A Simple Framework for Examining the Interannual Variability of Land Surface Moisture Fluxes

Randal D. Koster Hydrological Sciences Branch, Laboratory for Hydrospheric Processes, NASA/Goddard Space Flight Center, Greenbelt, Maryland

Search for other papers by Randal D. Koster in
Current site
Google Scholar
PubMed
Close
and
Max J. Suarez Climate and Radiation Branch, Laboratory for Atmospheres, NASA/Goddard Space Flight Center, Greenbelt, Maryland

Search for other papers by Max J. Suarez in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

An equation that describes the partitioning of annual mean precipitation into annual mean evaporation and runoff, developed decades ago by Budyko, is used to derive a second equation that relates the interannual variability of evaporation to gross characteristics of the atmospheric forcing. Both Budyko’s original equation and the new variability equation perform well when tested against results from a 20-yr GCM simulation. In these tests, using knowledge of the climatological mean precipitation and net radiation alone, the authors predict the ratio of annual evaporation to annual precipitation with a standard error of 0.10 in nondesert regions, and they predict the ratio of the standard deviation of annual evaporation to that of annual precipitation there with a standard error of 0.14. In analogy with Budyko’s conclusion for the mean hydrological cycle, water and energy availability appear to be the critical factors controlling the interannual variability of surface moisture fluxes. The derived equations suggest, and the GCM results confirm, that the ratio of an evaporation anomaly to the corresponding precipitation anomaly tends to be significantly less than the ratio of mean evaporation to mean precipitation.

Corresponding author address: Dr. Randal D. Koster, Hydrological Sciences Branch, NASA/GSFC, Code 974, Greenbelt, MD 20771.

Email: randal.koster@gsfc.nasa.gov

Abstract

An equation that describes the partitioning of annual mean precipitation into annual mean evaporation and runoff, developed decades ago by Budyko, is used to derive a second equation that relates the interannual variability of evaporation to gross characteristics of the atmospheric forcing. Both Budyko’s original equation and the new variability equation perform well when tested against results from a 20-yr GCM simulation. In these tests, using knowledge of the climatological mean precipitation and net radiation alone, the authors predict the ratio of annual evaporation to annual precipitation with a standard error of 0.10 in nondesert regions, and they predict the ratio of the standard deviation of annual evaporation to that of annual precipitation there with a standard error of 0.14. In analogy with Budyko’s conclusion for the mean hydrological cycle, water and energy availability appear to be the critical factors controlling the interannual variability of surface moisture fluxes. The derived equations suggest, and the GCM results confirm, that the ratio of an evaporation anomaly to the corresponding precipitation anomaly tends to be significantly less than the ratio of mean evaporation to mean precipitation.

Corresponding author address: Dr. Randal D. Koster, Hydrological Sciences Branch, NASA/GSFC, Code 974, Greenbelt, MD 20771.

Email: randal.koster@gsfc.nasa.gov

Save
  • Budyko, M. I., 1958: The Heat Balance of the Earth’s Surface. Translated by N. A. Stepanova, U.S. Dept. of Commerce, 259 pp.

  • ——, 1974: Climate and Life. Academic Press, 508 pp.

  • Charney, J. G., 1975: Dynamics of deserts and drought in the Sahel. Quart. J. Roy. Meteor. Soc.,101, 193–202.

  • Chou, M.-D., and M. Suarez, 1994: An efficient thermal infrared radiation parameterization for use in general circulation models. NASA Tech. Memo. 104606, Vol. 3, 102 pp.

  • Houghton, J. T., L. G. Meira Filho, B. A. Callander, N. Harris, A. Kattenberg, and K. Maskell, Eds., 1996: Climate Change 1995:The Science of Climate Change. Cambridge University Press, 572 pp.

  • Koster, R. D., and M. J. Suarez, 1992: Modeling the land surface boundary in climate models as a composite of independent vegetation stands. J. Geophys. Res.,97, 2697–2715.

  • ——, and ——, 1995: The relative contributions of land and ocean processes to precipitation variability. J. Geophys. Res.,100, 13 775–13 790.

  • ——, and ——, 1996a: The influence of land surface moisture retention on precipitation statistics. J. Climate,9, 2551–2567.

  • ——, and ——, 1996b: Energy and Water Balance Calculations in the Mosaic LSM. NASA Tech. Memo. 104606, Vol. 9, 76 pp.

  • Milly, P. C. D., 1994a: Climate, interseasonal storage of soil water, and the annual water balance. Adv. Water Resour.,17, 19–24.

  • ——, 1994b: Climate, soil water storage, and the average annual water balance. Water Resour. Res.,30, 2143–2156.

  • 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.

  • Ol’dekop, E. M., 1911: Ob isparenii s poverkhnosti rechnykh basseinov (On evaporation from the surface of river basins). Tr. Meteor. Observ. Iur’evskogo Univ. Tartu,4.

  • Schreiber, P., 1904: Uber die Beziehungen zwischen dem Niederschlag und der Wasserfuhrung der Flusse in Mitteleuropa. Z. Meteor.,21 (10).

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1222 399 84
PDF Downloads 709 151 19