Editorial Type:
Article
Article Type:
Research Article

Explicit Representation of Spatial Subgrid-Scale Heterogeneity in an ESM

Philipp de Vrese Max Planck Institute for Meteorology, Hamburg, Germany

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Stefan Hagemann Max Planck Institute for Meteorology, Hamburg, Germany

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Print Publication:
01 May 2016
DOI:
https://doi.org/10.1175/JHM-D-15-0080.1
Page(s):
1357–1371
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Abstract

In present-day Earth system models, the coupling of land surface and atmosphere is based on simplistic assumptions. Often the heterogeneous land surface is represented by a set of effective parameters valid for an entire model grid box. Other models assume that the surface fluxes become horizontally homogeneous at the lowest atmospheric model level. For heterogeneity above a certain horizontal length scale this is not the case, resulting in spatial subgrid-scale variability in the fluxes and in the state of the atmosphere. The Max Planck Institute for Meteorology’s Earth System Model is used with three different coupling schemes to assess the importance of the representation of spatial heterogeneity at the land surface as well as within the atmosphere. Simulations show that the land surface–atmosphere coupling distinctly influences the simulated near-surface processes with respect to different land-cover types. The representation of heterogeneity also has a distinct impact on the simulated gridbox mean state and fluxes in a large fraction of land surface.

Corresponding author address: Philipp de Vrese, Max Planck Institute for Meteorology, Bundesstrasse 53, 20146 Hamburg, Germany. E-mail: philipp.de-vrese@mpimet.mpg.de

Abstract

In present-day Earth system models, the coupling of land surface and atmosphere is based on simplistic assumptions. Often the heterogeneous land surface is represented by a set of effective parameters valid for an entire model grid box. Other models assume that the surface fluxes become horizontally homogeneous at the lowest atmospheric model level. For heterogeneity above a certain horizontal length scale this is not the case, resulting in spatial subgrid-scale variability in the fluxes and in the state of the atmosphere. The Max Planck Institute for Meteorology’s Earth System Model is used with three different coupling schemes to assess the importance of the representation of spatial heterogeneity at the land surface as well as within the atmosphere. Simulations show that the land surface–atmosphere coupling distinctly influences the simulated near-surface processes with respect to different land-cover types. The representation of heterogeneity also has a distinct impact on the simulated gridbox mean state and fluxes in a large fraction of land surface.

Corresponding author address: Philipp de Vrese, Max Planck Institute for Meteorology, Bundesstrasse 53, 20146 Hamburg, Germany. E-mail: philipp.de-vrese@mpimet.mpg.de
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  • Ament, F., and Simmer C. , 2006: Improved representation of land-surface heterogeneity in a non-hydrostatic numerical weather prediction model. Bound.-Layer Meteor., 121, 153–174, doi:10.1007/s10546-006-9066-4.

    • Search Google Scholar
    • Export Citation

  • Arino, O., Ramos Perez J. J. , Kalogirou V. , Bontemps S. , Defourny P. , and Van Bogaert E. , 2012: Global Land Cover Map for 2009 (GlobCover 2009). Pangaea, accessed 15 March 2016, doi:10.1594/PANGAEA.787668.

  • Arola, A., 1999: Parameterization of turbulent and mesoscale fluxes for heterogeneous surfaces. J. Atmos. Sci., 56, 584–598, doi:10.1175/1520-0469(1999)056<0584:POTAMF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Avissar, R., and Pielke R. A. , 1989: A parameterization of heterogeneous land surfaces for atmospheric numerical models and its impact on regional meteorology. Mon. Wea. Rev., 117, 2113–2136, doi:10.1175/1520-0493(1989)117<2113:APOHLS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Avissar, R., and Schmidt T. , 1998: An evaluation of the scale at which ground-surface heat flux patchiness affects the convective boundary layer using large-eddy simulations. J. Atmos. Sci., 55, 2666–2689, doi:10.1175/1520-0469(1998)055<2666:AEOTSA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Best, M. J., Beljaars A. , Polcher J. , and Viterbo P. , 2004: A proposed structure for coupling tiled surfaces with the planetary boundary layer. J. Hydrometeor., 5, 1271–1278, doi:10.1175/JHM-382.1.

    • Search Google Scholar
    • Export Citation

  • Bou-Zeid, E., Meneveau C. , and Parlange M. B. , 2004: Large-eddy simulation of neutral atmospheric boundary layer flow over heterogeneous surfaces: Blending height and effective surface roughness. Water Resour. Res., 40, W02505, doi:10.1029/2003WR002475.

    • Search Google Scholar
    • Export Citation

  • Brinkop, S., and Roeckner E. , 1995: Sensitivity of a general circulation model to parameterizations of cloud–turbulence interactions in the atmospheric boundary layer. Tellus, 47A, 197–220, doi:10.1034/j.1600-0870.1995.t01-1-00004.x.

    • Search Google Scholar
    • Export Citation

  • Brovkin, V., Raddatz T. , Reick C. H. , Claussen M. , and Gayler V. , 2009: Global biogeophysical interactions between forest and climate. Geophys. Res. Lett., 36, L07405, doi:10.1029/2009GL037543.

    • Search Google Scholar
    • Export Citation

  • Claussen, M., 1991: Estimation of areally-averaged surface fluxes. Bound.-Layer Meteor., 54, 387–410, doi:10.1007/BF00118868.

  • Claussen, M., 1995: Flux aggregation at large scales: On the limits of validity of the concept of blending height. J. Hydrol., 166, 371–382, doi:10.1016/0022-1694(94)05098-I.

    • Search Google Scholar
    • Export Citation

  • Claussen, M., Lohmann U. , Roeckner E. , and Schulzweida U. , 1994: A global dataset of land surface parameters. MPI Rep. 135, Max-Planck-Institute for Meteorology, 35 pp.

  • Cooper, H. J., Smith E. A. , Gu J. , and Shewchuk S. , 1997: Modeling the impact of averaging on aggregation of surface fluxes over BOREAS. J. Geophys. Res., 102, 29 235–29 253, doi:10.1029/97JD00456.

    • Search Google Scholar
    • Export Citation

  • de Vrese, P., Schulz J.-P. , and Hagemann S. , 2016: On the representation of heterogeneity in land-surface–atmosphere coupling. Bound.-Layer Meteor., doi:10.1007/s10546-016-0133-1, in press.

  • Dimri, A., 2009: Impact of subgrid scale scheme on topography and landuse for better regional scale simulation of meteorological variables over the western Himalayas. Climate Dyn., 32, 565–574, doi:10.1007/s00382-008-0453-z.

    • Search Google Scholar
    • Export Citation

  • Ekici, A., Beer C. , Hagemann S. , Boike J. , Langer M. , and Hauck C. , 2014: Simulating high-latitude permafrost regions by the JSBACH terrestrial ecosystem model. Geosci. Model Dev., 7, 631–647, doi:10.5194/gmd-7-631-2014.

    • Search Google Scholar
    • Export Citation

  • Essery, R., Best M. J. , Betts R. A. , and Taylor C. M. , 2003: Explicit representation of subgrid heterogeneity in a GCM land surface scheme. J. Hydrometeor., 4, 530–543, doi:10.1175/1525-7541(2003)004<0530:EROSHI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Feddes, R. A., Kabat P. , Doman A. J. , Hutjes R. W. A. , and Waterloo M. J. , 1998: Large-scale field experiments to improve land surface parameterisations. Proc. Second Int. Conf. on Climate and Water, Espoo, Finland, WMO/UNESCO, 619–647.

  • Fekete, B. M., Vörösmarty C. J. , Roads J. O. , and Willmott C. J. , 2004: Uncertainties in precipitation and their impacts on runoff estimates. J. Climate, 17, 294–304, doi:10.1175/1520-0442(2004)017<0294:UIPATI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Gates, W. L., and Coauthors, 1999: An overview of the results of the Atmospheric Model Intercomparison Project (AMIP I). Bull. Amer. Meteor. Soc., 80, 29–55, doi:10.1175/1520-0477(1999)080<0029:AOOTRO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Giorgetta, M. A., and Coauthors, 2013: The atmospheric general circulation model ECHAM6: Model description. MPI Rep. on Earth System Science 135, Max-Planck-Institute for Meteorology, 172 pp. [Available online at https://www.mpimet.mpg.de/fileadmin/publikationen/Reports/WEB_BzE_135.pdf.]

  • Giorgi, F., and Avissar R. , 1997: Representation of heterogeneity effects in earth system modeling: Experience from land surface modeling. Rev. Geophys., 35, 413–437, doi:10.1029/97RG01754.

    • Search Google Scholar
    • Export Citation

  • 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. J. Hydrometeor., 4, 317–333, doi:10.1175/1525-7541(2003)4<317:EOASTA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Guillod, B. P., Orlowsky B. , Miralles D. G. , Teuling A. J. , and Seneviratne S. I. , 2015: Reconciling spatial and temporal soil moisture effects on afternoon rainfall. Nat. Commun., 6, 6443, doi:10.1038/ncomms7443.

    • Search Google Scholar
    • Export Citation

  • Hagemann, S., Loew A. , and Andersson A. , 2013: Combined evaluation of MPI-ESM land surface water and energy fluxes. J. Adv. Model. Earth Syst., 5, 259–286, doi:10.1029/2012MS20008.

    • Search Google Scholar
    • Export Citation

  • Heinemann, G., and Kerschgens M. , 2005: Comparison of methods for area-averaging surface energy fluxes over heterogeneous land surfaces using high-resolution non-hydrostatic simulations. Int. J. Climatol., 25, 379–403, doi:10.1002/joc.1123.

    • Search Google Scholar
    • Export Citation

  • Kabat, P., Hutjes R. , and Feddes R. , 1997: The scaling characteristics of soil parameters: From plot scale heterogeneity to subgrid parameterization. J. Hydrol., 190, 363–396, doi:10.1016/S0022-1694(96)03134-4.

    • Search Google Scholar
    • Export Citation

  • Koster, R. D., 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305, 1138–1140, doi:10.1126/science.1100217.

    • Search Google Scholar
    • Export Citation

  • Koster, R. D., and Suarez M. J. , 1992: A comparative analysis of two land surface heterogeneity representations. J. Climate, 5, 1379–1390, doi:10.1175/1520-0442(1992)005<1379:ACAOTL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Ma, Y., Menenti M. , Feddes R. , and Wang J. , 2008: Analysis of the land surface heterogeneity and its impact on atmospheric variables and the aerodynamic and thermodynamic roughness lengths. J. Geophys. Res., 113, D08113, doi:10.1029/2007JD009124.

    • Search Google Scholar
    • Export Citation

  • Mahrt, L., 2000: Surface heterogeneity and vertical structure of the boundary layer. Bound.-Layer Meteor., 96, 33–62, doi:10.1023/A:1002482332477.

    • Search Google Scholar
    • Export Citation

  • Mahrt, L., and Sun J. , 1995: Dependence of surface exchange coefficients on averaging scale and grid size. Quart. J. Roy. Meteor. Soc., 121, 1835–1852, doi:10.1002/qj.49712152803.

    • Search Google Scholar
    • Export Citation

  • Manrique-Suñén, A., Nordbo A. , Balsamo G. , Beljaars A. , and Mammarella I. , 2013: Representing land surface heterogeneity: Offline analysis of the tiling method. J. Hydrometeor., 14, 850–867, doi:10.1175/JHM-D-12-0108.1.

    • Search Google Scholar
    • Export Citation

  • Mason, P. J., 1988: The formation of areally-averaged roughness lengths. Quart. J. Roy. Meteor. Soc., 114, 399–420, doi:10.1002/qj.49711448007.

    • Search Google Scholar
    • Export Citation

  • Molod, A., and Salmun H. , 2002: A global assessment of the mosaic approach to modeling land surface heterogeneity. J. Geophys. Res., 107, 4217, doi:10.1029/2001JD000588.

    • Search Google Scholar
    • Export Citation

  • Molod, A., Salmun H. , and Waugh D. W. , 2004: The impact on a GCM climate of an extended mosaic technique for the land–atmosphere coupling. J. Climate, 17, 3877–3891, doi:10.1175/1520-0442(2004)017<3877:TIOAGC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Otto, J., Raddatz T. , and Claussen M. , 2011: Strength of forest–albedo feedback in mid-Holocene climate simulations. Climate Past, 7, 1027–1039, doi:10.5194/cp-7-1027-2011.

    • Search Google Scholar
    • Export Citation

  • Patton, E. G., Sullivan P. P. , and Moeng C.-H. , 2005: The influence of idealized heterogeneity on wet and dry planetary boundary layers coupled to the land surface. J. Atmos. Sci., 62, 2078–2097, doi:10.1175/JAS3465.1.

    • Search Google Scholar
    • Export Citation

  • Polcher, J., Laval K. , Dümenil L. , Lean J. , and Rowntree P. , 1996: Comparing three land surface schemes used in general circulation models. J. Hydrol., 180, 373–394, doi:10.1016/0022-1694(95)02886-2.

    • Search Google Scholar
    • Export Citation

  • Polcher, J., and Coauthors, 1998: A proposal for a general interface between land surface schemes and general circulation models. Global Planet. Change, 19, 261–276, doi:10.1016/S0921-8181(98)00052-6.

    • Search Google Scholar
    • Export Citation

  • Raddatz, T., and Coauthors, 2007: Will the tropical land biosphere dominate the climate–carbon cycle feedback during the twenty-first century? Climate Dyn., 29, 565–574, doi:10.1007/s00382-007-0247-8.

    • Search Google Scholar
    • Export Citation

  • Raupach, M., and Finnigan J. , 1995: Scale issues in boundary-layer meteorology: Surface energy balances in heterogeneous terrain. Hydrol. Processes, 9, 589–612, doi:10.1002/hyp.3360090509.

    • Search Google Scholar
    • Export Citation

  • Rieck, M., Hohenegger C. , and van Heerwaarden C. C. , 2014: The influence of land surface heterogeneities on cloud size development. Mon. Wea. Rev., 142, 3830–3846, doi:10.1175/MWR-D-13-00354.1.

    • Search Google Scholar
    • Export Citation

  • Salmun, H., Molod A. , and Ira A. , 2007: Observational validation of an extended mosaic technique for capturing subgrid scale heterogeneity in a GCM. Tellus, 59B, 625–632, doi:10.1111/j.1600-0889.2007.00257.x.

    • Search Google Scholar
    • Export Citation

  • Schomburg, A., Venema V. , Ament F. , and Simmer C. , 2012: Disaggregation of screen-level variables in a numerical weather prediction model with an explicit simulation of subgrid-scale land-surface heterogeneity. Meteor. Atmos. Phys., 116, 81–94, doi:10.1007/s00703-012-0183-y.

    • Search Google Scholar
    • Export Citation

  • Sellers, P., 1991: Modeling and observing land-surface–atmosphere interactions on large scales. Surv. Geophys., 12, 85–114, doi:10.1007/BF01903413.

    • Search Google Scholar
    • Export Citation

  • Seth, A., Giorgi F. , and Dickinson R. E. , 1994: Simulating fluxes from heterogeneous land surfaces: Explicit subgrid method employing the Biosphere–Atmosphere Transfer Scheme (BATS). J. Geophys. Res., 99, 18 651–18 667, doi:10.1029/94JD01330.

    • Search Google Scholar
    • Export Citation

  • Stevens, B., and Coauthors, 2013: Atmospheric component of the MPI-M Earth System Model: ECHAM6. J. Adv. Model. Earth Syst., 5, 146–172, doi:10.1002/jame.20015.

    • Search Google Scholar
    • Export Citation

  • van den Hurk, B., and Beljaars A. , 1996: Impact of some simplifying assumptions in the new ECMWF surface scheme. J. Appl. Meteor., 35, 1333–1343, doi:10.1175/1520-0450(1996)035<1333:IOSSAI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Weedon, G. P., and Coauthors, 2011: Creation of the WATCH Forcing Data and its use to assess global and regional reference crop evaporation over land during the twentieth century. J. Hydrometeor., 12, 823–848, doi:10.1175/2011JHM1369.1.

    • Search Google Scholar
    • Export Citation
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