• Adler, R. F., and Coauthors, 2003: The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). J. Hydrometeor., 4 , 11471167.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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.

  • Beljaars, A. C. M., , Viterbo P. , , Miller M. , , and Betts A. K. , 1996: The anomalous rainfall over the United States during July 1993: Sensitivity to land surface parameterization and soil moisture anomalies. Mon. Wea. Rev., 124 , 362383.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berg, A. A., , Famiglietti J. S. , , Walker J. P. , , and Houser P. R. , 2003: Impact of bias correction to reanalysis products on simulations of North American soil moisture and hydrological fluxes. J. Geophys. Res., 108 .4490, doi:10.1029/2002JD003334.

    • Search Google Scholar
    • Export Citation
  • Budyko, M. I., 1974: Climate and Life. Academic Press, 508 pp.

  • Chou, M-D., , and Suarez M. , 1994: An efficient thermal infrared radiation parameterization for use in general circulation models. NASA Tech. Memo. 104606, Vol. 3, 84 pp.

  • Chou, M-D., , and Suarez M. , 1996: A solar radiation parameterization (CLIRAD-SW) for atmospheric studies. NASA Tech. Memo. 104606, Vol. 15, 38 pp.

  • Delworth, T., , and Manabe S. , 1989: The influence of soil wetness on near-surface atmospheric variability. J. Climate, 2 , 14471462.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dirmeyer, P. A., 2000: Using a global soil wetness dataset to improve seasonal climate simulation. J. Climate, 13 , 29002922.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Douville, H., , and Chauvin F. , 2000: Relevance of soil moisture for seasonal climate predictions: A preliminary study. Climate Dyn., 16 , 719736.

  • Eagleson, P. S., 1978: Climate, soil and vegetation. 4. The expected value of annual evapotranspiration. Water Resour. Res., 14 , 731739.

  • Entin, J. K., , Robock A. , , Vinnikov K. Y. , , Zabelin V. , , Liu S. , , Namkhai A. , , and Adyasuren T. , 1999: Evaluation of Global Soil Wetness Project soil moisture simulations. J. Meteor. Soc. Japan, 77 , 183198.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fennessy, M. J., , and Shukla J. , 1999: Impact of initial soil wetness on seasonal atmospheric prediction. J. Climate, 12 , 31673180.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guo, Z., and Coauthors, 2006: GLACE: The Global Land–Atmosphere Coupling Experiment. Part II: Analysis. J. Hydrometeor., 7 , 611625.

  • Gupta, S. K., , Ritchey N. A. , , Wilber A. C. , , Whitlock C. H. , , Gibson G. G. , , and Stackhouse P. W. Jr., 1999: A climatology of surface radiation budget derived from satellite data. J. Climate, 12 , 26912710.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Higgins, R. W., , Shi W. , , and Yarosh E. , 2000: : Improved United States Precipitation Quality Control System and Analysis. NCEP/Climate Prediction Center Atlas 7, 40 pp. [Available online at http://www.cpc.ncep.noaa.gov/research_papers/-ncep_cpc_atlas/7/index.html.].

  • Huang, J., , and Van den Dool M. H. , 1993: Monthly precipitation–temperature relations and temperature prediction over the United States. J. Climate, 6 , 11111132.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, J., , Van den Dool H. , , and Georgakakos K. P. , 1996: Analysis of model-calculated soil moisture over the United States (1931–1993) and applications to long-range temperature forecasts. J. Climate, 9 , 13501362.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koster, R. D., , 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 Milly P. C. D. , 1997: The interplay between transpiration and runoff formulations in land surface schemes used with atmospheric models. J. Climate, 10 , 15781591.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koster, R. D., , and Suarez M. J. , 2004: Suggestions in the observational record of land–atmosphere feedback operating at seasonal timescales. J. Hydrometeor., 5 , 567572.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koster, R. D., , Suarez M. J. , , and Heiser M. , 2000: Variance and predictability of precipitation at seasonal-to-interannual timescales. J. Hydrometeor., 1 , 2646.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koster, R. D., , Suarez M. J. , , Higgins R. W. , , and Van den Dool H. , 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: Realistic initialization of land surface states: Impacts on subseasonal forecast skill. J. Hydrometeor., 5 , 10491063.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and Coauthors, 2006: GLACE: The Global Land–Atmosphere Coupling Experiment. Part I: Overview. J. Hydrometeor., 7 , 590610.

  • Lawrimore, J. H., , and Peterson T. C. , 2000: Pan evaporation trends in dry and humid regions of the United States. J. Hydrometeor., 1 , 543546.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mahanama, S. P. P., , and Koster R. D. , 2005: AGCM biases in evaporation regime: Impacts on soil moisture memory and land–atmosphere feedback. J. Hydrometeor., 6 , 656669.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Manabe, S., 1969: Climate and the ocean circulation. I. The atmospheric circulation and the hydrology of the earth’s surface. Mon. Wea. Rev., 97 , 739774.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moorthi, S., , and Suarez M. J. , 1992: Relaxed Arakawa–Schubert: A parameterization of moist convection for general circulation models. Mon. Wea. Rev., 120 , 9781002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peterson, T. C., , and Vose R. S. , 1997: An overview of the Global Historical Climatology Network temperature data base. Bull. Amer. Meteor. Soc., 78 , 28372849.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Distinct Hydrological Signatures in Observed Historical Temperature Fields

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  • 1 Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland
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Abstract

In an atmospheric general circulation model (AGCM), the physical bounds on soil moisture content and the nonlinear relationship between soil moisture and evaporation lead to distinct geographical patterns in key surface energy and water balance variables. In particular, simple hydrological considerations suggest—and extensive AGCM simulations confirm—that the variance and skew of seasonally averaged [June–August (JJA)] air temperature on the planet should be maximized in specific, and different, regions: a variance maximum should appear on the dry side of the soil moisture variance maximum, and a positive skew maximum should appear on the wet side of the temperature variance maximum. These ideas are tested with multidecade observational temperature data from the Global Historical Climatology Network (GHCN). In the United States, where sufficient data exist, the predicted patterns in the seasonal temperature moments show up where expected. These results suggest that hydrological considerations do indeed control the patterns of seasonal temperature variance and skew in nature.

Corresponding author address: Randal Koster, Global Modeling and Assimilation Office, Code 610.1, NASA Goddard Space Flight Center, Greenbelt, MD 20771. Email: randal.d.koster@nasa.gov

Abstract

In an atmospheric general circulation model (AGCM), the physical bounds on soil moisture content and the nonlinear relationship between soil moisture and evaporation lead to distinct geographical patterns in key surface energy and water balance variables. In particular, simple hydrological considerations suggest—and extensive AGCM simulations confirm—that the variance and skew of seasonally averaged [June–August (JJA)] air temperature on the planet should be maximized in specific, and different, regions: a variance maximum should appear on the dry side of the soil moisture variance maximum, and a positive skew maximum should appear on the wet side of the temperature variance maximum. These ideas are tested with multidecade observational temperature data from the Global Historical Climatology Network (GHCN). In the United States, where sufficient data exist, the predicted patterns in the seasonal temperature moments show up where expected. These results suggest that hydrological considerations do indeed control the patterns of seasonal temperature variance and skew in nature.

Corresponding author address: Randal Koster, Global Modeling and Assimilation Office, Code 610.1, NASA Goddard Space Flight Center, Greenbelt, MD 20771. Email: randal.d.koster@nasa.gov

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