• Bonan, G. B., 1996: A land surface model (LSM version 1.0) for ecological, hydrological, and atmospheric studies: Technical description and user's guide. NCAR Tech. Note NCAR/TN-417+STR, 150 pp. [Available from NCAR, P.O. Box 3000, Boulder, CO 80307.].

    • Search Google Scholar
    • Export Citation
  • Bonan, G. B., and L. M. Stillwell-Soller, 1998: Soil water and the persistence of floods and droughts in the Mississippi River basin. Water Resour. Res, 34 , 26932701.

    • Search Google Scholar
    • Export Citation
  • Budyko, M. I., 1956: Heat Balance of the Earth's Surface (in Russian). Gidrometeoizdat, 255 pp.

  • Dai, Y., and Q-C. Zeng, 1997: A land surface model (IAP94) for climate studies. Part I: Formulation and validation in off-line experiments. Adv. Atmos. Sci, 14 , 433460.

    • Search Google Scholar
    • Export Citation
  • Dai, Y., X. Zeng, and R. E. Dickinson, cited 2001: The Common Land Model: Documentation and user's guide. [Available online at http://climate.eas.gatech.edu/dai/clmdoc.pdf.].

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

  • Delworth, T., and S. Manabe, 1988: The influence of potential evaporation on the variabilities of simulated soil wetness and climate. J. Climate, 1 , 523547.

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

  • Delworth, T., and S. Manabe, 1993: Climate variability and land-surface processes. Adv. Water Resour, 16 , 320.

  • Dickinson, R. E., 2000: How coupling of the atmosphere to ocean and land helps determine the timescales of interannual variability of climate. J. Geophys. Res, 105 , 2011520119.

    • Search Google Scholar
    • Export Citation
  • Dickinson, R. E., A. Henderson-Sellers, and P. J. Kennedy, 1993: Biosphere– Atmosphere Transfer Scheme (BATS) version 1e as coupled to the NCAR Community Climate Model. NCAR Tech. Note NCAR/TN-387+STR, 72 pp. [Available from NCAR, P.O. Box 3000, Boulder, CO 80307.].

    • Search Google Scholar
    • Export Citation
  • Dickinson, R. E., G. Wang, X. Zeng, and Q. Zeng, 2003: How does the partitioning of evapotranspiration and runoff between different processes affect the variability and predictability of soil moisture and precipitation? Adv. Atmos. Sci, 20 , 475478.

    • Search Google Scholar
    • Export Citation
  • Dirmeyer, P. A., A. J. Dolman, and N. Sato, 1999: The Global Soil Wetness Project: A pilot project for global land surface modeling and validation. Bull. Amer. Meteor. Soc, 80 , 851878.

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

    • Search Google Scholar
    • Export Citation
  • Eltahir, E. A. B., 1998: A soil moisture rainfall feedback mechanism 1. Theory and observations. Water Resour. Res, 34 , 765776.

  • Entin, J. K., A. Robock, K. Y. Vinnikov, S. E. Hollinger, S. Liu, and A. Namkhai, 2000: Temporal and spatial scales of observed soil moisture variations in the extratropics. J. Geophys. Res, 105 , 1186511877.

    • Search Google Scholar
    • Export Citation
  • Findell, K. L., and E. A. B. Eltahir, 1999: Analysis of the pathways relating soil moisture and subsequent rainfall in Illinois. J. Geophys. Res, 104 , 3156531574.

    • Search Google Scholar
    • Export Citation
  • Henderson-Sellers, A., Z-L. Yang, and R. E. Dickinson, 1993: The Project for Intercomparison of Land-Surface Parameterization Schemes (PILPS). Bull. Amer. Meteor. Soc, 74 , 13351349.

    • Search Google Scholar
    • Export Citation
  • Hollinger, S. E., and S. A. Isard, 1994: A soil moisture climatology of Illinois. J. Climate, 7 , 822833.

  • Hong, S. Y., and E. Kalnay, 2000: Role of sea surface temperature and soil-moisture feedback in the 1998 Oklahoma–Texas drought. Nature, 408 , 842844.

    • Search Google Scholar
    • Export Citation
  • Jenkins, G. M., and D. G. Watts, 1968: Spectral Analysis and Its Applications. Holden-Day, 525 pp.

  • Jones, R. H., 1975: Estimating the variance of time averages. J. Appl. Meteor, 14 , 159163.

  • Kiehl, J. T., J. J. Hack, G. B. Bonan, B. A. Boville, D. L. Williamson, and P. J. Rasch, 1998: The National Center for Atmospheric Research Community Climate Model: CCM3. J. Climate, 11 , 11311149.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and M. J. Suarez, 1995: Relative contributions of land and ocean processes to precipitation variability. J. Geophys. Res, 100 , 1377513790.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and M. J. Suarez, 2001: Soil moisture memory in climate models. J. Hydrometeor, 2 , 558570.

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

    • Search Google Scholar
    • Export Citation
  • Liu, Y., and R. Avissar, 1999a: A study of persistence in the land– atmosphere system using a general circulation model and observations. J. Climate, 12 , 21392153.

    • Search Google Scholar
    • Export Citation
  • Liu, Y., and R. Avissar, 1999b: A study of persistence in the land–atmosphere system with a fourth-order analytical model. J. Climate, 12 , 21542168.

    • Search Google Scholar
    • Export Citation
  • Manabe, S., 1969: Climate and the ocean circulation: 1. The atmospheric circulation and the hydrology of the earth's surface. Mon. Wea. Rev, 97 , 739774.

    • Search Google Scholar
    • Export Citation
  • Nicholson, S., 2000: Land surface processes and Sahel climate. Rev. Geophys, 38 , 117139.

  • Oglesby, R. J., S. Marshall, D. J. Erickson III, J. O. Roads, and F. R. Robertson, 2002: Thresholds in atmosphere–soil moisture interactions: Results from climate model studies. J. Geophys. Res.,107, 4224, doi:10.1029/2001JD001045.

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

    • Search Google Scholar
    • Export Citation
  • Robock, A., and Coauthors, 2000: The Global Soil Moisture Data Bank. Bull. Amer. Meteor. Soc, 81 , 12811299.

  • Sellers, P. J., and Coauthors, 1996: A revised land surface parameterization (SiB2) for atmospheric GCMs. Part I: Model formulation. J. Climate, 9 , 676705.

    • Search Google Scholar
    • Export Citation
  • Vinnikov, K. Y., A. Robock, N. A. Speranskaya, and C. A. Schlosser, 1996: Scales of temporal and spatial variability of midlatitude soil moisture. J. Geophys. Res, 101 , 71637174.

    • Search Google Scholar
    • Export Citation
  • Wang, W. Q., and A. Kumar, 1998: A GCM assessment of atmospheric seasonal predictability associated with soil moisture anomalies over North America. J. Geophys. Res, 103 (D22) 2863728646.

    • Search Google Scholar
    • Export Citation
  • Willmott, C. J., K. Matsuura, and D. L. Legates, cited 1998: Global air temperature and precipitation: Regridded monthly and annual climatologies (Version 2.01). [Available online at http://climate.geog.udel.edu/∼climate/html_pages/download.html.].

    • Search Google Scholar
    • Export Citation
  • Wu, W., M. A. Geller, and R. E. Dickinson, 2002: Soil moisture profile variability in response to long-term precipitation. J. Hydrometeor, 3 , 604613.

    • Search Google Scholar
    • Export Citation
  • Zeng, X., R. E. Dickinson, A. Walker, M. Shaikh, R. S. DeFries, and J. Qi, 2000: Derivation and evaluation of global 1-km fractional vegetation cover data for land modeling. J. Appl. Meteor, 39 , 826839.

    • Search Google Scholar
    • Export Citation
  • Zeng, X., M. Shaikh, Y. Dai, and R. E. Dickinson, 2002: Coupling of the Common Land Model to the NCAR Community Climate Model. J. Climate, 15 , 18321854.

    • Search Google Scholar
    • Export Citation
  • Zheng, X. Y., and E. A. B. Eltahir, 1998: A soil moisture rainfall feedback mechanism 2. Numerical experiments. Water Resour. Res, 34 , 777785.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 500 220 13
PDF Downloads 310 170 14

Time Scales of Layered Soil Moisture Memory in the Context ofLand–Atmosphere Interaction

View More View Less
  • 1 School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia
Restricted access

Abstract

The time scales of layered soil moisture memory in the Common Land Model (CLM) coupled with the National Center for Atmospheric Research Community Climate Model, version 3 (NCAR CCM3) have been examined using a 50-yr climate simulation. Such soil moisture memory has been characterized in terms of the spatial, seasonal, and vertical variations of 1-month-lag autocorrelation coefficients and the corresponding e-folding decay time scales. To understand this land memory mechanism, in terms of the variations that occur in the model, a cross-spectral analysis has been applied to the soil moisture profile with precipitation (P), runoff (R), evapotranspiration (ET), transpiration, and the residual of P − ET − R, respectively, together with an examination of the surface water budget of the annual cycle. These collectively provide physical insights on time scales of layered soil moisture memory in the context of land–atmosphere interaction. The major findings are: 1) soil moisture memory in warm climates can be at least several times longer for drier conditions than when it is sufficiently rainy; and 2) under wet conditions the time scales of soil moisture appear to be controlled by temperature-dependent climatic demand; but for drier conditions they appear to depend largely on increasing time scales for the coupling of soil moisture to ET and especially runoff.

Corresponding author address: Dr. Wanru Wu, School of Earth and Atmospheric Sciences, Georgia Institute of Technology, 311 Ferst Drive, Atlanta, GA 30332-0340. Email: wwu@eas.gatech.edu

Abstract

The time scales of layered soil moisture memory in the Common Land Model (CLM) coupled with the National Center for Atmospheric Research Community Climate Model, version 3 (NCAR CCM3) have been examined using a 50-yr climate simulation. Such soil moisture memory has been characterized in terms of the spatial, seasonal, and vertical variations of 1-month-lag autocorrelation coefficients and the corresponding e-folding decay time scales. To understand this land memory mechanism, in terms of the variations that occur in the model, a cross-spectral analysis has been applied to the soil moisture profile with precipitation (P), runoff (R), evapotranspiration (ET), transpiration, and the residual of P − ET − R, respectively, together with an examination of the surface water budget of the annual cycle. These collectively provide physical insights on time scales of layered soil moisture memory in the context of land–atmosphere interaction. The major findings are: 1) soil moisture memory in warm climates can be at least several times longer for drier conditions than when it is sufficiently rainy; and 2) under wet conditions the time scales of soil moisture appear to be controlled by temperature-dependent climatic demand; but for drier conditions they appear to depend largely on increasing time scales for the coupling of soil moisture to ET and especially runoff.

Corresponding author address: Dr. Wanru Wu, School of Earth and Atmospheric Sciences, Georgia Institute of Technology, 311 Ferst Drive, Atlanta, GA 30332-0340. Email: wwu@eas.gatech.edu

Save