Evaluation of CMIP6 model skills in simulating tropical climate extremes over Malawi, Southern Africa

• DOI: 10.1007/s40808-023-01867-3
• Publication Date: 2023-09-26T21:01:23Z
• Authors: Bernard Mmame; Cosmo Ngongondo
• Keywords: Dry season; Wet season

Abstract Malawi, a developing country in southeast Africa, is one of the most vulnerable countries to climate change and associated impacts. Availability observed data inform our knowledge on however, key challenge has led relatively little research subject. Alternative products, such as Global Climate Models (GCMs) phase6 Coupled Model Intercomparison Project (CMIP6), accords chance bridge this gap. These products need some validation against ascertain their level performance. This study therefore, evaluates ability nineteen CMIP6 models simulating both annual seasonal temperature precipitation over Malawi from 1980 2014. Observed performance metrics bias, root mean square error (RMSE), spatial correlation coefficient, standard deviation Percentage Bias (PBIAS) were employed assess individual models. Our quantitative analysis shows that could simulate area, with coefficient values 0.70, RMSE between 0.9 2.0 PBIAS $$\le$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>≤</mml:mo></mml:math> 10%. The results are suggesting better than those reported previous studies domain using CMIP3 CMIP5 model datasets. Of all evaluated study, no single performed best compared dataset, because varying season season. Hence, end users advised use simulations area care for decision making mitigation adaptation change.