The Regionalization of Indonesian Maritime Continent Rainfall based on Integrated Multi-satellite Retrievals for GPM (IMERG)

Abstract

Abstract The need for adequate rainfall data in all regions of Indonesia cannot be achieved only by relying on ground observation tools. This work aims to evaluate the application of spatial satellite rainfall data in characterizing rainfall associated with climatic condition over Indonesia. This study applied an Integrated Multi-satellite Retrievals for GPM (IMERG) data using a double correlation method (DCM). The analysis was carried out in the period April 2014 to March 2019. Before regionalization, IMERG V06 data were validated using observed rainfall data from the Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia (BMKG). The results showed that 96% of 154 total validation locations have a high correlation score between IMERG and rain gauges (r = 0.5 – 0.97). IMERG was also able to identify monthly and annual rainfall patterns in Indonesia. Based on DCM, we obtained four rainfall regions in Indonesia. Region A has the monsoonal characteristic, covers central and south Indonesia from south Sumatra to Nusa Tenggara, south parts of Kalimantan, some areas of Sulawesi, and parts of Papua. Region B has an equatorial pattern (semi-monsoonal), located in the equatorial area of Indonesia and covers the west and east part of Sumatra and the north-central part of Kalimantan. Region C, with an anti-monsoonal pattern, covers Maluku, western-central Papua, and parts of Sulawesi. Region D is influenced by monsoon and cold surge characteristics, located in the north part of Sumatera and a small portion of northern Kalimantan to the South China Sea region. Besides the new region D, this research also showed five other differences between IMERG-based map and gridded rain gauges’ data-based map (2003). The regionalization results based on IMERG reveal that there is a possibility of updating areas with certain rainfall characters in Indonesia related to resolution, density, and updates data sources.