Impact of Initial Soil Wetness on Seasonal Atmospheric Prediction

M. J. Fennessy Center for Ocean–Land–Atmosphere Studies, Calverton, Maryland

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J. Shukla Center for Ocean–Land–Atmosphere Studies, Calverton, Maryland

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Abstract

This study investigates the importance of initial soil wetness in seasonal predictions with dynamical models. Two experiments are performed, each consisting of two ensembles of global climate model integrations initialized from early June observed atmospheric states. In each experiment the only difference between the two ensembles is that they are initialized with a different soil wetness. In the first experiment both ensembles are initialized from 1988 observed atmospheric states and use observed 1988 SST; one ensemble is initialized with seasonally varying climatological soil wetness, and the other is initialized with proxy 1988 soil wetness derived from the European Centre for Medium-Range Weather Forecasts analysis–forecast system. In the second experiment the two ensembles are initialized from observed atmospheric states and use observed SST for five different years, and each ensemble is initialized with a different climatological soil wetness. After initialization, a coupled atmosphere–biosphere model determines the evolution of the soil wetness fields in all the integrations.

The experiments are analyzed to determine the impact of the initial soil wetness differences. In contrast to several previous studies in which initial soil wetness was prescribed arbitrarily, a somewhat more realistic soil wetness impact is analyzed by comparing integrations initialized with climatological soil wetness to integrations initialized with soil wetness derived from the output of an operational analysis–forecast model. The initial soil wetness impact is found to be largely local and is largest on near-surface fields, in agreement with previous results. Significant impacts were found in several tropical and extratropical regions in both experiments. Almost all the regions that had significant increases (decreases) in initial soil wetness had significant increases (decreases) in seasonal mean evaporation and significant decreases (increases) in seasonal mean surface air temperature. Half of the regions had significant increases (decreases) in seasonal mean precipitation in response to increased (decreased) initial soil wetness, though the response of the precipitation was more variable and was highly dependent on the response of the moisture flux convergence to the initial soil wetness anomaly. In order for an initial soil wetness difference to force a significant seasonal mean precipitation difference in a region, it must effectively alter the mean convective stability of the region and thereby the mean convective precipitation.

The strength of the impact of initial soil wetness differences, as well as the nature of the impact on precipitation and other atmospheric fields, depends on several factors. These factors include the areal extent and magnitude of the initial soil wetness difference, the persistence of the soil wetness difference, the strength of the solar forcing, the availability of nearby moisture sources, and the strength of the regional dynamical circulation. The results suggest that seasonal atmospheric prediction could be enhanced by using a realistic initial state of soil wetness.

Corresponding author address: Michael J. Fennessy, Center for Ocean–Land–Atmosphere Studies, 4041 Powder Mill Road, Suite 302, Calverton, MD 20705.

Abstract

This study investigates the importance of initial soil wetness in seasonal predictions with dynamical models. Two experiments are performed, each consisting of two ensembles of global climate model integrations initialized from early June observed atmospheric states. In each experiment the only difference between the two ensembles is that they are initialized with a different soil wetness. In the first experiment both ensembles are initialized from 1988 observed atmospheric states and use observed 1988 SST; one ensemble is initialized with seasonally varying climatological soil wetness, and the other is initialized with proxy 1988 soil wetness derived from the European Centre for Medium-Range Weather Forecasts analysis–forecast system. In the second experiment the two ensembles are initialized from observed atmospheric states and use observed SST for five different years, and each ensemble is initialized with a different climatological soil wetness. After initialization, a coupled atmosphere–biosphere model determines the evolution of the soil wetness fields in all the integrations.

The experiments are analyzed to determine the impact of the initial soil wetness differences. In contrast to several previous studies in which initial soil wetness was prescribed arbitrarily, a somewhat more realistic soil wetness impact is analyzed by comparing integrations initialized with climatological soil wetness to integrations initialized with soil wetness derived from the output of an operational analysis–forecast model. The initial soil wetness impact is found to be largely local and is largest on near-surface fields, in agreement with previous results. Significant impacts were found in several tropical and extratropical regions in both experiments. Almost all the regions that had significant increases (decreases) in initial soil wetness had significant increases (decreases) in seasonal mean evaporation and significant decreases (increases) in seasonal mean surface air temperature. Half of the regions had significant increases (decreases) in seasonal mean precipitation in response to increased (decreased) initial soil wetness, though the response of the precipitation was more variable and was highly dependent on the response of the moisture flux convergence to the initial soil wetness anomaly. In order for an initial soil wetness difference to force a significant seasonal mean precipitation difference in a region, it must effectively alter the mean convective stability of the region and thereby the mean convective precipitation.

The strength of the impact of initial soil wetness differences, as well as the nature of the impact on precipitation and other atmospheric fields, depends on several factors. These factors include the areal extent and magnitude of the initial soil wetness difference, the persistence of the soil wetness difference, the strength of the solar forcing, the availability of nearby moisture sources, and the strength of the regional dynamical circulation. The results suggest that seasonal atmospheric prediction could be enhanced by using a realistic initial state of soil wetness.

Corresponding author address: Michael J. Fennessy, Center for Ocean–Land–Atmosphere Studies, 4041 Powder Mill Road, Suite 302, Calverton, MD 20705.

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  • Alpert, J. C., M. Kanamitsu, P. M. Caplan, J. G. Sela, G. H. White, and E. Kalnay, 1988: Mountain induced gravity wave drag parameterization in the NMC medium-range forecast model. Preprints, Eighth Conf. on Numerical Weather Prediction, Baltimore, MD, Amer. Meteor. Soc., 726–733.

  • Anthes, R. A., 1977: A cumulus parameterization scheme utilizing a one-dimensional cloud model. Mon. Wea. Rev.,105, 270–300.

  • Arakawa, A., and W. H. Schubert, 1974: Interaction of cumulus cloud ensemble with the large-scale environment. J. Atmos. Sci.,31, 671–701.

  • 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, 2034–2048.

  • Betts, A. K., J. H. Ball, A. C. M. Beljaars, M. J. Miller, and P. Viterbo, 1994: Coupling between land surface boundary layer parameterizations and rainfall on local and regional scales: Lessons from the wet summer of 1993. Preprints, Fifth Symp. on Global Change, Nashville, TN, Amer. Meteor. Soc., 174–181.

  • Branković, Č., T. N. Palmer, and P. Viterbo, 1990: Diagnostic and model sensitivity study of the 1988 U.S. drought. Proc. Workshop on 1988 U.S. Drought, College Park, MD, Dept. of Meteorology, University of Maryland at College Park, 110–128. [Available from Dept. of Meteorology, University of Maryland at College Park, College Park, MD 20742.].

  • Cook, K. H., and A. Gnanadesikan, 1991: Effects of saturated and dry land surfaces on the tropical circulation and precipitation in a general circulation model. J. Climate,4, 873–889.

  • Delworth, T. L., and S. Manabe, 1988: The influence of potential evaporation on the variabilities of simulated soil wetness and climate. J. Climate,1, 523–547.

  • ——, and ——, 1989: The influence of soil wetness on near-surface atmospheric variability. J. Climate,2, 1447–1462.

  • Dewitt, D., 1996: The effects of cumulus convection parameterization on the climate of the COLA general circulation model. COLA Tech. Rep. 27, 43 pp. [Available from COLA, 4041 Powder Mill Road, Suite 302, Calverton, MD 20705.].

  • Dirmeyer, P. A., 1994: Vegetation stress as a feedback mechanism in midlatitude drought. J. Climate,7, 1463–1483.

  • ——, and J. Shukla, 1993: Observational and modeling studies of the influence of soil moisture anomalies on the atmospheric circulation. Predictions of Interannual Climate Variations, J. Shukla, Ed., NATO Series I, Vol. 6, Springer-Verlag, 1–23.

  • Dorman, J. L., and P. J. Sellers, 1989: A global climatology of albedo, roughness length and stomatal resistance for atmospheric general circulation models as represented by the Simple Biosphere Model (SiB). J. Appl. Meteor.,28, 833–855.

  • Fennessy, M. J., J. L. Kinter III, L. Marx, E. Schneider, P. J. Sellers, and J. Shukla, 1994: GCM simulations of the life cycles of the 1988 US drought and heat wave. COLA Tech. Rep. 6, 53 pp. [Available from COLA, 4041 Powder Mill Road, Suite 302, Calverton, MD 20705.].

  • Hao, W., and L. F. Bosart, 1987: A moisture budget analysis of the protracted heat wave in the southern plains during the summer of 1980. Wea. Forecasting,2, 269–288.

  • Harshvardhan, R. Davies, D. A. Randall, and T. G. Corsetti, 1987: A fast radiation parameterization for general circulation models. J. Geophys. Res.,92, 1009–1016.

  • Hogan, T. F., and T. E. Rosmond, 1991: The description of the Navy Operational Global Atmospheric Prediction System’s spectral forecast model. Mon. Wea. Rev.,119, 1786–1815.

  • Hou, Y.-T., 1990: Cloud–radiation–dynamics interaction. Ph.D. thesis, University of Maryland at College Park, 209 pp. [Available from Dept. of Meteorology, University of Maryland at College Park, College Park, MD 20742.].

  • Kinter, J. L., III, J. Shukla, L. Marx, and E. K. Schneider, 1988: A simulation of the winter and summer circulations with the NMC global spectral model. J. Atmos. Sci.,45, 2486–2522.

  • Kuo, H. L., 1965: On the formation and intensification of tropical cyclones through latent heat release by cumulus convection. J. Atmos. Sci.,22, 40–63.

  • Lacis, A. A., and J. E. Hansen, 1974: A parameterization for the absorption of solar radiation in the earth’s atmosphere. J. Atmos. Sci.,31, 118–133.

  • Liston, G. E., Y. C. Sud, and G. K. Walker, 1993: Design of a global soil moisture initialization procedure for the Simple Biosphere Model. NASA Tech. Memo. 104590, 130 pp. [Available from NTIS, 5285 Port Royal Rd., Springfield, VA 22161; NTIS N94-1094012INZ.].

  • Mellor, G. L., and T. Yamada, 1982: Development of a turbulence closure model for geophysical fluid problems. Rev. Geophys. Space Phys.,20, 851–875.

  • Mintz, Y., 1984: The sensitivity of numerically simulated climates to land-surface conditions. The Global Climate, J. Houghton, Ed., Cambridge University Press, 79–105.

  • ——, and Y. Serafini, 1981: Global fields of soil moisture and land-surface evapotranspiration. Research review—1980/81. NASA/Goddard Space Flight Center Tech. Memo. 83907, 269 pp. [Available from NASA/Goddard Space Flight Center, Greenbelt, MD 20771.].

  • ——, and ——, 1992: A global monthly climatology of soil moisture and water balance. Climate Dyn.,8, 13–17.

  • Miyakoda, K., and J. Sirutis, 1977: Comparative integrations of global spectral models with various parameterized processes of subgrid scale vertical transports. Beitr. Phys. Atmos.,50, 445–447.

  • ——, ——, and R. F. Strickler, 1979: Cumulative results of extended forecast experiments. Part II: Model performance for summer cases. Mon. Wea. Rev.,107, 395–420.

  • Moorthi, S., and M. J. Suarez, 1992: Relaxed Arakawa–Schubert: A parameterization of moist convection for general circulation models. Mon. Wea. Rev.,120, 978–1002.

  • Oglesby, R. J., 1991: Springtime soil moisture, natural climatic variability, and North American drought as simulated by the NCAR Community Climate Model 1. J. Climate,4, 890–897.

  • ——, and D. J. Erickson III, 1989: Soil moisture and the persistence of North American drought. J. Climate,2, 1362–1380.

  • Paegle, J., K. C. Mo, and J. Nogués-Paegle, 1996: Dependence of simulated precipitation on surface evaporation during the 1993 United States summer floods. Mon. Wea. Rev.,124, 345–361.

  • Phillips, N. A., 1957: A coordinate system having some special advantages for numerical forecasting. J. Meteor.,14, 184–185.

  • Reynolds, R. W., 1988: A real-time global sea surface temperature analysis. J. Climate,1, 75–86.

  • ——, and T. M. Smith, 1994: Improved global sea surface temperature analyses using optimum interpolation. J. Climate,7, 929–948.

  • Rind, D., 1982: The influence of ground moisture conditions in North America on summer climate as modeled in the GISS GCM. Mon. Wea. Rev.,110, 1487–1494.

  • Ropelewski, C. F., J. E. Janowiak, and M. F. Halpert, 1985: The analysis and display of real time surface climate data. Mon. Wea. Rev.,113, 1101–1107.

  • Sato, N., P. J. Sellers, D. A. Randall, E. K. Schneider, J. Shukla, J. L. Kinter III, Y.-T. Hou, and E. Albertazzi, 1989a: Effects of implementing the Simple Biosphere Model in a general circulation model. J. Atmos. Sci.,46, 2757–2782.

  • ——, ——, ——, ——, ——, ——, ——, and ——, 1989b: Implementing the Simple Biosphere Model (SiB) in a GCM: Methodology and results. NASA Contractor Report CR-185509, NASA, Washington, DC, 76 pp. [Available from NTIS, 5285 Port Royal Rd., Springfield, VA 22161.].

  • Sela, J. G., 1980: Spectral modeling at the National Meteorological Center. Mon. Wea. Rev.,108, 1279–1292.

  • Sellers, P. J., 1990: Specifying surface boundary conditions for drought studies. Proc. Workshop on 1988 U.S. Drought, College Park, MD, Dept. of Meteorology, University of Maryland at College Park, 170–172. [Available from Dept. of Meteorology, University of Maryland at College Park, College Park, MD 20742.].

  • ——, Y. Mintz, Y. C. Sud, and A. Dalcher, 1986: A Simple Biosphere Model (SiB) for use within general circulation models. J. Atmos. Sci.,43, 505–531.

  • ——, W. J. Shuttleworth, J. L. Dorman, A. Dalcher, and J. M. Roberts, 1989: Calibrating the simple biosphere model for Amazonian tropical forest using field and remote sensing data. Part I: Average calibration with field data. J. Appl. Meteor.,28, 727–759.

  • Shukla, J., and Y. Mintz, 1982: Influence of land-surface evapotranspiration on the earth’s climate. Science,215, 1498–1501.

  • Slingo, J. M., 1987: The development and verification of a cloud prediction scheme for the ECMWF model. Quart. J. Roy. Meteor. Soc.,113, 899–927.

  • Sud, Y. C., and M. J. Fennessy, 1984: Influence of evaporation in semi-arid regions on the July circulation: A numerical study. J. Climatol.,4, 383–398.

  • Tiedtke, M., 1984: The effect of penetrative cumulus convection on the large-scale flow in a general circulation model. Beitr. Phys. Atmos.,57, 216–239.

  • Vernekar, A., B. Kirtman, J. Zhou, and D. Dewitt, 1992: Orographic gravity–wave drag effects on medium-range forecasts with a general circulation model. Physical Processes in Atmospheric Models, D. R. Sikka and S. S. Singh, Eds., Wiley Eastern Limited, 295–307.

  • Walker, J., and P. R. Rowntree, 1977: The effect of soil moisture on circulation and rainfall in a tropical model. Quart. J. Roy. Meteor. Soc.,103, 29–46.

  • Willmott, C. J., C. M. Rowe, and Y. Mintz, 1985: Climatology of the terrestrial seasonal water cycle. Int. J. Climatol.,5, 589–606.

  • Xue, Y., P. J. Sellers, J. L. Kinter, and J. Shukla, 1991: A simplified biosphere model for global climate studies. J. Climate,4, 345–364.

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