Warm Season Land Surface — Climate Interactions in the United States Midwest from Mesoscale Observations

  • J. O. Adegoke
  • A. M. Carleton
Part of the Advances in Global Change Research book series (AGLO, volume 6)

Abstract

The United States Midwest over the last two decades has experienced marked warm season climate anomalies, including droughts and major floods. While the development of these extreme events can usually be traced to anomalies in atmospheric circulation, and may include teleconnections, studies based on model simulations have shown that land surface forcing may be partly responsible for the persistence of these climate anomalies. This study evaluates the presence and strength of long-term land surface-climate interactions in the U.S. Midwest. We do this via an analysis of the cross-seasonal (spring and summer) associations between temperature and moisture (Palmer Drought Severity Index-PDSI, Crop Moisture-Z Index, and precipitation) anomalies. Direct and lag correlations for the 1895–1995 and 1948–1995 periods show that warm and dry summers tend to follow warm spring seasons. These results imply that springtime precipitation anomalies may help to determine the temperature regime of the following summer, possibly via the moisture content of the upper soil. We also show that broad land cover types tend to modulate summer climate anomalies in the U. S. Midwest.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anderson, J.R., Hardy, E.E., Roach, J.T. and Witmer, R. E., (1976). ‘A land use and land cover classification system for use with remote sensing data’ U.S. Geological Survey Professional Paper, 964, 28p.Google Scholar
  2. Andre, J.-C., Goutorbe, J.-P. and Perrier, A., (1986). ‘HAPEX-MOBILHY: a hydrological atmospheric experiment for the study of water budget and evaporation flux at the climatic scale’ Bull. Amer. Meteor. Soc, 67, 138–144.CrossRefGoogle Scholar
  3. Arnold, D.L., (1994). Synoptic and Mesoscale Climatologies of Severe Local Storms for the American Midwest Ph.D. dissertation, Dept. of Geography, Indiana University, Bloomington. 257p.Google Scholar
  4. Betts, A. K., Hall, J.H., Beljaars, A.C.M., Miller, M.J., and Viterbo, P.A., (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 Studies, Nashville, Amer. Meteor. Soc., 174–181Google Scholar
  5. Bonan, G.B., Pollard, D. and Thompson, S.L., (1993). ‘Influence of subgrid-scale heterogeneity in leaf-area index, stomatal resistance, and soil moisture on grid-scale land-atmosphere interactions’ J. Climate, 6. 1882–1897.CrossRefGoogle Scholar
  6. Changnon, S.A. and Kunkel, K.E., (1992). ‘Assessing impacts of a climatologically unique year (1990) in the Midwest’ Phys. Geog., 13, 180–190.Google Scholar
  7. Charney, J.G., Quirk, W.J., Chow, S.H., and Kornfield, J., (1977). ‘A comparative study of the effects of albedo change on drought in semi-arid region’ J. Atmos. Sci., 34, 1336–1385.CrossRefGoogle Scholar
  8. Gibson, H.M. and Vonder Haar, T.H., (1990). ‘Cloud and convection frequencies over the southeast United States as related to small-scale geographic features’ Mon. Weath. Rev., 118, 2215–2227.CrossRefGoogle Scholar
  9. Goutorbe, J.-P., Noilhan, J., Valancogne, C. and Cuenca, R.H., (1989). ‘Soil moisture variations during HAPEX-MOBILHY’ Annals. Geophysics., 7, 415–425.Google Scholar
  10. Hammer, R.M., 1970. ‘Cloud development and distribution around Khartoum’ Weather, 28, 411–414.CrossRefGoogle Scholar
  11. 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’ Journal of. Climate, 9, 1350–1362.CrossRefGoogle Scholar
  12. Karl, T.B., (1986). ‘The relationship of soil moisture parameterizations to subsequent seasonal and monthly mean temperature in the United States’ Mon. Weath. Rev., 114, 675–686.CrossRefGoogle Scholar
  13. Kunkel, K.E., (1989). ‘A surface energy budget view of the 1988 Midwestern United States drought’ Bound.-Layer Meteorology, 48, 217–225.CrossRefGoogle Scholar
  14. Li, B. and Avissar, R., (1994). ‘The impact of spatial variability of land surface characteristics on land-surface heat fluxes’ Journal of. Climate, 7, 527–537.CrossRefGoogle Scholar
  15. Lott, N., (1993). ‘The summer of 1993: Flooding in the Midwest and drought in the Southeast’ National Climatic Data Center Research Customer Service Group Technical Report, 93–04. 21 p.Google Scholar
  16. Lozano-Garcia, D.F., Fernandez, R.N., Gallo, K.P. and Johannsen, C.J., (1995). ‘Monitoring the 1988 severe drought in Indiana, U.S.A. using AVHRR’ International. Journal of Remote Sensing, 16, 1327–1340.CrossRefGoogle Scholar
  17. Lyons, T.J., Schwerdtfeger, P., Hacker, J.M., Foster, I.J., Smith, R.C.G. and Xinmei, H., (1993). ‘Land-atmosphereinteraction in a semiarid region: the bunny fence experiment’ Bulletin of the American Meteorological Society, 74, 1327–1334.CrossRefGoogle Scholar
  18. McNab, A. L., (1989). ‘Climate and drought’ EOS, Transactions of the American Geophysics Union, 70, 882–883.Google Scholar
  19. Molders, N. and Raabe, A., (1996). ‘Numerical investigations on the influence of subgrid-scale surface heterogeneity on evapotranspiration and cloud processes’ Journal of Applied Meteorology, 35, 782–795.CrossRefGoogle Scholar
  20. Namias, J., (1960). ‘Factors in the initiation, perpetuation and termination of drought’ Extract of Publ. No. 51, IASH Commission of Surface Waters, 81–94. [Avail. from IASH, UNESCO, Paris].Google Scholar
  21. Namias, J., (1991). ‘Spring and summer 1988 drought over the contiguous United States-causes and prediction’ Journal of Climate, 4, 54–65.CrossRefGoogle Scholar
  22. Pielke, R.A., Dalu, G.A., Lee, T.J., Rodriguez, H., Eastman, J. and Kittel, T.G.F., (1993). ‘Mesoscale parameterization of heat fluxes due to landscape variability for use in general circulation models, In: Exchange Processes at the Land Surface for a Range of Space and Time Scales (Proc. of the Yokohama Symp., July 1993). IAHS Publ. No. 212. 331–342.Google Scholar
  23. Raymond, W.H., Rabin, R.M. and Wade, G.S., (1994) Evidence of an agricultural heat island in the lower Mississippi river floodplain’ Bulletin American Meteorological Society, 75, 1019–1025.CrossRefGoogle Scholar
  24. Sellers, P.J., Hall, F.G., Asrar, G., Strebel, D.E., and Murphy, R.E., (1992) ‘An overview of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE)’ Journal of Geophysical Research, 97, 18,345–18.Google Scholar
  25. Sellers, P.J., Hall, F.G., Asrar, G., Strebel, D.E., and Murphy, R.E., (1992) ‘An overview of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE)’ Journal of Geophysical Research, 97, 18,371.Google Scholar
  26. Shuttleworth, W.J., (1991). ‘Insight from large-scale observational studies of land/atmosphere interactions’ In: Wood, E.F. (ed.) Land Surface-Atmosphere Interactions for Climate Modeling: Observations, Models and Analysis. Kluwer, Dordrecht, p. 3–20.CrossRefGoogle Scholar
  27. Travis, D.J., (1997). ‘An investigation of Wisconsin’s anthropogenically-generated convergence boundary and possible influences on climate’ Wisconsin Geogr., 12, 34–46.Google Scholar
  28. Wetzel, P.J., Argentini, S., and Boone, A., (1996) ‘Role of land surface in controlling daytime cloud amount: two case studies in the GCIP-SW area’ J. Geophys. Res., 101, 7359–7370.CrossRefGoogle Scholar
  29. Yeh, T-C., Wetherald, R.T. and Manabe, S., (1984) ‘The effect of soil moisture on the short-term climate and hydrology change- a numerical experiment’ Mon. Weath. Rev., 112, 474–490.CrossRefGoogle Scholar

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • J. O. Adegoke
    • 1
  • A. M. Carleton
    • 1
  1. 1.Department of Geography and Earth System Science CenterThe Pennsylvania State UniversityUniversity ParkUSA

Personalised recommendations