• Bacmeister, J., , Pegion P. J. , , Schubert S. D. , , and Suarez M. J. , 2000: Atlas of seasonal means simulated by the NSIPP 1 atmospheric GCM. NASA Tech. Memo. 2000-104606, Vol. 17, 194 pp.

  • Boer, G. J., , McFarlane N. A. , , and Lazare M. , 1992: Greenhouse gas-induced climate change simulated with the CCC second-generation general circulation model. J. Climate, 5 , 10451077.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bonan, G. B., , Oleson K. W. , , Vertenstein M. , , Levis S. , , Zeng Z. , , Dai Y. , , Dickinson R. E. , , and Yang Z-L. , 2002: The land surface climatology of the Community Land Model coupled to the NCAR Community Climate Model. J. Climate, 15 , 31233149.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brubaker, K. L., , Entekhabi D. , , and Eagleson P. S. , 1993: Estimation of continental precipitation recycling. J. Climate, 6 , 10771089.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Charney, J., , Quirk W. J. , , Chow S. H. , , and Kornfield J. , 1977: Comparative study of effects of albedo change on drought in semi-arid regions. J. Atmos. Sci., 34 , 13661385.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Collins, W. D., and Coauthors, 2004: Description of the NCAR Community Atmosphere Model (CAM 3.0). NCAR Tech. Note NCAR/TN-464+STR. [Available at http://www.ccsm.ucar.edu/models/atm-cam/docs/description/.].

  • Colman, R., , Fraser J. , , and Rotstayn L. , 2001: Climate feedbacks in a general circulation model incorporating prognostic clouds. Climate Dyn., 18 , 103122.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Conaty, A. L., , Jusem J. C. , , Takacs L. , , Keyser D. , , and Atlas R. , 2001: The structure and evolution of extratropical cyclones, fronts, jet streams, and the tropopause in the GEOS general circulation model. Bull. Amer. Meteor. Soc., 82 , 18531867.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cox, P. M., , Betts R. A. , , Bunton C. B. , , Essery R. L. H. , , Rowntree P. R. , , and Smith J. , 1999: The impact of new land surface physics on the GCM simulation of climate and climate sensitivity. Climate Dyn., 15 , 183203.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Delworth, T. L., , and Manabe S. , 1989: The influence of soil wetness on near-surface atmospheric variability. J. Climate, 2 , 14471462.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Desborough, C. E., 1999: Surface energy balance complexity in GCM land surface models. Climate Dyn., 15 , 389403.

  • Desborough, C. E., , Pitman A. J. , , and McAvaney B. J. , 2001: Surface energy balance complexity in GCM land surface models, Part 2, Coupled simulations. Climate Dyn., 17 , 615626.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dirmeyer, P. A., 1994: Vegetation stress as a feedback mechanism in midlatitude drought. J. Climate, 7 , 14631483.

  • Dirmeyer, P. A., , and Zeng F. J. , 1999: An update to the distribution and treatment of vegetation and soil properties in SSiB. COLA Tech. Rep. 78, 25 pp.

  • Eltahir, E. A. B., , and Bras R. L. , 1996: Precipitation recycling. Rev. Geophys., 34 , 367378.

  • Essery, R. L. H., , Best M. J. , , Betts R. A. , , Cox P. M. , , and Taylor C. M. , 2003: Explicit representation of subgrid heterogeneity in a GCM land surface scheme. J. Hydrometeor., 4 , 530543.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • GFDL Global Atmospheric Model Development Team, 2004: The new GFDL global atmosphere and land model AM2–LM2: Evaluation with prescribed SST simulations. J. Climate, 17 , 46414673.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gleckler, P., and Ed., 1996: AMIP II guidelines. AMIP Newsletter, Vol. 8, PCMDI, Lawrence Livermore National Laboratory, Livermore, 20 pp.

  • Guo, Z-C., and Coauthors, 2006: GLACE: The Global Land–Atmosphere Coupling Experiment. Part II: Analysis. J. Hydrometeor., 7 , 611625.

  • Hahmann, A. N., , and Dickinson R. E. , 1997: RCCM2-BATS model over tropical South America: Applications to tropical deforestation. J. Climate, 10 , 19441963.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Henderson-Sellers, A., , and Gornitz V. , 1984: Possible climatic impacts of land cover transformations, with particular emphasis on tropical deforestation. Climatic Change, 6 , 231258.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., , Adler R. F. , , Chang A. , , Ferraro R. , , Gruber A. , , McNab A. , , Rudolf B. , , and Schneider U. , 1997: The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset. Bull. Amer. Meteor. Soc., 78 , 520.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77 , 437471.

  • Kinter, J. L., and Coauthors, 1997: The COLA atmosphere-biosphere general circulation model. Volume 1: Formulation. COLA Tech. Rep. 51, 46 pp.

  • Koster, R., , and Suarez M. , 1996: Energy and water balance calculations in the mosaic LSM. NASA Tech. Memo. 104606, Vol. 9, 59 pp.

  • Koster, R. D., , and Suarez M. J. , 2001: Soil moisture memory in climate models. J. Hydrometeor., 2 , 558570.

  • Koster, R. D., , and Suarez M. J. , 2004: Suggestions in the observational record of land–atmosphere feedback operating at seasonal time scales. J. Hydrometeor., 5 , 567572.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koster, R. D., , Dirmeyer P. A. , , Hahmann A. N. , , Ijpelaar R. , , Tyahla L. , , Cox P. , , and Suarez M. J. , 2002: Comparing the degree of land–atmosphere interaction in four atmospheric general circulation models. J. Hydrometeor., 3 , 363375.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koster, R. D., , Suarez M. J. , , Higgins R. W. , , and Van den Dool H. M. , 2003: Observational evidence that soil moisture variations affect precipitation. Geophys. Res. Lett., 30 .1241, doi:10.1029/2002GL016571.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and Coauthors, 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305 , 11381140.

  • Kowalczyk, E. A., , Garratt J. R. , , and Krummel P. B. , 1994: Implementation of a soil-canopy scheme into the CSIRO GCM—Regional aspects of the model response. CSIRO Atmospheric Research Tech. Paper 32. , 59 pp.

    • Search Google Scholar
    • Export Citation
  • Lau, K-M., , and Bua W. , 1998: Mechanisms of monsoon-Southern Oscillation coupling, insights from GCM experiments. Climate Dyn., 14 , 759779.

  • McFarlane, N. A., , Boer G. J. , , Blanchet J-P. , , and Lazare M. , 1992: The Canadian Climate Centre second-generation general circulation model and its equilibrium climate. J. Climate, 5 , 10131044.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McGregor, J. L., 1996: Semi-Lagrangian advection on conformal-cubic grids. Mon. Wea. Rev., 124 , 13111322.

  • McGregor, J. L., , and Dix M. R. , 2001: The CSIRO conformal-cubic atmospheric GCM. IUTAM Symposium on Advances in Mathematical Modeling of Atmosphere and Ocean Dynamics, P. F. Hodnett, Ed., Kluwer, 197–202.

    • Search Google Scholar
    • Export Citation
  • Milly, P. C. D., , and Shmakin A. B. , 2002: Global modeling of land water and energy balances. Part I: The Land Dynamics (LaD) model. J. Hydrometeor., 3 , 283299.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mocko, D. M., , and Sud Y. C. , 2001: Refinements to SSiB with an emphasis on snow-physics: Evaluation and validation with GSWP and Valdai data. Earth Interactions, 5 .[Available online at http://EarthInteractions.org.].

    • Search Google Scholar
    • Export Citation
  • Moorthi, S., , Pan H-L. , , and Caplan P. , 2001: Changes to the 2001 NCEP operational MRF/AVN Global Analysis/Forecast System. National Weather Service Office of Meteorology Technical Procedures Bulletin 484, 14 pp.

  • Nozawa, T., , Emori S. , , Numaguti A. , , Tsushima Y. , , Takemura T. , , Nakajima T. , , Abe-Ouchi A. , , and Kimoto M. , 2001: Projections of future climate change in the 21st century simulated by the CCSR/NIES CGCM under the IPCC SRES scenarios. Present and Future of Modeling Global Environmental Change: Toward Integrated Modeling, T. Matsuno and H. Kida, Eds., TERRAPUB, 15–28.

    • Search Google Scholar
    • Export Citation
  • Numaguti, A., 1993: Dynamics and energy balance of the Hadley circulation and the tropical precipitation zones: Significance of the distribution of evaporation. J. Atmos. Sci., 50 , 18741887.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Numaguti, A., , Takahashi M. , , Nakajima T. , , and Sumi A. , 1997: Description of CCSR/NIES Atmospheric General Circulation Model. CGER’s Supercomputer Monograph Report, 3, NIES, 1–48.

    • Search Google Scholar
    • Export Citation
  • Oglesby, R. J., , and Erickson D. J. III, 1989: Soil moisture and the persistence of North American drought. J. Climate, 2 , 13621380.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oleson, K. W., and Coauthors, 2004: Technical description of the Community Land Model (CLM). NCAR Tech. Note NCAR/TN-461+STR, 173 pp. [Available online at http://www.cgd.ucar.edu/tss/clm/distribution/clm3.0/TechNote/CLM_Tech_Note.pdf.].

  • Pan, H. L., , and Mahrt L. , 1987: Interaction between soil hydrology and boundary layer development. Bound.-Layer Meteor., 38 , 185202.

  • Pope, V. D., , Gallani M. L. , , Rowntree P. R. , , and Stratton R. A. , 2000: The impact of new physical parameterizations in the Hadley Centre climate model: HadAM3. Climate Dyn., 16 , 123146.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reale, O., , Dirmeyer P. A. , , and Schlosser C. A. , 2002: Modeling the effect of land surface evaporation variability on precipitation variability. Part II: Time- and space-scale structure. J. Hydrometeor., 3 , 451466.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shukla, J., , and Mintz Y. , 1982: Influence of land-surface evapotranspiration on the earth’s climate. Science, 215 , 14981501.

  • Sud, Y. C., , and Walker G. K. , 1999a: Microphysics of Clouds with the Relaxed Arakawa–Schubert Cumulus Scheme (McRAS). Part I: Design and evaluation with GATE Phase III data. J. Atmos. Sci., 56 , 31963220.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sud, Y. C., , and Walker G. K. , 1999b: Microphysics of Clouds with the Relaxed Arakawa–Schubert Cumulus Scheme (McRAS). Part II: Implementation and performance in GEOS II GCM. J. Atmos. Sci., 56 , 32213240.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., 1999: Atmospheric moisture recycling: Role of advection and local evaporation. J. Climate, 12 , 13681381.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Verseghy, D. L., 1991: CLASS—A Canadian land surface scheme for GCMs. I. Soil model. Int. J. Climatol., 11 , 111133.

  • Verseghy, D. L., 2000: The Canadian land surface scheme (CLASS): Its history and future. Atmos.–Ocean, 38 , 113.

  • Verseghy, D. L., , McFarlane N. A. , , and Lazare M. , 1993: CLASS—A Canadian land surface scheme for GCMs, II, Vegetation model and coupled runs. Int. J. Climatol., 13 , 347370.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xue, Y., , Sellers P. J. , , Kinter J. L. , , and Shukla J. , 1991: A simplified biosphere model for global climate studies. J. Climate, 4 , 345364.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xue, Y., , Zeng F. J. , , Mitchell K. E. , , Janjic Z. , , and Rogers E. , 2001: The impact of land surface processes on the simulation of the U.S. hydrological cycle: A case study of the 1993 flood using the SSiB land surface model in the NCEP Eta regional model. Mon. Wea. Rev., 129 , 28332860.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xue, Y., , Juang H-M. H. , , Li W-P. , , Prince S. , , DeFries R. , , Jiao Y. , , and Vasic R. , 2004: Role of land surface processes in monsoon development: East Asia and West Africa. J. Geophys. Res., 109 .D03105, doi:10.1029/2003JD003556.

    • Search Google Scholar
    • Export Citation
  • Zhong, A., , Coleman R. , , Smith N. , , Naughton M. , , Rikus L. , , Puri K. , , and Tseitkin F. , 2001: Ten-year AMIP 1 climatologies from versions of the BMRC Atmospheric Model. Bureau of Meteorology BMRC Research Rep. 83, 34 pp.

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GLACE: The Global Land–Atmosphere Coupling Experiment. Part I: Overview

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  • 1 NASA Goddard Space Flight Center, Greenbelt, Maryland
  • | 2 Center for Ocean–Land–Atmosphere Studies, Calverton, Maryland
  • | 3 National Center for Atmospheric Research, Boulder, Colorado
  • | 4 Meteorological Service of Canada, Toronto, Ontario, Canada
  • | 5 Centre for Ecology and Hydrology, Dorset, Dorset, United Kingdom
  • | 6 CSIRO Atmospheric Research, Aspendale, Victoria, Australia
  • | 7 Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey
  • | 8 Research Institute for Humanity and Nature, Kyoto, Japan
  • | 9 University of Reading, Reading, Berkshire, United Kingdom
  • | 10 Science Applications International Corporation, Beltsville, Maryland
  • | 11 National Centers for Environmental Prediction, Camp Springs, Maryland
  • | 12 Princeton University, Princeton, New Jersey
  • | 13 Bureau of Meteorology Research Centre, Melbourne, Victoria, Australia
  • | 14 University of Tokyo, Tokyo, Japan
  • | 15 Macquarie University, North Ryde, New South Wales, Australia
  • | 16 Centre for Ecology and Hydrology, Wallingford, Oxfordshire, United Kingdom
  • | 17 University of California, Los Angeles, Los Angeles, California
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Abstract

The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detail so that any interested modeling group can repeat them easily and thereby place their model’s coupling strength within the broad range of those documented here.

Corresponding author address: Randal Koster, NASA GFSC, Code 610.1, Greenbelt, MD 20771. Email: randal.d.koster@nasa.gov

Abstract

The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detail so that any interested modeling group can repeat them easily and thereby place their model’s coupling strength within the broad range of those documented here.

Corresponding author address: Randal Koster, NASA GFSC, Code 610.1, Greenbelt, MD 20771. Email: randal.d.koster@nasa.gov

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