Assessing uncertainties in the regional projections of precipitation in CORDEX-AFRICA

Adeline Bichet (), Arona Diedhiou, Benoit Hingray, Guillaume Evin, N’Datchoh Evelyne Touré, Klutse Nana Ama Browne and Kouakou Kouadio
Additional contact information
Adeline Bichet: University Grenoble Alpes, IGE UMR 5001
Arona Diedhiou: University Grenoble Alpes, IGE UMR 5001
Benoit Hingray: University Grenoble Alpes, IGE UMR 5001
Guillaume Evin: INRAE, ETNA
N’Datchoh Evelyne Touré: University Félix Houphouët Boigny
Klutse Nana Ama Browne: University of Ghana
Kouakou Kouadio: University Félix Houphouët Boigny

Climatic Change, 2020, vol. 162, issue 2, No 24, 583-601

Abstract: 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 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://link.springer.com/10.1007/s10584-020-02833-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:climat:v:162:y:2020:i:2:d:10.1007_s10584-020-02833-z

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/10584

DOI: 10.1007/s10584-020-02833-z

Access Statistics for this article

Climatic Change is currently edited by M. Oppenheimer and G. Yohe

More articles in Climatic Change from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().