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Evaluation and projection of extreme precipitation using CMIP6 model simulations in the Yellow River Basin

Authors :
Heng Xiao
Yue Zhuo
Peng Jiang
Yan Zhao
Kaiwen Pang
Xiuyu Zhang
Source :
Journal of Water and Climate Change, Vol 15, Iss 5, Pp 2326-2347 (2024)
Publication Year :
2024
Publisher :
IWA Publishing, 2024.

Abstract

The capabilities of 23 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 were evaluated for six extreme precipitation indices from 1961 to 2010 using interannual variability and Taylor skill scores in the Yellow River Basin and its eight subregions. The temporal variations and spatial distributions of extreme precipitation indices were projected from 2021 to 2050 under the shared socioeconomic pathway scenarios (SSP2–4.5 and SSP5–8.5). The results show that most GCMs perform well in simulating extreme values (1-day maximum precipitation (RX1day) and 5-day maximum precipitation (RX5day)), duration (consecutive dry days), and intensity index (simple daily intensity index (SDII)), and perform poor in simulating the threshold indices (precipitation on very wet days (R95p) and number of heavy precipitation days (R10mm)). The projected changes in extreme precipitation indicate that under the SSP2-4.5 scenario, future extreme precipitation will increase by 15.7% (RX1day), 15.8% (RX5day), 30.3% (R95p), 1d (R10mm), and 6.6% (SDII), respectively, decrease by 2.1d (CDD). The aforementioned changes are further enhanced under the SSP5-8.5 scenario. Extreme precipitation changes widely in Hekou Town to Longmen, in the northeastern part of the region from Longmen to Sanmenxia, below Huayuankou, and in the interflow basin. HIGHLIGHTS The study evaluated the biases of 23 global climate models (GCMs) from observations and the spatial distribution of the biases.; Interannual variability score, Taylor diagram, and Taylor skill score were used to evaluate CMIP6 GCMs.; The future changes of the Yellow River Basin and its subregions extreme precipitation under SSP2-4.5 and SSP5-8.5 scenarios were projected by using six ETCCDI indices.;

Details

Language :
English
ISSN :
20402244 and 24089354
Volume :
15
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Journal of Water and Climate Change
Publication Type :
Academic Journal
Accession number :
edsdoj.95b6cc65049bda4bfff1ff96c55df
Document Type :
article
Full Text :
https://doi.org/10.2166/wcc.2024.696