Climate Dynamics

, Volume 22, Issue 6–7, pp 555–572 | Cite as

Sensitivity of a general circulation model to land surface parameters in African tropical deforestation experiments

  • K. Maynard
  • J.-F. Royer


During the last two decades, several land surface schemes for use in climate, regional and/or mesoscale, hydrological and ecological models have been designed. Incorrect parametrization of land-surface processes and prescription of the surface parameters in atmospheric modeling, can result in artificial changes of the horizontal gradient of the sensible heat flux. Thus, an error in horizontal temperature gradient within the lower atmosphere may be introduced. The reliability of the model depends on the quality of boundary layer scheme implemented and its sensitivity to the bare soil and vegetation parameters. In this study, a series of sensitivity experiments has been conducted over broad time scales, using a version of the ARPEGE Climate Model coupled to the ISBA land surface scheme in order to investigate model sensitivity to separate changes in land surface parameters over Africa. Effects of perturbing vegetation cover, distribution of soil depth, albedo of vegetation, roughness length, leaf area index and minimum stomatal resistance were explored by using a simple statistical analysis. Identifying which parameters are important in controlling turbulent energy fluxes, temperature and soil moisture is dependent on which variables are used to determine sensibility, which type of vegetation and climate regime is being simulated and the magnitude and sign of the parameter change. This study does not argue that a particular parameter is important in ISBA, rather it shows that no general ranking of parameters is possible. So, it is essential to specify all land surface parameters with greater precision when attempting to determine the climate response to modification of the land surface. The implication of ISBA being sensitive to parameters that cannot be validated suggests that there will always be considerable doubt over the predictive quality of land-surface schemes.


Heat Flux Leaf Area Index Latent Heat Flux Roughness Length Surface Albedo 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors thank the IMAGE Team at RIVM for providing the IMAGE 2.2 simulations on CD-Rom, particularly Michiel Schaeffer and Bas Eickhout. We wish to thank Michel Déqué, Robin Clark and Hervé Douville for helpful comments and suggestions, and Fabrice Chauvin and Sophie Tyteca for their support. The software package GrADS ( was used to draw the figures. This study has been supported by a grant from the European Commission Fifth Framework Programme (PROMISE contract EVK2-CT-1999-00022) and by the French “Programme National d’Etude de la Dynamique du Climat” (PNEDC).


  1. Acs F (1994) A coupled soil-vegetation scheme: description, parameters, validation, and sensitivity studies. J Appl Meteorol 33: 268–284CrossRefGoogle Scholar
  2. Beljaars AC, Viterbo P (1994) Sensitivity of winter evaporation to the formulation of aerodynamic resistance in the ECMWF model. Bound Layer Meteorol 71: 135–149Google Scholar
  3. Boucher O, Lohmann U (1995) The sulfate-CCN-cloud albedo effect a sensitivity study with two general circulation models. Tellus 47: 281–300CrossRefGoogle Scholar
  4. Bougeault P (1985) A simple parametrization of the large-scale effects of cumulus convection. Mon Weather Rev 113: 2108-2121CrossRefGoogle Scholar
  5. Braud I, Noilhan J, Bessemoulin P, Mascart P, Haverkamp R, Vauclin M (1993) Bare-ground surface heat and water exchanges under dry conditions: observations and parametrization. Bound Layer Meteorol 66: 173–200Google Scholar
  6. Burke EJ, Shuttleworth WJ, Yang ZL, Mullen SL, Arain MA (2000) The impact of parametrization of heterogeneous vegetation on the modeled large-scale circulation in CCM3-BATS. Geophys Res 27: 397-400Google Scholar
  7. Charney JG (1975) Dynamics of deserts and droughts in the Sahel. Q J R Meteorol Soc l0l: 193–202CrossRefGoogle Scholar
  8. Charney JG, Quik WJ, Chow S-H, Kornfield (1977) A comparative study of the effects of albedo change on drought in semi-arid regions, J Atmos Sci 34: 1366–1385Google Scholar
  9. Chase TN, Pielke RA, Kittel TGF, Nemani R, Running SW (1996) Sensitivity of a general circulation model to changes in leaf area index. J Geophys Res 101: 7393–7408CrossRefGoogle Scholar
  10. Collins D, Avissar R (1994) An evaluation with the Fourier Amplitude Sensitivity Test (FAST) of which land-surface parameters are of greatest importance for atmospheric modelling, J Clim 7: 681–703Google Scholar
  11. Cook KH (1994) Mechanisms by which surface drying perturbs tropical precipitation fields. J Clim 7: 400–413CrossRefGoogle Scholar
  12. Cook KH (1997) Large-scale atmospheric dynamics and Sahelian precipitation. J Clim 10: 1137–1152CrossRefGoogle Scholar
  13. Costa MH, Foley JA (1999) Combined effects of deforestation and doubled atmospheric C02 concentrations on the climate of Amazonia. J Clim 13: 18–34CrossRefGoogle Scholar
  14. Deardorff JW (1978) Efficient prediction of ground surface temperature and moisture, with inclusion of a layer of vegetation. J Geophys Res – Oceans 83: 1889–1903Google Scholar
  15. Déqué M, Dreveton C, Braun A, Cariolle D (1994) The ARPEGE/IFS atmosphere model, a contribution to the French community climate modelling. Clim Dyn 10: 249–266CrossRefGoogle Scholar
  16. Dickinson RE (1984) Modeling evapotranspiration for three-dimensional global climate models. Climate processes and climate sensitivity. Geophys Monogr 29, Am Geophys Union: 58–72Google Scholar
  17. Dirmeyer PA, Shukla J (1994) Albedo as a modulator of climate response to tropical deforestation. J Geophys Res 99: 20 863–20 877CrossRefGoogle Scholar
  18. Douville H, Royer JF, Mahfouf JF (1995a) A new snow parametrization for the Météo-France climate model. Part I: validation in stand-alone experiments. Clim Dyn 12: 21–35CrossRefGoogle Scholar
  19. Douville H, Royer JF, Mahfouf JF (1995b) A new snow parametrization for the Meteo-France climate model. Part II: validation in a 3D GCM experiment. Clim Dyn 12: 37–52CrossRefGoogle Scholar
  20. Eidenshink JC, Faudeen JL (1994) The 1 km AVHRR global land data set-first stages in implementation. Int J Remote Sensing 15: 3,443–3,462Google Scholar
  21. Garratt JR, Hicks BB (1973) Momentum, heat and water vapour transfers to and from natural and artificial surfaces. Q J R Meteorol Soc 99: 680–687CrossRefGoogle Scholar
  22. Gupta HV, Bastidas LA, Sorooshian S, Shuttleworth WJ, Yang ZL (1999) Parameter estimation of a land surface scheme using multicriteria methods. J Geophys Res 104: 19,491–19,503CrossRefGoogle Scholar
  23. Hahmann AN, Dickinson R (1997) RCCM2-BATS model over tropical South America: application to tropical deforestation. J Clim 10: 1944–1964CrossRefGoogle Scholar
  24. Hahmann AN, Dickinson R (2001) A fine-mesh approach for general circulation model and its impact on regional climate. J Clim 14: 1634–1646CrossRefGoogle Scholar
  25. Hansen MC, DeFries RS, R TJG, Sohlberg R (2000) Global land cover classification at 1 km spatial resolution using a classification tree approach. Int J Remote Sensing 21: 1331–1364CrossRefGoogle Scholar
  26. Henderson-Sellers A (1992) Assessing the sensitivity of a land surface scheme to parameters used in tropical-deforestation experiments. Q J R Meteorol Soc 118:1101–1116CrossRefGoogle Scholar
  27. Henderson-Sellers A, Gornitz V (1984) Possible climatic impacts of land cover transformations, with particular emphasis on tropical deforestation. Clim Change 6: 231–257Google Scholar
  28. Henderson-Sellers A, McGuffie K (1995) Global climate models and ‘dynamic’ vegetation. Global Change Biol 1: 63–75Google Scholar
  29. Henderson-Sellers A, Dickinson RE, Durbidge TB, Kennedy PJ, McGuffie K, Pitman AJ (1993) Tropical deforestation: modelling local to regional-scale climate change. J Geophys Res 98: 7289–7315Google Scholar
  30. Hu Z, Islam S (1996) A method to evaluate the importance of interactions between land surface and atmosphere. Water Resour Res 32: 2497–2505CrossRefGoogle Scholar
  31. Jacobs CMJ, De Bruin HAR (1992) The sensitivity of regional transpiration to land-surface characteristics: significance of feedback. J Clim 5: 683–698CrossRefGoogle Scholar
  32. Jacquemin B, Noilhan J (1990) Sensitivity study and validation of a land surface parametrization using the HAPEX-MOBILHY data set. Bound Layer Meteorol 52: 93–134Google Scholar
  33. Kim CP, Entekhabi D (1998) Feedbacks in the land-surface and mixed-layer energy budgets. Bound Layer Meteorol 88: 1–21CrossRefGoogle Scholar
  34. Kleidon A, Heimann M (2000) Assessing the role of deep rooted vegetation in the climate system with model simulations: mechanism, comparison to observations and implications for amazonian deforestation. Clim Dyn 16: 183–199CrossRefGoogle Scholar
  35. Koeppe CE, De Long GC (1958) Weather and climate. McGraw-Hill, New YorkGoogle Scholar
  36. Lean J, Rowntree P (1997) Understanding the sensitivity of a GCM simulation of Amazonian deforestation to the specification of vegetation and soil characteristics. J Clim 10: 1216–1235CrossRefGoogle Scholar
  37. Louis JF (1979) A parametric model of vertical eddy fluxes in the atmosphere. Bound Layer Meteorol 17: 187–202Google Scholar
  38. Louis JF, Tiedtke M, Geleyn JF (1982) A short history of the operational PBL-parametrization at ECMWF. ECMWF Workshop Planetary Boundary Layer Parametrization, ECMWF, Reading, UK, pp 59–80Google Scholar
  39. Mahfouf JF, Manzi AO, Noilhan J, Giordani H, DéquéM (1995) The land surface scheme ISBA within the METEO-FRANCE climate model ARPEGE. Part 1, implementation and preliminary results. J Clim 8: 2039–2057CrossRefGoogle Scholar
  40. Margulis SA, Entekhabi D (2001) A coupled land surface-boundary layer model and its adjoint. J Hydrometeorol 2: 274–296CrossRefGoogle Scholar
  41. Mascart P, Noilhan J, Giordani H (1995) A modified parameterization of the surface layer flux-profile relationships using different roughness length values for heat and momentum. Bound Layer Meteorol 72: 331–344Google Scholar
  42. Masson V, Champeaux JL, Chauvin F, Meriguet C, Lacaze R (2002) Ecoclimap- a global database of land surface parameters at 1km resolution in meteorological and climate models. J Clim 16: 1261–1282Google Scholar
  43. Maynard K, Royer JF (2003) Effects of “realistic” land-cover change on a greenhouse-warmed African climate. Clim Dyn 22: 343–358Google Scholar
  44. Milly PCD, Dunne KA (1994) Potential evaporation and soil moisture in general circulation models. J Clim 3: 209–226Google Scholar
  45. Morcrette JJ (1990) Impact of changes to the radiation transfer parametrizations plus cloud optical properties in the ECMWF model. Mon Weather Rev 118: 847–873CrossRefGoogle Scholar
  46. Niyogi DS, Raman S, Alapaty K, Han J (1997) A dynamic statistical experiment for atmospheric interactions. Environ Mod Assess 2: 307–322CrossRefGoogle Scholar
  47. Noilhan J, Planton S (1989) A simple parametrization of land surface processes for meteorological models. Mon Weather Rev 117: 536–549CrossRefGoogle Scholar
  48. Pitman AJ (1994) Assessing the sensitivity of a land-surface scheme to the parameter values using a single column model. J Clim 7: 1856–1869CrossRefGoogle Scholar
  49. Polcher J, Laval K (1994) The impact of African and Amazonian deforestation on tropical climate. J Hydrol 155: 389–405CrossRefGoogle Scholar
  50. Reynolds RW (1988) A real-time global sea surface temperature analysis. J Clim 1: 75–86CrossRefGoogle Scholar
  51. Ricard JL, Royer JF (1993) A statistical cloud scheme for use in an AGCM. Ann Geophyicae 11: 1095–1115Google Scholar
  52. Rind D (1984) The influence of vegetation on the hydrologic cycle in a global climate model. In: Hansen JE, Takahashi T (eds) Climate processes and climate sensitivity AGU Geophys. Monograph 29 pp. 73–91, American Geophysical Union. Washington, D.C., USAGoogle Scholar
  53. Shukla J, Mintz Y (1982) The influence of land-surface evapotranspiration on the earth’s climate. Science 215: 1498–1501Google Scholar
  54. Siebert J, Sievers U, Zdunkowski W (1992) A one-dimensional simulation of the interaction between land surface processes and the atmosphere. Bound Layer Meteorol 59: 1–34Google Scholar
  55. Sud YC, Fennessy MJ (1982) A study of the influence of surface albedo on July circulation in semi-arid regions using the GLAS GCM. J Climatol 2: 105–125Google Scholar
  56. Sud YC, Smith WE (1985) Influence of local land surface processes on the Indian Monsoon: a numerical study. J Clim Appl Meteorol 4: 1015–1036CrossRefGoogle Scholar
  57. Sud YC, Molod A (1988) A GCM simulation study of the influence of Sahara evapotranspiration and surface-albedo anomalies on July circulation and rainfall. Mon Weather Rev 116: 2388–2400CrossRefGoogle Scholar
  58. Sud YC, Shukla J, Mintz Y (1988) Influence of land surface roughness on atmospheric circulation and precipitation: a sensitivity study with a general circulation model. J Appl Meteorol 27: 1036–1054CrossRefGoogle Scholar
  59. Sud YC, Lau KM, Walker GK, Kim JH (1995) Understanding biosphere-precipitation relationships: theory, model similations and logical inferences. Mausam 46: 1–14Google Scholar
  60. Verhoff A, Alen SJ, Lloyd CR (1999) Seasonal variation of surface energy balance over two sahelian surfaces. Int J Climatol 19: 1267–1277CrossRefGoogle Scholar
  61. Webb RS, Rosenzweig CE, Levine ER (1991) A global data set of soil particle size properties. Technical Report 4286, NASA, GISS, New YorkGoogle Scholar
  62. Wetzel PJ, Chang JT (1988) Evapotranspiration from a nonuniform surface: a first approach for short term numerical weather prediction. Mon Weather Rev 116: 600–621CrossRefGoogle Scholar
  63. Wilson MF, Henderson-Sellers A (1985) A global archive of land cover and soils data for use in general circulation climate models. J Climatol 5: 119–143Google Scholar
  64. Wilson MF, Henderson-Sellers A, Dickinson RE, Kennedy PJ (1987a) Sensitivity of the biosphere-atmosphere transfer scheme (BATS) to the inclusion of variable soil characteristics. J Appl Meteorol 26: 341–362CrossRefGoogle Scholar
  65. Wilson MF, Henderson-Sellers A, Dickinson RE, Kennedy PJ (1987b) Investigation of the sensitivity of the land-surface parametrization of the NCAR community climate model in regions of tundra vegetation. J Climatol 7: 319–343Google Scholar
  66. Xie P, Arkin PA (1996) Analyses of global monthly precipitation using gauge observations, satellite estimates and numerical model predictions. J Clim 9: 840–858CrossRefGoogle Scholar
  67. Xue Y, Bastable HG, Dirmeyer HG, Sellers PJ (1996) Sensitivity of simulated surface fluxes to changes in land surface parametrizations: a study using ABRACOS data. J App Meteorol 35: 386–401CrossRefGoogle Scholar

Copyright information

© Springer-Verlag  2004

Authors and Affiliations

  1. 1.Météo-France CNRMToulouse Cedex 1France

Personalised recommendations