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United States Department of Agriculture

Agricultural Research Service

Title: Effects of Surface Temperature Contrast on Land-Atmosphere Exchage: a Case Study from Monsoon 90

Authors
item Kustas, William
item Albertson, John - DUKE UNIVERSITY

Submitted to: Water Resource Center Publication
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 11, 2002
Publication Date: June 18, 2003
Citation: Kustas, W.P., Albertson, J.D. 2003. Effects of surface temperature contrast on land-atmosphere exchange: A case study from Monsoon 90. Water Resources Research. 39(6):1159, doi:10.1029/2001WR001226.

Interpretive Summary: A modeling framework to explore the interaction between the land and the lower atmosphere using a large eddy simulation (LES) model, which simulates the 3-dimensional atmospheric turbulence field, with remotely sensed land surface images is used to evaluate the impacts of changes in the magnitude of surface variability (i.e. spatial contrasts) on lower atmospheric properties. We focus our simulations and analysis with re-scaled surface temperature fields to explore a wider range of contrasts (i.e. spatial variance). We demonstrate that the increase in temperature contrast has negligible effect on regionally averaged fluxes. However, the strength of coupling (or feedback) between spatial fields of land surface and surface layer temperature (z ~ 10 m) increases with increasing temperature contrast. This dampens increases in the spatial variance in heat fluxes relative to increases in the spatial variance in surface temperature, suggesting the feedbacks act to limit the spatial variability in the fluxes. We also use the LES to explore the errors induced in spatially distributed heat flux predictions from using spatially uniform atmospheric variables commonly employed when computing surface fluxes from remotely sensed land surface data. This leads to significant differences in the spatial distribution of land surface fluxes when compared to LES derived fluxes. This effort reflects a merging of active lines of research using remotely sensed land surface properties to study water and energy fluxes and the use of LES to study impacts of surface variability on the lower atmosphere. This is a fundamental step in addressing the effects of agricultural management practices on local and regional climate and in the development of mitigative strategies for sustainable agriculture.

Technical Abstract: Atmospheric boundary layer (ABL) simulations over remotely sensed boundary conditions using a Large Eddy Simulation (LES) code are employed here to explore the dynamical coupling of heterogeneous land surfaces and the ABL. The LES was recently extended to incorporate remotely observed surface states, and the ability to account for the soil and vegetation (i.e. two sources) contributions to the mass and energy exchanges (Albertson et al., 2001). In this effort we explore the impacts of changes in the magnitude of surface variability (i.e. spatial contrasts). We focus our simulations and analysis with re-scaled surface temperature fields to explore a wider range of contrasts (i.e. spatial variance). We demonstrate that the increase in temperature contrast has negligible effect on regionally averaged fluxes. However, the strength of coupling (or feedback) between spatial fields of land surface and surface layer temperature (z ~ 10 m) increases with increasing temperature contrast. This dampens increases in the spatial variance in the sensible heat flux relative to increases in the spatial variance in surface temperature, suggesting the feedbacks act to limit the spatial variability in the flux. We also use the LES to explore the errors induced in spatially distributed heat flux predictions from using spatially uniform atmospheric variables in a related two-source-energy-balance scheme. The use of spatially uniform atmospheric variables is commonly employed when computing surface fluxes from remotely sensed land surface data. This leads to significant differences in the spatial distribution of land surface fluxes when compared to LES derived fluxes. This was particularly evident in the overestimated Bowden ratio, primarily for locations with relatively low vegetation cover.

Last Modified: 10/22/2014
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