the Performance of Gridded Precipitation Datasets in Indonesia. (9th May 2022)

• Record Type: Journal Article
• Authors: Wati, Trinah; Hadi, Tri W.; Sopaheluwakan, Ardhasena; Hutasoit, Lambok M.
• Other Names: Coscarelli Roberto Academic Editor.
• Is Part Of: Advances in meteorology. Volume 2022(2022)
• Publication Date: 2022-05-09
• Subjects: Meteorology -- Periodicals; Meteorology; Periodicals; 551.505
• DOI: 10.1155/2022/7995761
• Languages: English
• ISSNs: 1687-9309

Abstract

Abstract : Gridded precipitation datasets have been used as alternatives to rain gauge observations, but their applicability for a specific region should be thoroughly evaluated. This article aims at finding the most appropriate one for climatological and hydrological applications in Indonesia, by evaluating the statistics of the performance of eight different datasets (research products) having horizontal resolutions between 0.1 and 0.25 and with a time span of data availability from 2003 to 2015. The datasets are compared against the observed daily rainfall at 133 stations using 13 statistical metrics that can be classified into three groups with different characteristics of measurements, namely distribution, time sequence, and extreme value representations. By applying summation of rank (SR), it is found that MSWEP and TMPA 3B42 are the top two datasets that outperformed based on distribution and time sequence performance metric groups. The extreme performances for all datasets are still good in 75 th percentiles; however, the performances decrease at more than 75th percentiles indicating still a poorly representation of daily extreme rainfall for all gridded datasets. Results of this study suggest that MSWEP (v2) is presently the best gridded precipitation datasets available for climatological and hydrological applications in Indonesia.