Validation of Satellite-Derived and Reanalysis Solar Irradiance Databases Across Indonesia’s Tropical Climate Zones

Accurate solar irradiance data are essential for photovoltaic (PV) resource assessment in Indonesia, yet no hourly-resolution multi-database validation exists across the archipelago scale. This study evaluates four gridded solar irradiance databases, CAMS, JAXA Himawari-9, NASA POWER, and ERA5, against quality-controlled ground measurements from 26 BMKG stations spanning all three major Köppen climate zones (Af, Am, Aw) during 2023–2024. CAMS achieved the highest hourly correspondence (median R2 = 0.855, rRMSE = 28.1%), and JAXA was close behind (R2 = 0.848), while NASA POWER showed the lowest systematic bias (rMBE = +3.6%). ERA5 showed the largest hourly errors (R2 = 0.617, rRMSE = 41.2%) consistent with its model-generated cloud fields that are unable to reproduce the localized convective-cloud variability. Because CAMS and JAXA infer cloud from the same Himawari-9 AHI observations on a common 0.05° grid, their comparison reduced sensor and resolution-related differences and focused on the retrieval design. Both showed closely comparable performance (clear-sky R2 = 0.925 vs. 0.913), and this gap widens as cloud frequency increases across the three climate zones. All four databases showed substantially larger relative errors under overcast conditions (Kt < 0.35); the temporal aggregation reduced relative error substantially, with CAMS showing the lowest error at hourly and daily scales and NASA POWER the lowest monthly rRMSE. These results provide an archipelago-scale hourly-resolution validation of four structurally distinct databases across Indonesia’s three tropical climate zones, supporting product selection and bias-correction strategies for solar resource application in Indonesia.