Assessment of NEX-GDDP-CMIP6 Downscale Data in Simulating Extreme Precipitation over the Huai River Basin

Author:

Jiang Fushuang1,Wen Shanshan1ORCID,Gao Miaoni2,Zhu Aiping1

Affiliation:

1. School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China

2. Institute for Disaster Risk Management, Nanjing University of Information Science & Technology, Nanjing 210044, China

Abstract

This study aimed to assess the performance of 35 global climate models included in NEX-GDDP-CMIP6, derived from downscaling CMIP6 data to high spatial (25 km) and temporal (daily) resolutions, in reproducing extreme precipitation events over the Huai River Basin. Eight widely used extreme precipitation indices were employed to quantitatively describe the models’ capability of simulation. Results indicate that the majority of models can reasonably capture trends, with UKESM1-0-LL performing the best among all considered models. All models demonstrate high accuracy in simulating climatological means, especially for the total precipitation (PRCPTOT), displaying a spatial correlation coefficient exceeding 0.8 when compared to the observed data. NorESM2-MM and MRI-ESM2-0 can accurately simulate the frequency and intensity of extreme precipitation, respectively. In general, UKESM1-0-LL, CESM2, MIROC6, MRI-ESM2-0, CMCC-CM2-SR5, and MPI-ESM-2-LR exhibit superior simulation capabilities in terms of capturing both the trends and climatology of extreme precipitation. The aforementioned findings provide guidance for future studies on the regional impacts of climate change using NEX model data, and therefore hold great importance in comprehending the regional impacts of, and the adaptability to, climate change, as well as the development of adaptation strategies.

Funder

The National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Atmospheric Science,Environmental Science (miscellaneous)

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