Projected trends of extreme rainfall events from CMIP5 models over Central Africa

Abstract

In this study, the projections of daily rainfall from an ensemble mean of 20 global climate models (GCMs) are used to examine projected trends in heavy rainfall distribution over Central Africa (CA), under the representative concentration pathway 8.5. For this purpose, two analyses periods of 40-years have been selected (2006-2045 and 2056-2095) to compute trends in the 90th and 99th percentiles of the daily rainfall distributions. We found that large increase trend is mostly found in the 99th percentile of rainfall events, over southern Chad, northern Cameroon, northern Zambia, and in the Great Lakes Area. This can be attributed to the increase of moisture convergence intensified by the presence of the Congo Basin rainforest. It is also shown that the largest number of GCMs with a trend of the same sign as the average trend is observed over the above regions. It is thus clear that the projected increase trends in heavy rainfall events may further worse floods which are real problems in the CA countries. Therefore, strong subregional policies are needed to help design effective adaptation and mitigation measures for the region's countries.

Assessment of CMIP5 multimodel mean for the historical climate of Africa

“…The interpolation method used in this study do not have any significant impact on the spatial distribution of climatology, trends, biases or annual cycle. Several past studies have also used bi‐linear interpolation and obtained satisfactory results (New et al ., ; Hempel et al ., ; Zhao et al ., ; Li et al ., ; Fotso‐Nguemo et al ., ; Salunke et al ., ). Since this paper mainly focuses on the climatological seasonal means, the interpolation has negligible impact on the findings of this paper.…”

“…Many studies have examined the response of precipitation over the African region under the global climate change (Biasutti et al, 2008(Biasutti et al, , 2009Monerie et al, 2012aMonerie et al, , 2012b. The extreme weather conditions are noted to increase over the major part of African continent (Nicholson, 2013) and frequent changes are noted in wet and dry conditions (Fontaine et al, 2011;Fotso-Nguemo et al, 2018;Ongoma et al, 2018). This year-to-year precipitation variance tends to change the populace lifestyles and activities, such as changes in the areas under cultivation.…”

An evaluation of COSMO‐CLM regional climate model in simulating precipitation over Central Africa

“…Given the fact that frequency and intensity of rainy days are major sources which highly contribute to total precipitation (Camberlin et al ., ), and that only intensity of rainy days is strongly underestimated by the model during most seasons, it appears that the dry biases reported in Figures m–p and are likely connected to the less intense events simulated by the model. It is worth to mention that the CCLM's behaviour to simulate too much rainy days but less intense events is typical of most GCMs and RCMs models (Crétat et al ., ; Diallo et al ., ; Vondou and Haensler, ; Fotso‐Nguemo et al ., ; Sonkoué et al ., ; Fotso‐Nguemo et al ., ; Tamoffo et al ., ).…”

“…The main objective of the CORDEX project is to develop international collaboration in order to generate an ensemble of high‐resolution climate projections of regional climate models (RCMs; Nikulin et al ., ), by downscaling different global climate models (GCMs; Taylor et al ., ) over selected continental domains. For instance, several studies using GCMs have been carried out to investigate different characteristics of the African climate (Kamga, ; Dai, ; Washington et al ., ; Aloysius et al ., ; Fotso‐Nguemo et al ., ; Nkiaka et al ., ; Sonkoué et al ., ; Zebaze et al ., ). In these studies, despite the great ability demonstrated by GCMs to reasonably replicate the basic main features of the African climate, they nevertheless showed considerable weaknesses.…”

CORDEX Multi‐RCM Hindcast Over Central Africa: Evaluation Within Observational Uncertainty

“…Coarse spatial resolution global climate models (GCMs) are the primary tools for investigating the planetary response of the climate system to various forcing and for making global projections of future climate over the current centuries, and beyond (Aloysius et al, ; Creese et al, ; Fotso‐Nguemo et al, ; James & Washington, ; Lee & Wang, ; Moise & Delage, ; Ruiz‐Barradas et al, ; Seth et al, ; Sonkoué et al, ; Taylor et al, ). Abilities of GCMs to anticipate climate change are often riddled by range of uncertainties including models' imperfection, natural variability, and differences in societal and technological development scenarios (Deser, Knutti, et al, ; Deser, Phillips, et al, ; Hawkins & Sutton, ; Hewitt et al, ; Kay et al, ; Knutti & Sedláček, ; Knutti et al, ; Schaller et al, ; Xie et al, ).…”