Precipitation Climatology in an Ensemble of CORDEX-Africa Regional Climate Simulations

Author:

Nikulin Grigory1,Jones Colin1,Giorgi Filippo2,Asrar Ghassem3,Büchner Matthias4,Cerezo-Mota Ruth5,Christensen Ole Bøssing6,Déqué Michel7,Fernandez Jesus8,Hänsler Andreas9,van Meijgaard Erik10,Samuelsson Patrick1,Sylla Mouhamadou Bamba2,Sushama Laxmi11

Affiliation:

1. Rossby Centre, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden

2. Abdus Salam International Centre for Theoretical Physics, Trieste, Italy

3. World Climate Research Programme, Geneva, Switzerland

4. Potsdam Institute for Climate Impact Research, Potsdam, Germany

5. University of Cape Town, Cape Town, South Africa

6. Danmarks Meteorologiske Institut, Copenhagen, Danmark

7. Centre National de Recherches Météorologiques, Météo-France, Toulouse, France

8. Universidad de Cantabria, Santander, Spain

9. Climate Service Center, Helmholtz-Zentrum Geesthacht, Hamburg, Germany

10. Koninklijk Nederlands Meteorologisch Instituut, De Bilt, Netherlands

11. Université du Québec à Montréal, Montréal, Quebec, Canada

Abstract

Abstract An ensemble of regional climate simulations is analyzed to evaluate the ability of 10 regional climate models (RCMs) and their ensemble average to simulate precipitation over Africa. All RCMs use a similar domain and spatial resolution of ~50 km and are driven by the ECMWF Interim Re-Analysis (ERA-Interim) (1989–2008). They constitute the first set of simulations in the Coordinated Regional Downscaling Experiment in Africa (CORDEX-Africa) project. Simulated precipitation is evaluated at a range of time scales, including seasonal means, and annual and diurnal cycles, against a number of detailed observational datasets. All RCMs simulate the seasonal mean and annual cycle quite accurately, although individual models can exhibit significant biases in some subregions and seasons. The multimodel average generally outperforms any individual simulation, showing biases of similar magnitude to differences across a number of observational datasets. Moreover, many of the RCMs significantly improve the precipitation climate compared to that from their boundary condition dataset, that is, ERA-Interim. A common problem in the majority of the RCMs is that precipitation is triggered too early during the diurnal cycle, although a small subset of models does have a reasonable representation of the phase of the diurnal cycle. The systematic bias in the diurnal cycle is not improved when the ensemble mean is considered. Based on this performance analysis, it is assessed that the present set of RCMs can be used to provide useful information on climate projections over Africa.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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