Kurniawan Raharjo

Magister of Physics, MIPA Faculty, University of Jember, Jl. Kalimantan No. 37 Jember, Indonesia
SAMS Sepinggan Meteorological Station, Indonesian Agency for Meteorological, Climatological and Geophysics., Marsma R. Iswahyudi Street No. 365 Sepinggan Balikpapan, East Kalimantan, Indonesia

Bowo Eko Cahyono

Physics Department, MIPA Faculty, University of Jember, Jl. Kalimantan No. 37 Jember, Indonesia

Artoto Arkundato

Physics Department, MIPA Faculty, University of Jember, Jl. Kalimantan No. 37 Jember, Indonesia

Agus Suprianto

Physics Department, MIPA Faculty, University of Jember, Jl. Kalimantan No. 37 Jember, Indonesia

Huda A. Mukhsinin

SAMS Sepinggan Meteorological Station, Indonesian Agency for Meteorological, Climatological and Geophysics., Marsma R. Iswahyudi Street No. 365 Sepinggan Balikpapan, East Kalimantan, Indonesia

DOI: https://doi.org/10.19184/jid.v27i1.60001

ABSTRACT 

Precise precipitation records are essential in supporting climate monitoring and extreme weather early warning systems in coastal regions such as Balikpapan. Driven by the need to provide more accurate and representative rainfall information, the primary objective of this research is to assess the efficacy of three Satellite Precipitation Products (SPPs), namely Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Integrated Multi-satellite Retrievals for GPM—Global Precipitation Measurement (IMERG), and Global Satellite Mapping of Precipitation (GSMaP), against ground-based observations (Surface Synoptic Observations (SYNOP)) data in Balikpapan spanning from January 2020 through December 2024. The evaluation was conducted at three temporal scales from monthly, ten-days and daily which were selected to represent rainfall variability from short-term to long-term scales. The results showed that at the monthly scale, GSMaP exhibits the highest accuracy, with a correlation coefficient (R) of 0.96, a Nash–Sutcliffe Efficiency (NSE) value of 0.92, and the lowest error levels (Root Mean Square Error (RMSE) = 34.36, (Mean Absolute Error (MAE) = 22.50). At the 10-days scale, GSMaP demonstrate strong performance by R = 0.94 and NSE = 0.88. Dichotomous at both temporal scales confirms the dominance of GSMaP in detecting rainfall events, as indicated by high Critical Success Index (CSI), Accuracy, and Heidke Skill Score (HSS) values, along with minimal False Alarm Ratio (FAR). In contrast, IMERG tends to overestimate rainfall with a Pbias of +10.5%, while CHIRPS shows the lowest accuracy and generally underestimates rainfall. At the daily scale across different seasons (December-January-February(DJF), March – April – May (MAM), June–July–August (JJA), and September–October–November (SON)), GSMaP consistently outperforms the other SPPs, exhibiting an R-value interval between 0.79 and 0.82. The findings of this study demonstrate that GSMaP is the most credible satellite rainfall dataset for real-time weather monitoring in Balikpapan across all evaluated timeframes.

Keywords: Balikpapan, CHIRPS, GSMaP, IMERG, Precipitation, Satellite.