A Statistical Approach for Comparison of Secondary Precipitation Products

Meteorological data retrieval is the fundamental process for any hydrological research. Precipitation data collection from some constrained territories like high slant geography and inaccessible areas is exceptionally troublesome. Setting the rain gauges is a matter of expense and timely maintenance. To overcome these issues, satellite sensors producing high spatial and temporal resolution datasets can be utilized in the studies involving precipitation component. These satellite products are affected by biases, and hence, there is a need for calibration and verification by using ground observation data based on the statistical coefficients. In this study, the most accessible satellite data products, i.e., CHIRPS, PERSIANN-CDR and TRMM, are employed to check the accuracies against IMD gridded data for the years 2000–2012 using a statistical approach. Selecting the data product having a high coefficient of correlation and low PBIAS is utmost necessary. The current study was performed based on catchment-to-catchment (C-C) method by comparing IMD gridded data with satellite datasets obtained from Google Earth Engine. The results can highlight the data product which can conquer the issue of data inaccessibility in the investigation territory and can be utilized as reference precipitation dataset for different hydrological applications.