Evaluating Soil Water Content in a WRF-Noah Downscaling Experiment

Peter Greve Institute of Physics and Meteorology, University of Hohenheim, Stuttgart, Germany

Search for other papers by Peter Greve in
Current site
Google Scholar
PubMed
Close
,
Kirsten Warrach-Sagi Institute of Physics and Meteorology, University of Hohenheim, Stuttgart, Germany

Search for other papers by Kirsten Warrach-Sagi in
Current site
Google Scholar
PubMed
Close
, and
Volker Wulfmeyer Institute of Physics and Meteorology, University of Hohenheim, Stuttgart, Germany

Search for other papers by Volker Wulfmeyer in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Soil water content (SWC) depends on and affects the energy flux partitioning at the land–atmosphere interface. Above all, the latent heat flux is limited by the SWC of the root zone on one hand and radiation on the other. Therefore, SWC is a key variable in the climate system. In this study, the performance of the Weather Research and Forecasting model coupled with the Noah land surface model (WRF-Noah) system in a climate hindcast simulation from 1990 to 2008 is evaluated with respect to SWC versus two reanalysis datasets for Europe during 2007 and 2008 with in situ soil moisture observations from southern France. When compared with the in situ observations, WRF-Noah generally reproduces the SWC annual cycle while the reanalysis SWCs do not. The biases in areal mean WRF-Noah SWCs relate to biases in precipitation and evapotranspiration in a cropland environment. The spatial patterns and temporal variability of the seasonal mean SWCs from the WRF-Noah simulations and from the two reanalyses correspond well, while absolute values differ significantly, especially at the regional scale.

Denotes Open Access content.

Current affiliation: Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland.

Corresponding author address: Peter Greve, Institute for Atmospheric and Climate Science, ETH Zürich, Universitätsstrasse 16, Zürich 8092, Switzerland. E-mail: peter.greve@env.ethz.ch

Abstract

Soil water content (SWC) depends on and affects the energy flux partitioning at the land–atmosphere interface. Above all, the latent heat flux is limited by the SWC of the root zone on one hand and radiation on the other. Therefore, SWC is a key variable in the climate system. In this study, the performance of the Weather Research and Forecasting model coupled with the Noah land surface model (WRF-Noah) system in a climate hindcast simulation from 1990 to 2008 is evaluated with respect to SWC versus two reanalysis datasets for Europe during 2007 and 2008 with in situ soil moisture observations from southern France. When compared with the in situ observations, WRF-Noah generally reproduces the SWC annual cycle while the reanalysis SWCs do not. The biases in areal mean WRF-Noah SWCs relate to biases in precipitation and evapotranspiration in a cropland environment. The spatial patterns and temporal variability of the seasonal mean SWCs from the WRF-Noah simulations and from the two reanalyses correspond well, while absolute values differ significantly, especially at the regional scale.

Denotes Open Access content.

Current affiliation: Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland.

Corresponding author address: Peter Greve, Institute for Atmospheric and Climate Science, ETH Zürich, Universitätsstrasse 16, Zürich 8092, Switzerland. E-mail: peter.greve@env.ethz.ch
Save
  • Albergel, C., and Coauthors, 2008: From near-surface to root-zone soil moisture using an exponential filter: An assessment of the method based on in-situ observations and model simulations. Hydrol. Earth Syst. Sci. Discuss., 5, 16031640, doi:10.5194/hessd-5-1603-2008.

    • Search Google Scholar
    • Export Citation
  • Alfieri, L., P. Claps, P. D'Odorico, F. Laio, and T. Over, 2008: An analysis of the soil moisture feedback on convective and stratiform precipitation. J. Hydrometeor., 9, 280291.

    • Search Google Scholar
    • Export Citation
  • Barthlott, C., C. Hauck, G. Schädler, N. Kalthoff, and C. Kottmeier, 2011: Soil moisture impacts on convective indices and precipitation over complex terrain. Meteor. Z., 20, 185197, doi:10.1127/0941-2948/2011/0216.

    • Search Google Scholar
    • Export Citation
  • Beljaars, A., M. Miller, and P. Viterbo, 1996: The land surface–atmosphere interaction: A review based on observational and global modeling perspectives. J. Geophys. Res., 101, 72097225.

    • Search Google Scholar
    • Export Citation
  • Beniston, M., 2004: The 2003 heat wave in Europe: A shape of things to come? An analysis based on Swiss climatological data and model simulations. Geophys. Res. Lett.,31, L02202, doi:10.1029/2003GL018857.

  • Black, E., M. Blackburn, G. Harrison, B. Hoskins, and J. Methven, 2004: Factors contributing to the summer 2003 European heatwave. Weather, 59, 217223, doi:10.1256/wea.74.04.

    • Search Google Scholar
    • Export Citation
  • Calvet, J., N. Fritz, F. Froissard, D. Suquia, A. Petitpa, and B. Piguet, 2007: In situ soil moisture observations for the CAL/VAL of SMOS: The SMOSMANIA network. Proc. Int. Geoscience and Remote Sensing Symp., Barcelona, Spain, IEEE, 1196–1199.

  • Chen, F., and J. Dudhia, 2001: Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569585.

    • Search Google Scholar
    • Export Citation
  • Clark, R., S. Brown, and J. Murphy, 2006: Modeling Northern Hemisphere summer heat extreme changes and their uncertainties using a physics ensemble of climate sensitivity experiments. J. Climate, 19, 44184435.

    • Search Google Scholar
    • Export Citation
  • Collins, W., and Coauthors, 2004: Description of the NCAR Community Atmosphere Model (CAM 3.0). NCAR Tech. Note NCAR/TN-464+STR, 214 pp.

  • Decharme, B., 2007: Influence of runoff parameterization on continental hydrology: Comparison between the Noah and the ISBA land surface models. J. Geophys. Res.,112, D19108, doi:10.1029/2007JD008463.

  • Dee, D., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, doi:10.1002/qj.828.

    • Search Google Scholar
    • Export Citation
  • Ek, M., and L. Mahrt, 1994: Daytime evolution of relative humidity at the boundary layer top. Mon. Wea. Rev., 122, 27092721.

  • Ek, M., and A. Holtslag, 2004: Influence of soil moisture on boundary layer cloud development. J. Hydrometeor., 5, 8699.

  • Ek, M., K. E. Mitchell, Y. Lin, E. Rogers, P. Grunmann, V. Koren, G. Gayno, and J. D. Tarpley, 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta Model. J. Geophys. Res., 108, 8851, doi:10.1029/2002JD003296.

    • Search Google Scholar
    • Export Citation
  • Eltahir, E., 1998: A soil moisture–rainfall feedback mechanism. 1: Theory and observations. Water Resour. Res., 34, 765776.

  • Fan, Y., H. Van den Dool, D. Lohmann, and K. Mitchell, 2006: 1948–98 U.S. hydrological reanalysis by the Noah land data assimilation system. J. Climate, 19, 12141237.

    • Search Google Scholar
    • Export Citation
  • Findell, K., and E. Eltahir, 2003: Atmospheric controls on soil moisture-boundary layer interactions. Part I: Framework development. J. Hydrometeor.,4, 552–569.

  • Fischer, E., S. Seneviratne, P. Vidale, D. Lüthi, and C. Schär, 2007: Soil moisture–atmosphere interactions during the 2003 European summer heat wave. J. Climate, 20, 50815099.

    • Search Google Scholar
    • Export Citation
  • Gantner, L., and N. Kalthoff, 2010: Sensitivity of a modelled life cycle of a mesoscale convective system to soil conditions over West Africa. Quart. J. Roy. Meteor. Soc., 136 (S1), 471482, doi:10.1002/qj.425.

    • Search Google Scholar
    • Export Citation
  • Gayler, S., J. Ingwersen, E. Priesack, T. Wöhling, V. Wulfmeyer, and T. Streck, 2013: Assessing the relevance of subsurface processes for the simulation of evapotranspiration and soil moisture dynamics with CLM3.5: Comparison with field data and crop model simulations. Environ. Earth Sci., 69, 415427.

    • Search Google Scholar
    • Export Citation
  • Grathwohl, P., and Coauthors, 2013: Catchments as reactors: A comprehensive approach for water fluxes and solute turn-over. Environ. Earth Sci., 69, 317–333.

    • Search Google Scholar
    • Export Citation
  • Guillod, B., E. Davin, C. Kündig, G. Smiatek, and S. Seneviratne, 2013: Impact of soil map specifications for European climate simulations. Climate Dyn., 40, 123–141, doi:10.1007/s00382-012-1395-z.

    • Search Google Scholar
    • Export Citation
  • Hauck, C., C. Barthlott, L. Krauss, and N. Kalthoff, 2011: Soil moisture variability and its influence on convective precipitation over complex terrain. Quart. J. Roy. Meteor. Soc., 137, 4256, doi:10.1002/qj.766.

    • Search Google Scholar
    • Export Citation
  • Heerwaarden, C. V., J. V.-G. de Arellano, A. Moene, and A. Holtslag, 2009: Interactions between dry-air entrainment, surface evaporation and convective boundary-layer development. Quart. J. Roy. Meteor. Soc., 135, 12771291, doi:10.1002/qj.431.

    • Search Google Scholar
    • Export Citation
  • Heikkilä, U., A. Sandvik, and A. Sorteberg, 2011: Dynamical downscaling of ERA-40 in complex terrain using the WRF regional climate model. Climate Dyn., 37, 15511564.

    • Search Google Scholar
    • Export Citation
  • Hirschi, M., and Coauthors, 2010: Observational evidence for soil-moisture impact on hot extremes in southeastern Europe. Nat. Geosci., 4, 1721, doi:10.1038/ngeo1032.

    • Search Google Scholar
    • Export Citation
  • Hohenegger, C., P. Brockhaus, C. Bretherton, and C. Schär, 2009: The soil moisture–precipitation feedback in simulations with explicit and parameterized convection. J. Climate, 22, 50035020.

    • Search Google Scholar
    • Export Citation
  • Hong, S., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341.

    • Search Google Scholar
    • Export Citation
  • Hurrell, J., 1995: Decadal trends in the North Atlantic Oscillation: Regional temperatures and precipitation. Science, 269, 676679.

  • Hurrell, J., and H. van Loon, 1997: Decadal variations in climate associated with the North Atlantic Oscillation. Climatic Change, 36, 301326.

    • Search Google Scholar
    • Export Citation
  • Ingwersen, J., and Coauthors, 2011: Comparison of noah simulations with eddy covariance and soil water measurements at a winter wheat stand. Agric. For. Meteor., 151, 345355, doi:10.1016/j.agrformet.2010.11.010.

    • Search Google Scholar
    • Export Citation
  • Kain, J., 2004: The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170181.

  • Kalinka, F., and B. Ahrens, 2011: A modification of the mixed form of Richards equation and its application in vertically inhomogeneous soils. Adv. Sci. Res., 6, 123127, doi:10.5194/asr-6-123-2011.

    • Search Google Scholar
    • Export Citation
  • Kalthoff, N., and Coauthors, 2011: The dependence of convection-related parameters on surface and boundary-layer conditions over complex terrain. Quart. J. Roy. Meteor. Soc., 137, 7080, doi:10.1002/qj.686.

    • Search Google Scholar
    • Export Citation
  • Keenlyside, N., M. Latif, J. Jungclaus, L. Kornblueh, and E. Roeckner, 2008: Advancing decadal-scale climate prediction in the North Atlantic sector. Nature, 453, 8488, doi:10.1038/nature06921.

    • Search Google Scholar
    • Export Citation
  • Koster, R., and Coauthors, 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305, 11381140, doi:10.1126/science.1100217.

    • Search Google Scholar
    • Export Citation
  • Koster, R., Z. Guo, R. Yang, P. Dirmeyer, K. Mitchell, and M. Puma, 2009: On the nature of soil moisture in land surface models. J. Climate, 22, 43224335.

    • Search Google Scholar
    • Export Citation
  • Lorenz, R., E. Jaeger, and S. Seneviratne, 2010: Persistence of heat waves and its link to soil moisture memory. Geophys. Res. Lett.,37, L09703, doi:10.1029/2010GL042764.

  • Mahfouf, J., P. Viterbo, H. Douville, A. Beljaars, and S. Saarinen, 2000: A revised land-surface analysis scheme in the integrated forecasting system. ECMWF Newsletter, No. 88, ECMWF, Reading, United Kingdom, 8–13.

  • Mahrt, L., and M. Ek, 1984: The influence of atmospheric stability on potential evaporation. J. Climate Appl. Meteor., 23, 222234.

  • Manabe, S., and K. Bryan, 1969: Climate calculations with a combined ocean–atmosphere model. J. Atmos. Sci., 26, 786789.

  • Maxwell, R., and N. Miller, 2005: Development of a coupled land surface and groundwater model. J. Hydrometeor., 6, 233247.

  • Morrison, H., G. Thompson, and V. Tatarskii, 2009: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one-and two-moment schemes. Mon. Wea. Rev., 137, 9911007.

    • Search Google Scholar
    • Export Citation
  • Pauwels, V., and G. D. Lannoy, 2006: Improvement of modeled soil wetness conditions and turbulent fluxes through the assimilation of observed discharge. J. Hydrometeor., 7, 458477.

    • Search Google Scholar
    • Export Citation
  • Sanchez, P., and Coauthors, 2009: Digital soil map of the world. Science, 325, 680–681, doi:10.1126/science.1175084.

  • Santanello, J., M. Friedl, and M. Ek, 2007: Convective planetary boundary layer interactions with the land surface at diurnal time scales: Diagnostics and feedbacks. J. Hydrometeor., 8, 10821097.

    • Search Google Scholar
    • Export Citation
  • Schär, C., D. Lüthi, U. Beyerle, and E. Heise, 1999: The soil–precipitation feedback: A process study with a regional climate model. J. Climate, 12, 722741.

    • Search Google Scholar
    • Export Citation
  • Schwitalla, T., H. Bauer, V. Wulfmeyer, and F. Aoshima, 2011: High-resolution simulation over central Europe: Assimilation experiments during COPS IOP 9C. Quart. J. Roy. Meteor. Soc., 137 (S1), 156175, doi:10.1002/qj.721.

    • Search Google Scholar
    • Export Citation
  • Sellers, P., and Coauthors, 1997: Modeling the exchanges of energy, water, and carbon between continents and the atmosphere. Science, 275, 502–509, doi:10.1126/science.275.5299.502.

    • Search Google Scholar
    • Export Citation
  • Seneviratne, S., D. Lüthi, M. Litschi, and C. Schär, 2006: Land–atmosphere coupling and climate change in Europe. Nature, 443, 205209, doi:10.1038/nature05095.

    • Search Google Scholar
    • Export Citation
  • Seneviratne, S., T. Corti, E. Davin, M. Hirschi, E. Jaeger, I. Lehner, B. Orlowsky, and A. Teuling, 2010: Investigating soil moisture–climate interactions in a changing climate: A review. Earth Sci. Rev., 99, 125161, doi:10.1016/j.earscirev.2010.02.004.

    • Search Google Scholar
    • Export Citation
  • Shao, Y., and A. Henderson-Sellers, 1996: Modeling soil moisture: A Project for Intercomparison of Land Surface Parameterization Schemes phase 2(B). J. Geophys. Res., 101 (D3), 72277250.

    • Search Google Scholar
    • Export Citation
  • Shorthouse, C., and N. Arnell, 1999: The effects of climatic variability on spatial characteristics of European river flows. Phys. Chem. Earth, 24B, 713.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp.

  • Taylor, C., and R. Ellis, 2006: Satellite detection of soil moisture impacts on convection at the mesoscale. Geophys. Res. Lett.,33, L03404, doi:10.1029/2005GL025252.

  • Trigo, R., D. Pozo-Vázquez, T. Osborn, Y. Castro-Díez, S. Gámiz-Fortis, and M. Esteban-Parra, 2004: North Atlantic Oscillation influence on precipitation, river flow and water resources in the Iberian Peninsula. Int. J. Climatol., 24, 925944, doi:10.1002/joc.1048.

    • Search Google Scholar
    • Export Citation
  • Van den Dool, H., J. Huang, and Y. Fan, 2003: Performance and analysis of the constructed analogue method applied to U.S. soil moisture over 1981–2001. J. Geophys. Res.,108,8617, doi:10.1029/2002JD003114.

  • Visbeck, M., J. Hurrell, L. Polvani, and H. Cullen, 2001: The North Atlantic Oscillation: Past, present, and future. Proc. Natl. Acad. Sci. USA, 98, 12 876–12 877, doi:10.1073/pnas.231391598.

    • Search Google Scholar
    • Export Citation
  • Viterbo, P., and A. Beljaars, 1995: An improved land surface parameterization scheme in the ECMWF model and its validation. J. Climate, 8, 27162748.

    • Search Google Scholar
    • Export Citation
  • Warrach, K., H.-T. Mengelkamp, and E. Raschke, 2001: Treatment of frozen soil and snow cover in the land surface model SEWAB. Theor. Appl. Climatol., 69, 2337.

    • Search Google Scholar
    • Export Citation
  • Warrach-Sagi, K., and V. Wulfmeyer, 2010: Streamflow data assimilation for soil moisture analysis. Geosci. Model Dev., 3, 112, doi:10.5194/gmdd-2-551-2009.

    • Search Google Scholar
    • Export Citation
  • Warrach-Sagi, K., V. Wulfmeyer, R. Grasselt, F. Ament, and C. Simmer, 2008: Streamflow simulations reveal the impact of the soil parameterization. Meteor. Z., 17, 751762, doi:10.1127/0941-2948/2008/0343.

    • Search Google Scholar
    • Export Citation
  • Warrach-Sagi, K., T. Schwitalla, V. Wulfmeyer, and H.-S. Bauer, 2013: Evaluation of a simulation based on the WRF-Noah model system: Precipitation in Germany. Climate Dyn., 41, 755774.

    • Search Google Scholar
    • Export Citation
  • Wei, J., P. Dirmeyer, Z. Guo, L. Zhang, and V. Misra, 2010: How much do different land models matter for climate simulation? Part I: Climatology and variability. J. Climate, 23, 31203134.

    • Search Google Scholar
    • Export Citation
  • Wöhling, T., S. Gayler, J. Ingwersen, T. Streck, J. Vrugt, and E. Priesack, 2012: Multiobjective calibration of coupled soil-vegetation-atmosphere models. Proc. ModelCARE2011: Models—Repositories of Knowledge. S. E. Oswald, O. Kolditz, and S. Attinger, Eds. Publ. 255, IAHS, 357–364.

  • Wood, E., and Coauthors, 1998: The Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) Phase 2(c) Red–Arkansas River basin experiment: 1. Experiment description and summary intercomparisons. Global Planet. Change, 19, 115135, doi:10.1016/S0921-8181(98)00044-7.

    • Search Google Scholar
    • Export Citation
  • Wulfmeyer, V., and Coauthors, 2011: The Convective and Orographically-induced Precipitation Study (COPS): The scientific strategy, the field phase, and research highlights. Quart. J. Roy. Meteor. Soc., 137 (S1), 330, doi:10.1002/qj.752.

    • Search Google Scholar
    • Export Citation
  • Yeh, T., R. Wetherald, and S. Manabe, 1984: The effect of soil moisture on the short-term climate and hydrology change—A numerical experiment. Mon. Wea. Rev., 112, 474490.

    • Search Google Scholar
    • Export Citation
  • Zeng, X., and M. Decker, 2009: Improving the numerical solution of soil moisture–based Richards equation for land models with a deep or shallow water table. J. Hydrometeor., 10, 308319.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1643 798 252
PDF Downloads 587 54 12