Two
simulations of five years (2003-2007) were conducted with the Regional Climate
models RegCM4, one coupled with Land surface models BATS and the other with
CLM4.5 over West Africa, where simulated air temperature and precipitation were
analyzed. The purpose of this study is to assess the performance of RegCM4
coupled with the new CLM4.5 Landsurface scheme and the standard one named BATS in order to find the best
configuration of RegCM4 over West African. This study could improve our
understanding of the sensitivity of land surface model in West Africa climate
simulation, and provide relevant information to RegCM4 users. The results show
fairly realistic restitution of West Africa’s climatology and indicate
correlations of 0.60 to 0.82 between the simulated fields (BATS and CLM4.5) for
precipitation. The substitution of BATS surface scheme by CLM4.5 in the model
configuration, leads mainly to an improvement of precipitation over the
Atlantic Ocean, however, the impact is not sufficiently noticeable over the
continent. While the CLM4.5 experiment restores the seasonal cycles and spatial
distribution, the biases increase for precipitation and temperature. Positive
biases already existing with BATS are amplified over some sub-regions. This
study concludes that temporal localization (seasonal effect), spatial
distribution (grid points) and magnitude of precipitation and temperature
(bias) are not simultaneously improved by CLM4.5. The introduction of the new
land surface scheme CLM4.5, therefore, leads to a performance of the same order
as that of BATS, albeit with a more detailed formulation.
References
[1]
Rummukainen, M. (2010) State-of-the-Art with Regional Climate Models. WIREs Climate Change, 1, 82-96. https://doi.org/10.1002/wcc.8
[2]
Giorgi, F., Coppola, E., Solmon, F., Mariotti, L., Sylla, M.B., Bi, X., et al. (2012) RegCM4: Model Description and Preliminary Tests over Multiple CORDEX Domains. Climate Research, 52, 7-29. https://doi.org/10.3354/cr01018
[3]
Sylla, M.B., Giorgi, F., Coppola, E. and Mariotti, L. (2013) Uncertainties in Daily Rainfall over Africa: Assessment of Gridded Observation Products and Evaluation of a Regional Climate Model Simulation. International Journal of Climatology, 33, 1805-1817. https://doi.org/10.1002/joc.3551
[4]
Martínez-Castro, D., Porfirio da Rocha, R., Bezanilla-Morlot, A., Alvarez-Escudero, L., Reyes-Fernández, J.P., Silva-Vidal, Y., et al. (2006) Sensitivity Studies of the RegCM3 Simulation of Summer Precipitation, Temperature and Local Wind Field in the Caribbean Region. Theoretical and Applied Climatology, 86, 5-22. https://doi.org/10.1007/s00704-005-0201-9
[5]
Sylla, M.B., Gaye, A.T., Pal, J.S., Jenkins, G.S. and Bi, X.Q. (2009) High-Resolution Simulations of West African Climate Using Regional Climate Model (RegCM3) with Different Lateral Boundary Conditions. Theoretical and Applied Climatology, 98, 293-314. https://doi.org/10.1007/s00704-009-0110-4
[6]
Diallo, I., Sylla, M.B., Camara, M. and Gaye, A.T. (2013) Interannual Variability of Rainfall over the Sahel Based on Multiple Regional Climate Models Simulations. Theoretical and Applied Climatology, 113, 351-362. https://doi.org/10.1007/s00704-012-0791-y
[7]
Raju, P.V.S., Bhatla, R., Almazroui, M. and Assiri, M. (2015) Performance of Convection Schemes on the Simulation of Summer Monsoon Features over the South Asia CORDEX Domain Using RegCM-4.3. International Journal of Climatology, 35, 4695-4706. https://doi.org/10.1002/joc.4317
[8]
Chung, J.X., Juneng, L., Tangang, F. and Jamaluddin, A.F. (2018) Performances of BATS and CLM Land-Surface Schemes in RegCM4 in Simulating Precipitation over CORDEX Southeast Asia Domain. International Journal of Climatology, 38, 794-810. https://doi.org/10.1002/joc.5211
[9]
Koné, B., Diedhiou, A., Sylla, M.B., Giorgi, F., Anquetin, S., Bamba, A., et al. (2018) Sensitivity Study of the Regional Climate Model RegCM4 to Different Convective Schemes over West Africa. Earth System Dynamics, 9, 1261-1278. https://doi.org/10.5194/esd-9-1261-2018
[10]
Chen, L., Ma, Z. and Fan, X. (2012) A Comparative Study of Two Land Surface Schemes in WRF Model over Eastern China. Journal of Tropical Meteorology, 18, 445-456.
[11]
Steiner, A.L., Pal, J.S., Rauscher, S.A., Bell, J.L., Diffenbaugh, N.S., Boone, A., et al. (2009) Land Surface Coupling in Regional Climate Simulations of the West African Monsoon. Climate Dynamics, 33, 869-892. https://doi.org/10.1007/s00382-009-0543-6
[12]
Halder, S., Saha, S., Dirmeyer, P., Chase, T. and Goswami, B.N. (2016) Investigating the Impact of Land-Use Land-Cover Change on Indian Summer Monsoon Daily Rainfall and Temperature during 1951-2005 Using a Regional Climate Model. Hydrology and Earth System Sciences, 20, 1765-1784. https://doi.org/10.5194/hess-20-1765-2016
[13]
Wang, X., Yang, M. and Pang, G. (2015) Influences of Two Land-Surface Schemes on RegCM4 Precipitation Simulations over the Tibetan Plateau. Advances in Meteorolgy, 2015, Article ID: 106891. https://doi.org/10.1155/2015/106891
[14]
Grell, G.A., Dudhia, J. and Stauffer, D.R. (1994) A Description of the Fifth-Generation Penn State/NCAR Mesoscale Model (MM5) (No. NCAR/TN-398+STR). University Corporation for Atmospheric Research, Boulder.
[15]
Kiehl, J.T., Hack, J.J., Bonan, G.B., Boville, B.A. and Briegleb, B.P. (1996) Description of the NCAR Community Climate Model (CCM3). Technical Note, National Center for Atmospheric Research, Boulder.
[16]
Zakey, A.S., Solmon, F. and Giorgi, F. (2006) Implementation and Testing of a Desert Dust Module in a Regional Climate Model. Atmospheric Chemistry and Physics, 6, 4687-4704. https://doi.org/10.5194/acp-6-4687-2006
[17]
Dickinson, R., Henderson-Sellers, A. and Kennedy, P. (1993) Biosphere-Atmosphere Transfer Scheme (BATS) Version 1e as Coupled to the NCAR Community Climate Model. UCAR (University Corporation for Atmospheric Research)/NCAR (National Center for Atmospheric Research), Boulder.
[18]
Wilson, M.F. (1984) The Construction and Use of Land Surface Information in a General Circulation Climate Model. PhD Thesis, University of Liverpool, Liverpool, 234 p.
[19]
Giorgi, F., Francisco, R. and Pal, J. (2003) Effects of a Subgrid-Scale Topography and Land Use Scheme on the Simulation of Surface Climate and Hydrology. Part I: Effects of Temperature and Water Vapor Disaggregation. Journal of Hydrometeorology, 4, 317-333. https://doi.org/10.1175/1525-7541(2003)4<317:EOASTA>2.0.CO;2
[20]
Oleson, K.W., Niu, G.-Y., Yang, Z.-L., Lawrence, D.M., Thornton, P.E., Lawrence, P.J., et al. (2008) Improvements to the Community Land Model and Their Impact on the Hydrological Cycle. Journal of Geophysical Research: Biogeosciences, 113, Article ID: G01021. https://doi.org/10.1029/2007JG000563
[21]
Bonan, G.B., Levis, S., Kergoat, L. and Oleson, K.W. (2002) Landscapes as Patches of Plant Functional Types: An Integrating Concept for Climate and Ecosystem Models. Global Biogeochemical Cycles, 16, 5-1-5-23. https://doi.org/10.1029/2000GB001360
[22]
Lawrence, P.J. and Chase, T.N. (2007) Representing a New Modis Consistent Land Surface in the Community Land Model (CLM 3.0). Journal of Geophysical Research: Biogeosciences, 112, Article ID: G01023. https://doi.org/10.1029/2006JG000168
[23]
Thornton, P.E. and Zimmermann, N.E. (2007) An Improved Canopy Integration Scheme for a Land Surface Model with Prognostic Canopy Structure. Journal of Climate, 20, 3902-3923. https://doi.org/10.1175/JCLI4222.1
[24]
Dee, D.P., Uppala, S.M., Simmons, A.J., Berrisford, P., Poli, P., Kobayashi, S., et al. (2011) The ERA-Interim Reanalysis: Configuration and Performance of the Data Assimilation System. Quarterly Journal of the Royal Meteorological Society, 137, 553-597. https://doi.org/10.1002/qj.828
[25]
Huffman, G.J., Bolvin, D.T., Nelkin, E.J., Wolff, D.B., Adler, R.F., Gu, G., et al. (2007) The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales. Journal of Hydrometeorology, 8, 38-55. https://doi.org/10.1175/JHM560.1
[26]
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., et al. (2015) The Climate Hazards Infrared Precipitation with Stations—A New Environmental Record for Monitoring Extremes. Scientific Data, 2, Article No. 150066. https://doi.org/10.1038/sdata.2015.66
[27]
Xie, P. and Arkin, P.A. (1997) Global Precipitation: A 17-Year Monthly Analysis Based on Gauge Observations, Satellite Estimates, and Numerical Model Outputs. Bulletin of the American Meteorological Society, 78, 2539-2558. https://doi.org/10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2
[28]
Nikulin, G., Jones, C., Giorgi, F., Asrar, G., Büchner, M., Cerezo-Mota, R., et al. (2012) Precipitation Climatology in an Ensemble of CORDEX-Africa Regional Climate Simulations. Journal of Climate, 25, 6057-6078. https://doi.org/10.1175/JCLI-D-11-00375.1
[29]
Taylor, K.E. (2001) Summarizing Multiple Aspects of Model Performance in a Single Diagram. Journal of Geophysical Research: Atmospheres, 106, 7183-7192. https://doi.org/10.1029/2000JD900719
[30]
Cook, K.H. (1999) Generation of the African Easterly Jet and Its Role in Determining West African Precipitation. Journal of Climate, 12, 1165-1184. https://doi.org/10.1175/1520-0442(1999)012<1165:GOTAEJ>2.0.CO;2
[31]
Sylla, M.B., Giorgi, F. and Stordal, F. (2012) Large-Scale Origins of Rainfall and Temperature Bias in High-Resolution Simulations over Southern Africa. Climate Research, 52, 193-211. https://doi.org/10.3354/cr01044
[32]
Wang, W. and Seaman, N.L. (1997) A Comparison Study of Convective Parameterization Schemes in a Mesoscale Model. Monthly Weather Review, 125, 252-278. https://doi.org/10.1175/1520-0493(1997)125<0252:ACSOCP>2.0.CO;2
