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

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  • معلومة اضافية
    • Contributors:
      Institut des Géosciences de l’Environnement (IGE); Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (Fédération OSUG)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP); Université Grenoble Alpes (UGA); Université Félix Houphouët-Boigny Abidjan, Côte d'Ivoire (UFHB); Erosion torrentielle neige et avalanches (UR ETGR (ETNA)); Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Université du Ghana = University of Ghana; NERC/DFID "Future Climate for Africa" program under the AMMA-2050 project NE/M019969/1; IRD (Institut de Recherche pour le Developpement; France) UMR IGE Imputation 252RA5; French National program LEFE (Les Enveloppes Fluides et l'Environnement)
    • بيانات النشر:
      CCSD
      Springer Verlag
    • الموضوع:
      2020
    • Collection:
      Université Grenoble Alpes: HAL
    • نبذة مختصرة :
      International audience ; 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).
    • ISBN:
      978-0-00-568215-9
      0-00-568215-0
    • Relation:
      IRD: fdi:010079693; WOS: 000568215000001
    • الرقم المعرف:
      10.1007/s10584-020-02833-z
    • الدخول الالكتروني :
      https://hal.inrae.fr/hal-02949569
      https://hal.inrae.fr/hal-02949569v1/document
      https://hal.inrae.fr/hal-02949569v1/file/Bichet2020_Article_AssessingUncertaintiesInTheReg.pdf
      https://doi.org/10.1007/s10584-020-02833-z
    • Rights:
      http://creativecommons.org/licenses/by/ ; info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.9758B9CF