Uzoma Chukwuemeka Nworgu, H. Nnamchi, Nilton Manuel Évora Do Rosário
{"title":"Divergent future change in South Atlantic Ocean Dipole impacts on regional rainfall in CMIP6 models","authors":"Uzoma Chukwuemeka Nworgu, H. Nnamchi, Nilton Manuel Évora Do Rosário","doi":"10.1088/2752-5295/ad3a0e","DOIUrl":null,"url":null,"abstract":"\n The South Atlantic Ocean Dipole (SAOD) exerts strong influence on climate variability in parts of Africa and South America. Here we assess the ability of an ensemble of 35 state-of-the-art coupled global climate models to simulate the SAOD impacts on regional rainfall for the historical period (1950 to 2014) and future projections (2015 - 2079). For both periods we consider the peak phase of the dipole which is in austral winter. Observational analysis reveals four regions with spatially coherent SAOD impacts on rainfall; Northern Amazon, Guinea Coast, Central Africa, and Southeast Brazil. The observed rainfall response to the SAOD over Northern Amazon (0.31 mm/day), Guinea Coast (0.38 mm/day), and Southeast Brazil (0.12 mm/day) are significantly underestimated by the modeled ensemble-mean response of 0.10±0.15 mm/day, 0.05±0.15 mm/day, -0.01±0.04 mm/day, respectively. A too southerly rain belt in the ensemble, associated with warmer-than-observed Atlantic cold tongue, leads to better performance of models over Central Africa (46% simulate observations-consistent SAOD-rainfall correlations) and poor performance over the Guinea Coast (only 5.7% simulate observations-consistent SAOD-rainfall correlations). We found divergent responses among the projections of ensemble members precluding a categorical statement on the future strength of the SAOD-rainfall relationship in a high-emissions scenario. Our findings highlight key uncertainties that must be addressed to enhance the value of SAOD-rainfall projections for the affected African and South American countries.","PeriodicalId":432508,"journal":{"name":"Environmental Research: Climate","volume":"316 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Research: Climate","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/2752-5295/ad3a0e","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The South Atlantic Ocean Dipole (SAOD) exerts strong influence on climate variability in parts of Africa and South America. Here we assess the ability of an ensemble of 35 state-of-the-art coupled global climate models to simulate the SAOD impacts on regional rainfall for the historical period (1950 to 2014) and future projections (2015 - 2079). For both periods we consider the peak phase of the dipole which is in austral winter. Observational analysis reveals four regions with spatially coherent SAOD impacts on rainfall; Northern Amazon, Guinea Coast, Central Africa, and Southeast Brazil. The observed rainfall response to the SAOD over Northern Amazon (0.31 mm/day), Guinea Coast (0.38 mm/day), and Southeast Brazil (0.12 mm/day) are significantly underestimated by the modeled ensemble-mean response of 0.10±0.15 mm/day, 0.05±0.15 mm/day, -0.01±0.04 mm/day, respectively. A too southerly rain belt in the ensemble, associated with warmer-than-observed Atlantic cold tongue, leads to better performance of models over Central Africa (46% simulate observations-consistent SAOD-rainfall correlations) and poor performance over the Guinea Coast (only 5.7% simulate observations-consistent SAOD-rainfall correlations). We found divergent responses among the projections of ensemble members precluding a categorical statement on the future strength of the SAOD-rainfall relationship in a high-emissions scenario. Our findings highlight key uncertainties that must be addressed to enhance the value of SAOD-rainfall projections for the affected African and South American countries.