气候变化领域集成服务门户(CCPortal): Optimal reliability ensemble averaging approach for robust climate projections over China

CCPortal

DOI	10.1002/joc.8485
	Optimal reliability ensemble averaging approach for robust climate projections over China
	Gao, Yiyan; Yu, Zhongbo; Zhou, Minpei; Ju, Qin; Wen, Lei; Huang, Tangkai
发表日期	2024
ISSN	0899-8418
EISSN	1097-0088
英文摘要	Accurate simulation and reliable projection of temperature and precipitation over China under climate change is important for proposing adaptation measures for future natural ecosystems. This study proposes a novel method to construct an optimal reliability ensemble averaging (REA) subset from the Coupled Model Intercomparison Project Phase 6 (CMIP6) based on their historical performance in simulating temperature and precipitation across different subregions. The optimal REA ensemble outperforms the multi-model ensemble mean (MMEM) and single optimal model in reproducing the spatial patterns of historical annual mean temperature and precipitation over China from 1985 to 2014. Under the examined Shared Socioeconomic Pathway scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5), the REA projects persistent warming and increased precipitation towards the end of the 21st century, intensifying under higher emissions. Nationwide mean temperature rises of 1.39, 2.69 and 5.05 degrees C, and precipitation increases of 9%, 10% and 20% are projected in the long-term (2081-2100) relative to 1995-2014 under SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios, respectively. Northwestern China and the Tibetan Plateau are expected to experience amplified warming and precipitation increases, respectively. Compared to the MMEM, the REA generally indicates reduced warming but larger precipitation increases, especially over the Tibetan Plateau under higher-emissions scenarios. The REA exhibits lower projection uncertainty than the MMEM for both temperature and precipitation, primarily attributed to reduced internal variability. The novel optimal framework for REA shows the potential for extracting robust regional climate information applicable to different subregions of China. This study may contribute to new comprehension of future climate change over China. This study proposes a novel method to construct an optimal reliability ensemble averaging (REA) subset from the Coupled Model Intercomparison Project Phase 6 (CMIP6) based on their historical performance in simulating temperature and precipitation across different subregions. image
英文关键词	China; CMIP6 model selection; multi-model ensemble; reliability ensemble averaging; spatial variability; uncertainty
语种	英语
WOS研究方向	Meteorology & Atmospheric Sciences
WOS类目	Meteorology & Atmospheric Sciences
WOS记录号	WOS:001220111400001
来源期刊	INTERNATIONAL JOURNAL OF CLIMATOLOGY
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/290838
作者单位	Hohai University; China Meteorological Administration
推荐引用方式 GB/T 7714	Gao, Yiyan,Yu, Zhongbo,Zhou, Minpei,et al. Optimal reliability ensemble averaging approach for robust climate projections over China[J],2024.
APA	Gao, Yiyan,Yu, Zhongbo,Zhou, Minpei,Ju, Qin,Wen, Lei,&Huang, Tangkai.(2024).Optimal reliability ensemble averaging approach for robust climate projections over China.INTERNATIONAL JOURNAL OF CLIMATOLOGY.
MLA	Gao, Yiyan,et al."Optimal reliability ensemble averaging approach for robust climate projections over China".INTERNATIONAL JOURNAL OF CLIMATOLOGY (2024).