Impacts of Soil Heating Condition on Precipitation Simulations in the Weather Research and Forecasting Model

Xingang Fan Geosystems Research Institute, Mississippi State University, Starkville, Mississippi

Search for other papers by Xingang Fan in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Soil temperature is a major variable in land surface models, representing soil energy status, storage, and transfer. It serves as an important factor indicating the underlying surface heating condition for weather and climate forecasts. This study utilizes the Weather Research and Forecasting (WRF) model to study the impacts of changes to the surface heating condition, derived from soil temperature observations, on regional weather simulations. Large cold biases are found in the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis project (ERA-40) soil temperatures as compared to observations. At the same time, a warm bias is found in the lower boundary assumption adopted by the Noah land surface model. In six heavy rain cases studied herein, observed soil temperatures are used to initialize the land surface model and to provide a lower boundary condition at the bottom of the model soil layer. By analyzing the impacts from the incorporation of observed soil temperatures, the following major conclusions are drawn: 1) A consistent increase in the ground heat flux is found during the day, when the observed soil temperatures are used to correct the cold bias present in ERA-40. Soil temperature changes introduced at the initial time maintain positive values but gradually decrease in magnitude with time. Sensible and latent heat fluxes and the moisture flux experience an increase during the first 6 h. 2) An increase in soil temperature impacts the air temperature through surface exchange, and near-surface moisture through evaporation. During the first two days, an increase in air temperature is seen across the region from the surface up to about 800 hPa (∼1450 m). The maximum near-surface air temperature increase is found to be, averaged over all cases, 0.5 K on the first day and 0.3 K on the second day. 3) The strength of the low-level jet is affected by the changes described above and also by the consequent changes in horizontal gradients of pressure and thermal fields. Thus, the three-dimensional circulation is affected, in addition to changes seen in the humidity and thermal fields and the locations and intensities of precipitating systems. 4) Overall results indicate that the incorporation of observed soil temperatures introduces a persistent soil heating condition that is favorable to convective development and, consequently, improves the simulation of precipitation.

Corresponding author address: Xingang Fan, Geosystems Research Institute, Mississippi State University, P.O. Box 2669, Starkville, MS 39762. Email: fan@gri.msstate.edu

Abstract

Soil temperature is a major variable in land surface models, representing soil energy status, storage, and transfer. It serves as an important factor indicating the underlying surface heating condition for weather and climate forecasts. This study utilizes the Weather Research and Forecasting (WRF) model to study the impacts of changes to the surface heating condition, derived from soil temperature observations, on regional weather simulations. Large cold biases are found in the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis project (ERA-40) soil temperatures as compared to observations. At the same time, a warm bias is found in the lower boundary assumption adopted by the Noah land surface model. In six heavy rain cases studied herein, observed soil temperatures are used to initialize the land surface model and to provide a lower boundary condition at the bottom of the model soil layer. By analyzing the impacts from the incorporation of observed soil temperatures, the following major conclusions are drawn: 1) A consistent increase in the ground heat flux is found during the day, when the observed soil temperatures are used to correct the cold bias present in ERA-40. Soil temperature changes introduced at the initial time maintain positive values but gradually decrease in magnitude with time. Sensible and latent heat fluxes and the moisture flux experience an increase during the first 6 h. 2) An increase in soil temperature impacts the air temperature through surface exchange, and near-surface moisture through evaporation. During the first two days, an increase in air temperature is seen across the region from the surface up to about 800 hPa (∼1450 m). The maximum near-surface air temperature increase is found to be, averaged over all cases, 0.5 K on the first day and 0.3 K on the second day. 3) The strength of the low-level jet is affected by the changes described above and also by the consequent changes in horizontal gradients of pressure and thermal fields. Thus, the three-dimensional circulation is affected, in addition to changes seen in the humidity and thermal fields and the locations and intensities of precipitating systems. 4) Overall results indicate that the incorporation of observed soil temperatures introduces a persistent soil heating condition that is favorable to convective development and, consequently, improves the simulation of precipitation.

Corresponding author address: Xingang Fan, Geosystems Research Institute, Mississippi State University, P.O. Box 2669, Starkville, MS 39762. Email: fan@gri.msstate.edu

Save
  • Avissar, R., and R. Pielke, 1989: A parameterization of heterogeneous land surfaces for atmospheric numerical models and its impact on regional meteorology. Mon. Wea. Rev., 117 , 21132136.

    • Search Google Scholar
    • Export Citation
  • Betts, A. K., F. Chen, K. E. Mitchell, and Z. Janjic, 1997: Assessment of the land surface and boundary layer models in two operational versions of the NCEP Eta model using FIFE data. Mon. Wea. Rev., 125 , 28962916.

    • Search Google Scholar
    • Export Citation
  • Chang, J-T., and P. J. Wetzel, 1991: Effects of spatial variations of soil moisture and vegetation on the evolution of a prestorm environment: A numerical case study. Mon. Wea. Rev., 119 , 13681390.

    • Search Google Scholar
    • Export Citation
  • Chen, F., and R. Avissar, 1994: Impact of land-surface moisture variability on local shallow convective cumulus and precipitation in large-scale models. J. Appl. Meteor., 33 , 13821401.

    • Search Google Scholar
    • Export Citation
  • 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
  • Chen, F., and Coauthors, 1996: Modeling of land surface evaporation by four schemes and comparison with FIFE observations. J. Geophys. Res., 101 , (D3). 72517268.

    • Search Google Scholar
    • Export Citation
  • Cheng, W. Y. Y., and W. J. Steenburgh, 2005: Evaluation of surface sensible weather forecasts by the WRF and the Eta models over the western United States. Wea. Forecasting, 20 , 812821.

    • Search Google Scholar
    • Export Citation
  • Chudinova, S. M., O. W. Frauenfeld, R. G. Barry, T. Zhang, and V. A. Sorokovikov, 2006: Relationship between air and soil temperature trends and periodicities in the permafrost regions of Russia. J. Geophys. Res., 111 , F02008. doi:10.1029/2005JF000342.

    • Search Google Scholar
    • Export Citation
  • Clark, C. A., and R. W. Arritt, 1995: Numerical simulations of the effect of soil moisture and vegetation cover on the development of deep convection. J. Appl. Meteor., 34 , 20292045.

    • Search Google Scholar
    • Export Citation
  • Climate Data Office, 1981: Monthly meteorological report of surface observations in China, 1980.01-12. Beijing Meteorological Center, Meteorological Press, 2352 pp.

    • Search Google Scholar
    • Export Citation
  • Climate Data Office, 1984: Monthly meteorological report of surface observations in China, 1980.01-12. Beijing Meteorological Center, Meteorological Press, 2328 pp.

  • Cressman, G. P., 1959: An operation objective analysis system. Mon. Wea. Rev., 87 , 367374.

  • Dai, Y., and Coauthors, 2003: The Common Land Model. Bull. Amer. Meteor. Soc., 84 , 10131023.

  • Deardorff, J. W., 1978: Efficient prediction of ground surface temperature and moisture, with inclusion of a layer of vegetation. J. Geophys. Res., 83 , 18891903.

    • Search Google Scholar
    • Export Citation
  • Diak, G. R., S. Heikkinen, and J. Bates, 1986: The influence of variations in surface treatment on 24-hour forecasts with a limited area model, including a comparison of modeled and satellite-measure surface temperatures. Mon. Wea. Rev., 114 , 215232.

    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46 , 30773107.

    • Search Google Scholar
    • Export Citation
  • Ek, M., and R. H. Cuenca, 1994: Variation in soil parameters: Implications for modeling surface fluxes and atmospheric boundary-layer development. Bound.-Layer Meteor., 70 , 369383.

    • Search Google Scholar
    • Export Citation
  • Entekhabi, D., and P. S. Eagleson, 1989: Land surface hydrology parameterization for atmospheric general circulation models including subgrid-scale spatial variability. J. Climate, 2 , 816831.

    • Search Google Scholar
    • Export Citation
  • Fan, X., 1993: A preliminary analysis of relationship between torrential rain and underlying heat field in mid- and lower-reaches of Yangtze River. Plateau Meteor., 12 , 322327.

    • Search Google Scholar
    • Export Citation
  • Fan, X., and M. Tang, 1996: Structural feature of soil temperature and precipitation and soil heat flux fields of strong earthquakes. Chin. J. Geophys., 39 , 247261.

    • Search Google Scholar
    • Export Citation
  • Fan, X., J. R. Krieger, D. J. Morton, J. Zhang, M. D. Shulski, and A. E. Klenne, 2007: Simulating Beaufort Sea coastal wind events using MM5 and WRF. Proc. Great Alaska Weather Modeling Symposium, Fairbanks, AK, National Weather Service, University of Alaska Fairbanks, p. 11.

    • Search Google Scholar
    • Export Citation
  • Findell, K. L., and E. A. B. Eltahir, 2003: Atmospheric controls on soil moisture-boundary layer interactions. Part II: Feedbacks within the continental United States. J. Hydrometeor., 4 , 570583.

    • Search Google Scholar
    • Export Citation
  • Grell, G. A., and D. Devenyi, 2002: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., 29 , 1693. doi:10.1029/2002GL015311.

    • Search Google Scholar
    • Export Citation
  • Harris, R. N., and D. S. Chapman, 1997: Borehole temperatures and a baseline for 20th-century global warming estimates. Science, 275 , 16181621.

    • Search Google Scholar
    • Export Citation
  • Hong, S-Y., J. Dudhia, and S-H. Chen, 2004: A revised approach to ice microphysics process for the bulk parameterization of clouds and precipitation. Mon. Wea. Rev., 132 , 103120.

    • Search Google Scholar
    • Export Citation
  • Huang, S., P. Y. Shen, and H. N. Pollack, 1996: Deriving century-long trends of surface temperature change from borehole temperatures. Geophys. Res. Lett., 23 , 257260.

    • Search Google Scholar
    • Export Citation
  • Janjic, Z. I., 1996: The surface layer parameterization in the NCEP Eta Model. Preprints, 11th Conf. on Numerical Weather Prediction, Norfolk, VA, Amer. Meteor. Soc., 354–355.

    • Search Google Scholar
    • Export Citation
  • Janjic, Z. I., 2002: Nonsingular implementation of the Mellor-Yamada level 2.5 scheme in the NCEP Meso Model. NCEP Office Note, 437, 61 pp.

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

  • Lachenbruch, A. H., and B. V. Marshall, 1986: Changing climate: Geothermal evidence from permafrost in the Alaskan Arctic. Science, 234 , 689696.

    • Search Google Scholar
    • Export Citation
  • Mahfouf, J. F., E. Richard, and P. Mascart, 1987: The influence of soil and vegetation on the development of mesoscale circulations. J. Climate Appl. Meteor., 26 , 14831495.

    • Search Google Scholar
    • Export Citation
  • Mintz, Y., 1984: The sensitivity of numerically simulated climates to land surface boundary conditions. The Global Climate, J. T Houghton, Ed., Cambridge University Press, 79–105.

    • Search Google Scholar
    • Export Citation
  • Mlawer, E. J., S. J. Taubman, P. D. Brwon, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102 , (D14). 1666316682.

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

  • Pielke Sr., R. A., 2001: Influence of the spatial distribution of vegetation and soils on the prediction of cumulus convective rainfall. Rev. Geophys., 39 , 151177.

    • Search Google Scholar
    • Export Citation
  • Pollack, H. N., S. Huang, and P-Y. Shen, 1998: Climate change record in subsurface temperatures: A global perspective. Science, 282 , 279281.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and J. G. Powers, 2005: A description of the advanced research WRF Version 2. NCAR Tech. Note 468+STR, 88 pp.

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

    • Search Google Scholar
    • Export Citation
  • Shukla, J., and Y. Mintz, 1982: Influence of land-surface evapotranspiration on the Earth’s climate. Science, 215 .doi:10.1126/science.215.4539.1498.

    • Search Google Scholar
    • Export Citation
  • Sutton, C., T. M. Hamill, and T. T. Warner, 2006: Will perturbing soil moisture improve warm-season ensemble forecasts? A proof of concept. Mon. Wea. Rev., 134 , 31743189.

    • Search Google Scholar
    • Export Citation
  • Tang, M., and J. Zhang, 1994: Seasonal mean soil temperature anomaly field at depth 3.2m and its application in prediction for flood season. Plateau Meteor., 13 , 178187.

    • Search Google Scholar
    • Export Citation
  • Tang, M., Z. Zhao, and Z. Ma, 1997: A summary of flood-season precipitation prediction by using the method of underground information during the recent ten years (1985–1994). Climatic Environ. Res., 2 , 5560.

    • Search Google Scholar
    • Export Citation
  • Viterbo, P., and A. C. M. Bejaars, 1995: An improved land surface parameterization scheme in the ECMWF model and its validation. J. Climate, 8 , 28162748.

    • Search Google Scholar
    • Export Citation
  • Wang, K., and T. J. Lewis, 1992: Geothermal evidence from Canada for a cold period before recent climatic warming. Science, 256 , 10031005.

    • Search Google Scholar
    • Export Citation
  • Wang, W., and N. L. Seaman, 1997: A comparison study of convective parameterization schemes in a mesoscale model. Mon. Wea. Rev., 125 , 252278.

    • Search Google Scholar
    • Export Citation
  • Wilks, D., 1995: Statistical Methods in the Atmospheric Sciences: An Introduction. Academic Press, 467 pp.

  • Xin, J-S., 1985: Review of ten-year (1975–1984) flood-season precipitation forecasts. Plateau Meteor., 4 , 372381.

  • Xue, Y., F. J. Zeng, K. E. Mitchell, Z. Janjic, and E. Rogers, 2001: The impact of land surface processes on 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.

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

    • Search Google Scholar
    • Export Citation
  • Zhang, T., R. G. Barry, D. Gilichinsky, S. S. Bykhovets, V. A. Sorokovikov, and J. Ye, 2001: An amplified signal of climatic change in soil temperatures during the last century at Irkutsk, Russia. Climatic Change, 49 , 4176.

    • Search Google Scholar
    • Export Citation
  • Zhang, T., M. Serreze, R. G. Barry, D. Gilichinsky, and A. Etringer, 2003: Climate change: Evidence from Russian historical soil temperature measurements. Geophysical Research Abstracts, Vol. 5, Abstract 01485. [Available online at http://www.cosis.net/abstracts/EAE03/01485/EAE03-J-01485.pdf].

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1228 814 55
PDF Downloads 236 50 5