Submitted to: Journal of Hydrometeorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/1/2004
Publication Date: 12/15/2005
Citation: Crow, W.T., Kustas, W.P., Li, F. 2005. Intercomparison of spatially disturbed models for predicting surface energy flux patterns during SMACEX. Journal of Hydrometerorology. 6(6):941-954. Interpretive Summary: A wide variety of land surface models are currently available to make spatially distributed predictions of surface energy fluxes. While the number and complexity of these approaches continues to grow, relatively little work has focused on the intercomparison of existing approaches. Data sets collected during the 2002 Soil Moisture Atmosphere Coupling Experiment (SMACEX) provide a unique opportunity to assess the ability of contrasting model to accurately predict spatial variations in surface energy fluxes patterns over agricultural areas. Results demonstrate the relative accuracy of models and illustrates opportunities for improving model performance via model calibration and data assimilation techniques.
Technical Abstract: The treatment of aerodynamic surface temperature in surface vegetation atmosphere transfer (SVAT) models can be used to classify approaches into two broad categories. The first category contains models utilizing remote sensing (RS) observations of surface radiometric temperature to estimate aerodynamic surface temperature and solve for surface energy fluxes. The second category contains combined water and energy balance (WEB) approaches that simultaneously solve for surface temperature and energy fluxes based on observations of incoming radiation, precipitation, and micro-meteorological variables. To date, few studies have focused on intercomparing models from each category. Land surface and remote sensing data sets collected during the 2002 Soil Moisture Atmosphere Coupling Experiment (SMACEX) provide an opportunity to evaluate and intercompare spatially distributed surface energy balance models. Intercomparison results presented here focus on the ability of a WEB-SVAT approach (the TOPmodel-based Land Atmosphere Transfer Scheme - TOPLATS) and a RS-SVAT approach (the Two-Source Energy Balance model - TSEB) to accurately predict patterns of turbulent energy fluxes observed during SMACEX. During the experiment, TOPLATS and TSEB latent heat flux predictions match flux tower observations with a root-mean-square (RMS) accuracy of 64 and 67 Wm^-2, respectively. TSEB prediction of sensible heat flux, however, are significantly more accurate with an RMS accuracy of 24 Wm^-2 versus 48 Wm^-2 for TOPLATS. Intercomparisons of flux predictions from each models suggests the models errors from each approach are sufficiently independent that significant opportunities for improving the spatial performance of both models exist via data assimilation and model calibration techniques.