Assessing uncertainties in the regional projections of precipitation in CORDEX-AFRICA
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Assessing uncertainties in the regional projections of precipitation in CORDEX-AFRICA Adeline Bichet 1 & Arona Diedhiou 1,2 & Benoit Hingray 1 & Guillaume Evin 3 & N’Datchoh Evelyne Touré 2 & Klutse Nana Ama Browne 4 & Kouakou Kouadio 2 Received: 14 October 2019 / Accepted: 12 August 2020/ # The Author(s) 2020
Abstract
Over the past decades, large variations of precipitation were observed in Africa, which often led to dramatic consequences for local society and economy. To avoid such disasters in the future, it is crucial to better anticipate the expected changes, especially in the current context of climate change and population growth. To this date, however, projections of precipitation over Africa are still associated with very large uncertainties. To better understand how this uncertainty can be reduced, this study uses an advanced Bayesian analysis of variance (ANOVA) method to characterize, for the first time in the regional climate projections of CORDEX-AFRICA, the different sources of uncertainty associated with the projections of precipitation over Africa. By 2090, the ensemble mean precipitation is projected to increase over the Horn of Africa from September to May and over the eastern Sahel and Guinea Coast from June to November. It is projected to decrease over the northern coast and southern Africa all year long, over western Sahel from March to August, and over the Sahel and Guinea Coast from March to May. Most of these projections however are not robust, i.e., the magnitude of change is smaller than the associated uncertainty. Over time, the relative contribution of internal variability (excluding interannual variability) to total uncertainty is moderate and quickly falls below 10%. By 2090, it is found that over the Horn of Africa, northern coast, southern Africa, and Sahel, most of the uncertainty results from a large dispersion across the driving Global Climate Models (in particular MIROC, CSIRO, CCCma, and IPSL), whereas over the tropics and parts of eastern Africa, most of the uncertainty results from a large dispersion across Regional Climate Models (in particular CLMcom). Keywords CORDEX-AFRICA . Precipitation . Bayesian ANOVA . Model uncertainty . Internal variability
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10584-02002833-z) contains supplementary material, which is available to authorized users.
* Adeline Bichet adeline.bichet@univ–grenoble–alpes.fr Extended author information available on the last page of the article
Climatic Change
1 Introduction Global warming is expected to have substantial consequences on precipitation and its variability, especially extreme events, potentially leading to more frequent and severe droughts and flood episodes in both, the tropics and the subtropical regions (Zwiers et al. 2013; Giorgi et al. 2014). Precipitation is the main driver of the variability of water resources, and Africa is particularly vulnerable to its variations, especially in the rural areas where agriculture is the most prominent
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