Assessing the monthly performance of daily precipitation products over Southeast Asia using the gauge-based analysis.

Abstract

Accurate precipitation data is essential for understanding land surface processes and the hydrological cycle, particularly in Southeast Asia (SEA), where precipitation patterns are influenced by complex climatic interactions. This study evaluates the monthly performance of five widely-used daily precipitation products-CPC, CHIRPS, IMERG, ERA5, and PERSIANN-against the benchmark SAOBS dataset over SEA from January 2001 to December 2017. By aggregating daily data into monthly values, we identify the strengths and weaknesses of each product in capturing the spatial and temporal characteristics of precipitation in the tropical region. The evaluation includes analyses of data population, spatial distribution, and temporal variability at a monthly scale. Our findings reveal significant spatial heterogeneity in the performance of these products, emphasizing the importance of scale-specific assessments before their application in regional studies and management practices. Results indicate that the CPC product generally provides the most accurate monthly estimates, with the highest correlation coefficients and lowest root-mean-square errors. However, all products exhibit systematic biases, such as overestimation in high-rainfall regions and seasonal discrepancies. These findings underscore the need for regional calibration to improve the applicability of precipitation products for monthly-scale climate studies and resource management in SEA.