Climate Dynamics

, Volume 33, Issue 6, pp 869–892 | Cite as

Land surface coupling in regional climate simulations of the West African monsoon

  • Allison L. Steiner
  • Jeremy S. Pal
  • Sara A. Rauscher
  • Jason L. Bell
  • Noah S. Diffenbaugh
  • Aaron Boone
  • Lisa C. Sloan
  • Filippo Giorgi


Coupling of the Community Land Model (CLM3) to the ICTP Regional Climate Model (RegCM3) substantially improves the simulation of mean climate over West Africa relative to an older version of RegCM3 coupled to the Biosphere Atmosphere Transfer Scheme (BATS). Two 10-year simulations (1992–2001) show that the seasonal timing and magnitude of mean monsoon precipitation more closely match observations when the new land surface scheme is implemented. Specifically, RegCM3–CLM3 improves the timing of the monsoon advance and retreat across the Guinean Coast, and reduces a positive precipitation bias in the Sahel and Northern Africa. As a result, simulated temperatures are higher, thereby reducing the negative temperature bias found in the Guinean Coast and Sahel in RegCM3–BATS. In the RegCM3–BATS simulation, warmer temperatures in northern latitudes and wetter soils near the coast create excessively strong temperature and moist static energy gradients, which shifts the African Easterly Jet further north than observed. In the RegCM3–CLM3 simulation, the migration and position of the African Easterly Jet more closely match reanalysis winds. This improvement is triggered by drier soil conditions in the RegCM3–CLM3 simulation and an increase in evapotranspiration per unit precipitation. These results indicate that atmosphere–land surface coupling has the ability to impact regional-scale circulation and precipitation in regions exhibiting strong hydroclimatic gradients.


African monsoon Land surface modeling Soil moisture Land surface–atmosphere coupling RegCM3 Regional climate modeling 



This work was supported in part by NSF awards 0315677 and 0450221 to LCS and NSD. We gratefully acknowledge the European Centre for Medium-Range Weather Forecasts for the use of the ERA-40 data. We also acknowledge the use of CMAP Precipitation data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA (, and the contributed simulations of the ALMIP Working Group: G. Balsamo, P. de Rosnay, A. Beljaars, C. Delire, P. Harris, C. Taylor, T. Orgeval, J. Polcher, A. Ducharne, A. Nørgaard, I. Sandholt, Y. Xue, I. Poccard-Leclercq, S. Gascoin, Y. Gusev, O. Nasonova, S. Saux-Picart, C. Ottle, and B. Decharme. We thank Benjamin Lintner and Adrian Tompkins for useful discussions.


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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Allison L. Steiner
    • 1
  • Jeremy S. Pal
    • 2
  • Sara A. Rauscher
    • 3
  • Jason L. Bell
    • 4
  • Noah S. Diffenbaugh
    • 5
  • Aaron Boone
    • 6
  • Lisa C. Sloan
    • 4
  • Filippo Giorgi
    • 3
  1. 1.Department of Atmospheric, Oceanic and Space SciencesUniversity of MichiganAnn ArborUSA
  2. 2.Department of Civil Engineering and Environmental ScienceLoyola Marymount UniversityLos AngelesUSA
  3. 3.Earth System Physics – Weather and Climate GroupAbdus Salam International Centre for Theoretical PhysicsTriesteItaly
  4. 4.Department of Earth and Planetary SciencesUniversity of CaliforniaSanta CruzUSA
  5. 5.Purdue Climate Change Research Center and Department of Earth and Atmospheric SciencesPurdue UniversityWest LafayetteUSA
  6. 6.CNRS/GAME, CNRM Météo-FranceToulouseFrance

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