A Comparison and Ranking Study of Monthly Average Rainfall Datasets with IMD Gridded Data in India

Precise rainfall measurement is essential for achieving reliable results in hydrologic applications. The technological advancement has brought numerous datasets that can be available to assess patterns. However, the suitability of a given dataset specific location remains an open question. objective this study find which perform well India at various spatial resolutions: pixel level, meteorological sub-divisions (MSDs) and as whole temporal monthly yearly. This performs skill metrics analysis on seven widely used datasets—GPM, CRU, CHIRPS, GLDAS, PERSIANN-CDR, SM2RAIN, TerraClimate—using Indian Meteorological Department’s (IMD) gridded data reference. rule-based decision tree techniques are employed obtained values good-performing each value among all used. MSD pixel-wise analyses reveal GPM well, while TerraClimate performed most poorly almost MSDs. suggests satellite-derived, gauged, merged datasets, merged-type with approximately 17 MSDs demonstrating same. (in both month- year-wise scales) also dataset. optimal selected datasets. typically ranks fit, followed by CHIRPS then PERSIANN-CDR. Despite its finer resolution, lowest level. research will aid selecting pixels obtain agricultural applications, contribute sustainable development.