干旱区生态环境知识资源中心(Arid): Evaluating CMIP6 Historical Mean Precipitation over Africa and the Arabian Peninsula against Satellite-Based Observation

Arid

DOI	10.3390/atmos14030607
	Evaluating CMIP6 Historical Mean Precipitation over Africa and the Arabian Peninsula against Satellite-Based Observation
	Nooni, Isaac Kwesi; Ogou, Faustin Katchele; Chaibou, Abdoul Aziz Saidou; Nakoty, Francis Mawuli; Gnitou, Gnim Tchalim; Lu, Jiao
通讯作者	Lu, J
来源期刊	ATMOSPHERE
EISSN	2073-4433
出版年	2023
卷号	14 期号:3
英文摘要	This study evaluated the historical precipitation simulations of 49 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) in reproducing annual and seasonal precipitation climatology, linear trends, and their spatial correlation with global SST across Africa and the Arabian Peninsula during the period of 1980-2014, using Global Precipitation Climatology Centre (GPCP) data as a reference. Taylor's diagram was used to quantify the strengths and weaknesses of the models in simulating precipitation. The CMIP6 multi-mean ensemble (MME) and the majority of the GCMs replicated the dominant features of the spatial and temporal variations reasonably well. The CMIP6 MME outperformed the majority of the individual models. The spatial variation of the CMIP6 MME closely matched the observation. The results showed that at annual and seasonal scales, the GPCP and CMIP6 MME reproduced a coherent spatial pattern in terms of the magnitude of precipitation. The humid region received >300 mm and the arid region received <50 mm across Africa and the Arabian Peninsula. The models from the same modeling centers replicated the precipitation levels across different seasons and regions. The CMIP6 MME and the majority of the individual models overestimate (underestimate) in humid (arid and semi-arid)-climate zones. The annual and pre-monsoon seasons (i.e., DJFMA) were better replicated in the CMIP6 GCMs than in the monsoon-precipitation model (MJJASON). The CMIP6 MME (GPCP) showed stronger wetting (drying) trends in the northern hemisphere. In contrast, a strong drying trend in the CMIP6 MME and a weak wetting trend in the GPCP were shown in the Southern Hemisphere. The CMIP6 MME captures the spatial pattern of linear trends better than individual models across different climate zones and regions. The relationship between precipitation and sea-surface temperature (SST) exhibited a high spatial correlation (-0.80 and 0.80) with large variability across different regions and climate zones. The GPCP (CMIP6 MME) exhibited a heterogenous (homogeneous) spatial pattern, with higher correlation coefficients recorded in the CMIP6 MME than in the GPCP in all cases. Individual models from the same modeling centers showed spatial homogeneity in correlation values. The differences exhibited by the individual GCMs highlight the significance of each model's unique dynamics and physics; however, model selection should be considered for specific applications.
英文关键词	Africa Arabian Peninsula GPCP CMIP6 precipitation historical simulation
类型	Article
语种	英语
开放获取类型	gold, Green Published
收录类别	SCI-E
WOS记录号	WOS:000957732500001
WOS关键词	20-1ST CENTURY ; RAINFALL ; CLIMATE ; TEMPERATURE ; MONSOON
WOS类目	Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/395470
推荐引用方式 GB/T 7714	Nooni, Isaac Kwesi,Ogou, Faustin Katchele,Chaibou, Abdoul Aziz Saidou,et al. Evaluating CMIP6 Historical Mean Precipitation over Africa and the Arabian Peninsula against Satellite-Based Observation[J],2023,14(3).
APA	Nooni, Isaac Kwesi,Ogou, Faustin Katchele,Chaibou, Abdoul Aziz Saidou,Nakoty, Francis Mawuli,Gnitou, Gnim Tchalim,&Lu, Jiao.(2023).Evaluating CMIP6 Historical Mean Precipitation over Africa and the Arabian Peninsula against Satellite-Based Observation.ATMOSPHERE,14(3).
MLA	Nooni, Isaac Kwesi,et al."Evaluating CMIP6 Historical Mean Precipitation over Africa and the Arabian Peninsula against Satellite-Based Observation".ATMOSPHERE 14.3(2023).