Statistical assessment of uncertainty and performance of multiple satellite-based precipitation products in capturing extreme precipitation events across Punjab Province, Pakistan

Abstract

ABSTRACT The changing climate poses a significant danger to both environment and humans. Precipitation stands out as a critical factor for impacting hydrology, ecology, agriculture, and vegetation as well as crucial for maintaining the atmospheric equilibrium. This research examined four satellite-based precipitation products spanning from 2010 to 2018, focusing on assessing the uncertainty associated with these products in Punjab Province, Pakistan. Additionally, a comparative analysis of multi-satellite-derived precipitation data was conducted for the region. Various evaluation metrics, including CC, RMSE, Bias, rBias, and POD, were employed to gauge the performance of these datasets throughout the study area. Our research yielded the following findings: (1) datasets CHIRP and SM2RAIN exhibited the capability of capturing temporal changes observed in precipitation throughout the study area. (2) All satellite-derived datasets displayed superior performance on a monthly basis compared to daily timeframes. (3) On a seasonal scale, CHIRP and SM2RAIN exhibited superior precipitation detection capabilities compared to PERSIANN-CCS and PERSIANN-CDR. (4) CHIRP and SM2RAIN exhibited superior performance across all seasons when compared to PERSIANN-CCS and PERSIANN-CDR. Nonetheless, all products exhibited reasonably accurate detection of light to moderate precipitation events. This study serves to establish a foundation for effective monitoring, mitigation, and decision-making processes.