Evaluation of CMIP6 Models Skill in Representing Annual Extreme Precipitation over Northern and Southern Nigeria

Autor: Adamu Bala, A. Momoh Aliu, Liman Salihu Wan
Rok vydání: 2023
Předmět:
Zdroj: Journal of Geography, Environment and Earth Science International. 27:49-61
ISSN: 2454-7352
DOI: 10.9734/jgeesi/2023/v27i2670
Popis: In this study, we evaluate the performance of 13 climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating seven (7) extreme precipitation indices over Northern and southern Nigeria. The considered extreme indices designated in this study were, Total precipitation (PRCPTOT), maximum consecutive wet days (CWD), Heavy precipitation days (R10mm), Very heavy precipitation days (R20mm), Max-5 days Precipitation (RX5day), Extremely wet days (R99pTOT) and Very wet days (R95pTOT). The performance of these 13 climate models are assesed by comparing the model simulation to the observed dataset from the Global Precipitation Climatology Project (GPCP). The performance of CMIP6 models in capturing extreme precipitation characteristics is revealed through some selected multiple descriptive statistics: the normalized mean bias error, RMSE, NRMSE, and Taylor diagram. The descriptive statistics conclusively revealed the satisfactory performance of Cmip6 models in simulation of most extreme events over the north and southern region of Nigeria, as the selected 13 climate models showed a high statistical correlation of (~0.8) when compared with the observed GPCP data except for maximum consecutive wet days (CWD). Overall, majority of CMIP6 models were able to accurately represented only six (6) of the extreme indices, and a significant majority of CMIP6 models failed in simulating maximum consecutive wet days (CWD) in both northern and southern Nigeria.
Databáze: OpenAIRE