Evaluation of precipitation extremes over the Tibetan plateau using the NASA global daily downscaled datasets NEX-GDDP-CMIP6

Abstract

The utility of statistically downscaled data is in its provision of detailed, high-resolution insights, surpassing global models, which is essential for precise assessments of climate impact. This study delves into the changes in extreme precipitation across the Tibetan Plateau (TP) and its five subregions, thereby deepening our understanding of climate impacts in the region. Employing NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP-CMIP6), which are bias-corrected and statistically downscaled, in conjunction with three gauge-based datasets (CN05.1, CMFD, GMFD) spanning from 1979 to 2014, this study conducts an extensive analysis using eight extreme precipitation indices in the TP. The findings reveal significant spatial disparities in extreme precipitation, with the southern subregion experiencing a significant increase while the two northern subregions show statistically insignificant changes. NEX-GDDP-CMIP6 performs best in the eastern subregion but fails to capture extreme precipitation characteristics in the southern and western subregions. Averaging over the whole period of 1979–2014 (climatology), the NEX-GDDP-CMIP6 dataset performs better on the intensity and persistence indices than on the absolute and relative threshold indices. NEX-GDDP-CMIP6's performance on climate trends is significantly below that of climatology. The NEX-GDDP-CMIP6 dataset has limitations over the TP because of its reliance on the underperforming GMFD reference data. This study provides a comprehensive understanding of the variability of extreme precipitation and disparities among different subregions of the TP, laying a robust scientific groundwork for climate impact studies and future projection in this region.