• Atlas, R., , N. Wolfson, , and J. Terry, 1993: The effect of SST and soil moisture anomalies on GLA model simulations of the 1988 U.S. summer drought. J. Climate, 6 , 20342048.

    • Search Google Scholar
    • Export Citation
  • Atlas, R., and Coauthors. 2001: The effects of marine winds from scatterometer data on weather analysis and forecasting. Bull. Amer. Meteor. Soc., 82 , 19651990.

    • Search Google Scholar
    • Export Citation
  • Atlas, R., , G. D. Emmitt, , J. Terry, , E. Brin, , J. Ardizzone, , J-C. Jusem, , and D. Bungato, 2003: Recent observing system simulation experiments at the NASA DAO. Preprints,. Seventh Symp. on IOS: The Water Cycle, 83d Annual Meeting of the AMS, Long Beach, CA, Amer. Meteor. Soc., CD-ROM, 2.2.

    • Search Google Scholar
    • Export Citation
  • Castro, C. L., , T. B. McKee, , and R. A. Pielke, 2001: The relationship of the North American monsoon to tropical and North Pacific sea surface temperatures as revealed by observational analyses. J. Climate, 14 , 44494473.

    • Search Google Scholar
    • Export Citation
  • Chou, M-D., , and M. J. Suarez, 1994: An efficient thermal infrared radiation parameterization for use in general circulation models. Goddard Space Flight Center NASA Tech. Memo. 104606, Vol. 3, 102 pp.

    • Search Google Scholar
    • Export Citation
  • Chou, M-D., , M. J. Suarez, , C-H. Ho, , M-H. Yan, , and K-T. Lee, 1998: Parameterizations for cloud overlapping and shortwave single scattering properties for use in general circulation and cloud ensemble models. J. Climate, 11 , 202214.

    • Search Google Scholar
    • Export Citation
  • Chou, M-D., , K-T. Lee, , S-C. Tsay, , and Q. Fu, 1999: Parameterization of cloud longwave scattering for use in atmospheric models. J. Climate, 12 , 159169.

    • Search Google Scholar
    • Export Citation
  • Conaty, A. L., , J. C. Jusem, , L. Takacs, , D. Keyser, , and R. Atlas, 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.

    • Search Google Scholar
    • Export Citation
  • Dirmeyer, P. A., 1999: Assessing GCM sensitivity to soil wetness using GSWP data. J. Meteor. Soc. Japan, 77 , 367385.

  • Dirmeyer, P. A., 2000: Using a global soil wetness dataset to improve seasonal climate simulation. J. Climate, 13 , 29002922.

  • Dirmeyer, P. A., , A. J. Dolman, , and N. Sato, 1999: The pilot phase of the Global Soil Wetness Project. Bull. Amer. Meteor. Soc., 80 , 851878.

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

  • Fennessy, M. J., , and J. Shukla, 2000: Seasonal prediction over North America with a regional model nested in a global model. J. Climate, 13 , 26052627.

    • Search Google Scholar
    • Export Citation
  • Fennessy, M. J., , J. Kinter, , and A. Vernekar, 1990: Proceedings of the Workshop on the 1988 United States Drought, 30 April–2 May, 1990. Department of Meteorology, University of Maryland, 201 pp.

    • Search Google Scholar
    • Export Citation
  • Fox-Rabinovitz, M. S., , L. L. Takacs, , R. C. Govindaraju, , and M. J. Saurez, 2001: A variable resolution stretched-grid general circulation model: Regional climate simulation. Mon. Wea. Rev., 129 , 453469.

    • Search Google Scholar
    • Export Citation
  • Fritsch, J. M., , R. J. Kane, , and C. R. Chelius, 1986: The contribution of mesoscale convective weather systems to the warm-season precipitation in the United States. J. Climate Appl. Meteor., 25 , 13331345.

    • Search Google Scholar
    • Export Citation
  • Ghan, S., and Coauthors. 2000: A comparison of single column model simulations of summertime midlatitude continental convection. J. Geophys. Res., 105 (D2) 20912124.

    • Search Google Scholar
    • Export Citation
  • Giorgi, F., , L. O. Mearns, , C. Shields, , and L. Mayer, 1996: A regional model study of the importance of local versus remote controls of the 1988 drought and the 1993 flood over the central United States. J. Climate, 9 , 11501162.

    • Search Google Scholar
    • Export Citation
  • Helfand, M. H., , and J. C. Lebraga, 1988: Design of a non-singular level 2.5 second-order closure model for prediction of atmospheric turbulence. J. Atmos. Sci., 45 , 113132.

    • Search Google Scholar
    • Export Citation
  • Hong, S-Y., , and H-L. Pan, 2000: Impact of soil moisture anomalies on seasonal, summertime circulation over North America in a Regional Climate Model. J. Geophys. Res., 105 (D24) 2962529634.

    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., and Coauthors. 1997: The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset. Bull. Amer. Meteor. Soc., 78 , 520.

    • Search Google Scholar
    • Export Citation
  • Jenkins, G. S., , and E. J. Barron, 2000: Regional climate simulations over the continental United States during the summer of 1988 driven by a GCM and the ECMWF analyses. Global Planet. Change, 25 , 1938.

    • Search Google Scholar
    • Export Citation
  • Karl, T. R., , P. Y. Groisman, , R. W. Knight, , and R. R. Heim, 1993: Recent variations of snow cover and snowfall in North America and their relation to precipitation and temperature variations. J. Climate, 6 , 13271344.

    • Search Google Scholar
    • Export Citation
  • Lau, K-M., , K-M. Kim, , and S. S. P. Shen, 2002: Potential predictability of seasonal precipitation over the United States from canonical ensemble correlation predictions. Geophys. Res. Lett., 29 .1097, doi:10.1029/2001GL014263.

    • Search Google Scholar
    • Export Citation
  • Meeson, B. W., , F. E. Corprew, , J. M. P. McManus, , D. M. Myers, , J. W. Closs, , K-J. Sun, , D. J. Sunday, , and P. J. Sellers, 1995: ISLSCP Initiative I—Global Data Sets for Land–Atmosphere Models, 1987–1988. Vols. 1–5,. NASA CD-ROM.

    • Search Google Scholar
    • Export Citation
  • Mo, K. C., , J. R. Zimmerman, , E. Kalnay, , and M. Kanamitsu, 1991: A GCM study of the 1988 United States drought. Mon. Wea. Rev., 119 , 15121532.

    • Search Google Scholar
    • Export Citation
  • Mocko, D. M., , and Y. C. Sud, 2001: Refinements to SSiB with an emphasis on snowphysics: Evaluation and validation using GSWP and Valdai data. Earth Interact., 5 , 131.

    • Search Google Scholar
    • Export Citation
  • Mocko, D. M., , G. K. Walker, , and Y. C. Sud, 1999: New snow-physics to complement SSiB. Part II: Effects on soil moisture initialization and simulated surface fluxes, precipitation, and hydrology of GEOS 2 GCM. J. Meteor. Soc. Japan, 77 , 349366.

    • Search Google Scholar
    • Export Citation
  • Namias, J., 1991: Spring and summer 1988 drought over the contiguous United States—Causes and prediction. J. Climate, 4 , 5465.

  • Pal, J. S., , and E. A. B. Eltahir, 2001: Pathways relating soil moisture conditions to future summer rainfall with a model of the land–atmosphere system. J. Climate, 14 , 12271242.

    • Search Google Scholar
    • Export Citation
  • Schubert, S. D., , R. B. Rood, , and J. Pfaendtner, 1993: An assimilated dataset for Earth science applications. Bull. Amer. Meteor. Soc., 74 , 23312342.

    • Search Google Scholar
    • Export Citation
  • Shen, S. S. P., , K-M. Lau, , G. Li Kim, , and A. Basist, 2002: Formulation of the canonical ensemble correlation prediction for seasonal precipitation. Chin. J. Atmos. Sci., 26 , 114140.

    • Search Google Scholar
    • Export Citation
  • Sittel, M., 1994: Differences in the means of ENSO extremes for temperature and precipitation in the United States. COAPS Tech. Rep. 94-2, 50 pp.

    • Search Google Scholar
    • Export Citation
  • Sud, Y. C., , and A. Molod, 1988: A GCM simulation study of the influence of Saharan evapotranspiration and surface-albedo anomalies on July circulation and rainfall. Mon. Wea. Rev., 116 , 23882400.

    • Search Google Scholar
    • Export Citation
  • Sud, Y. C., , and D. M. Mocko, 1999: New snow-physics to complement SSiB. Part I: Design and evaluation with ISLSCP Initiative 1 datasets. J. Meteor. Soc. Japan, 77 , 335348.

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

    • Search Google Scholar
    • Export Citation
  • Sud, Y. C., , and G. K. Walker, 1999b: Microphysics of Clouds with the Relaxed Arakawa–Schubert Scheme (McRAS). Part II: Implementation and performance in GEOS II GCM. J. Atmos. Sci., 56 , 31213240.

    • Search Google Scholar
    • Export Citation
  • Sud, Y. C., , W. C. Chao, , and G. K. Walker, 1993: Dependence of rainfall on vegetation: Theoretical considerations, simulation experiments, observations, and inferences from simulated atmospheric soundings. J. Arid Environ., 25 , 518.

    • Search Google Scholar
    • Export Citation
  • Sud, Y. C., , K-M. Lau, , G. K. Walker, , and J-H. Kim, 1995: Understanding biosphere–precipitation relationships: Theory, model simulations, and logical inferences. MAUSAM, 46 , 114.

    • Search Google Scholar
    • Export Citation
  • Sud, Y. C., , G. K. Walker, , V. Mehta, , and K-M. Lau, 2002: Relative importance of the annual cycles of sea surface temperature and solar irradiance for tropical circulation and precipitation: A climate model simulation study. Earth Interact., 6 , 132.

    • Search Google Scholar
    • Export Citation
  • Takacs, L. L., , A. Molod, , and T. Weng, 1994: Documentation of the Goddard Earth Observing System (GEOS) General Circulation Model—Version 1. Goddard Space Flight Center NASA Tech. Memo. 104606, Vol. 1, Greenbelt, MD, 100 pp.

    • Search Google Scholar
    • Export Citation
  • Terry, J., , and R. Atlas, 1996: Objective cyclone tracking and its applications to ERS-1 scatterometer forecast impact studies. Preprints, 15th Conf. on Weather Analysis and Forecasting, Norfolk, VA, Amer. Meteor. Soc., 146–149.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., , and G. W. Branstator, 1992: Issues in establishing causes of the 1988 drought over North America. J. Climate, 5 , 159172.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., , and C. J. Guillemot, 1996: Physical processes involved in the 1988 drought and 1993 floods in North America. J. Climate, 9 , 12881298.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., , G. W. Branstator, , and P. A. Arkin, 1988: Origins of the 1988 North American drought. Science, 242 , 16401645.

  • Xie, S-C., and Coauthors. 2002: Intercomparison and evaluation of cumulus parameterizations under summertime midlatitude continental conditions. Quart. J. Roy. Meteor. Soc., 128 , 10951136.

    • 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
  • Zhou, J., , Y. C. Sud, , and K-M. Lau, 1996: Impact of orographically induced gravity–wave drag in the GLA GCM. Quart. J. Roy. Meteor. Soc., 122 , 903927.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 202 202 7
PDF Downloads 33 33 1

Simulating the Midwestern U.S. Drought of 1988 with a GCM

View More View Less
  • 1 Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, Maryland
© Get Permissions Rent on DeepDyve
Restricted access

Abstract

Past studies have suggested that the drought of the summer of 1988 over the midwestern United States may have been caused by sea surface temperature (SST) anomalies, an evolving stationary circulation, a soil-moisture feedback on circulation and rainfall, or even by remote forcings. The relative importance of various contributing factors is investigated in this paper through the use of Goddard Earth Observing System (GEOS) GCM simulations. Seven different experiments, each containing an ensemble of four simulations, were conducted with the GCM. For each experiment, the GCM was integrated through the summers of 1987 and 1988 starting from an analyzed atmosphere in early January of each year. In the baseline case, only the SST anomalies and climatological vegetation parameters were prescribed, while everything else (such as soil moisture, snow cover, and clouds) was interactive. The precipitation differences (1988 minus 1987) show that the GCM was successful in simulating reduced precipitation in 1988, but the accompanying low-level circulation anomalies in the Midwest were not well simulated. To isolate the influence of the model’s climate drift, analyzed winds and analyzed soil moisture were prescribed globally as continuous updates (in isolation or jointly). The results show that remotely advected wind biases (emanating from potential errors in the model’s dynamics and physics) are the primary cause of circulation biases over North America. Inclusion of soil moisture helps to improve the simulation as well as to reaffirm the strong feedback between soil moisture and precipitation. In a case with both updated winds and soil moisture, the model produces more realistic evapotranspiration and precipitation differences. An additional case also used soil moisture and winds updates, but only outside North America. Its simulation is very similar to that of the case with globally updated winds and soil moisture, which suggests that North American simulation errors originate largely outside the region. Two additional cases examining the influence of vegetation were built on this case using correct and opposite-year vegetation. The model did not produce a discernible improvement in response to vegetation for the drought year. One may conclude that the soil moisture governs the outcome of the land–atmosphere feedback interaction far more than the vegetation parameters. A primary inference of this study is that even though SSTs have some influence on the drought, model biases strongly influence the prediction errors. It must be emphasized that the results from this study are dependent upon the GEOS model’s identified errors and biases, and that the conclusions do not necessarily apply to results from other models.

Additional affiliation: SAIC/General Sciences Operation, Beltsville, Maryland

Corresponding author address: Dr. Y. C. Sud, Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, MD 20771. Email: sud@climate.gsfc.nasa.gov

Abstract

Past studies have suggested that the drought of the summer of 1988 over the midwestern United States may have been caused by sea surface temperature (SST) anomalies, an evolving stationary circulation, a soil-moisture feedback on circulation and rainfall, or even by remote forcings. The relative importance of various contributing factors is investigated in this paper through the use of Goddard Earth Observing System (GEOS) GCM simulations. Seven different experiments, each containing an ensemble of four simulations, were conducted with the GCM. For each experiment, the GCM was integrated through the summers of 1987 and 1988 starting from an analyzed atmosphere in early January of each year. In the baseline case, only the SST anomalies and climatological vegetation parameters were prescribed, while everything else (such as soil moisture, snow cover, and clouds) was interactive. The precipitation differences (1988 minus 1987) show that the GCM was successful in simulating reduced precipitation in 1988, but the accompanying low-level circulation anomalies in the Midwest were not well simulated. To isolate the influence of the model’s climate drift, analyzed winds and analyzed soil moisture were prescribed globally as continuous updates (in isolation or jointly). The results show that remotely advected wind biases (emanating from potential errors in the model’s dynamics and physics) are the primary cause of circulation biases over North America. Inclusion of soil moisture helps to improve the simulation as well as to reaffirm the strong feedback between soil moisture and precipitation. In a case with both updated winds and soil moisture, the model produces more realistic evapotranspiration and precipitation differences. An additional case also used soil moisture and winds updates, but only outside North America. Its simulation is very similar to that of the case with globally updated winds and soil moisture, which suggests that North American simulation errors originate largely outside the region. Two additional cases examining the influence of vegetation were built on this case using correct and opposite-year vegetation. The model did not produce a discernible improvement in response to vegetation for the drought year. One may conclude that the soil moisture governs the outcome of the land–atmosphere feedback interaction far more than the vegetation parameters. A primary inference of this study is that even though SSTs have some influence on the drought, model biases strongly influence the prediction errors. It must be emphasized that the results from this study are dependent upon the GEOS model’s identified errors and biases, and that the conclusions do not necessarily apply to results from other models.

Additional affiliation: SAIC/General Sciences Operation, Beltsville, Maryland

Corresponding author address: Dr. Y. C. Sud, Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, MD 20771. Email: sud@climate.gsfc.nasa.gov

Save