Estimation of land surface water and energy balance flux components and closure relation using conditional sampling

Abstract

Models of terrestrial water and energy balance include numerical treatment of heat and moisture diffusion in the soil-vegetation-atmosphere continuum. These two diffusion and exchange processes are linked only at a few critical points. The performance and sensitivity of models are highly dependent on the nature of these linkages that are expressed as the closure function between heat and moisture dynamics. Land response to radiative forcing and partitioning of available energy into sensible and latent heat fluxes are dependant on the functional form. Since the function affects the surface fluxes, the influence reaches through the boundary layer and affects the lower atmosphere weather. As important as these closure functions are, they remain essentially empirical and untested across diverse conditions. It is critically important to develop observation-driven estimation procedures for the terrestrial water and energy closure problem, especially at the scale of modeling and with global coverage. In this dissertation a new approach to the estimation of key unknown parameters of water and energy balance equation and their closure relationship is introduced. This approach is based on averaging of heat and moisture diffusion equations conditioned on land surface temperature and moisture states respectively. The method is derived only from statistical stationarity and conservation statements of water and energy and thus it is scale free. The aim of this dissertation is to establish the theoretical basis for the approach and perform a global test using multi-platform remote sensing measurements. The feasibility of this approach is demonstrated at point-scale using synthetic data and flux-tower field site data. The method is applied to the mesoscale region of Gourma (West Africa) using multi-platform remote sensing data. The retrievals were verified against tower-flux field site data and physiographic characteristics of the region. The approach is used to find the functional form of the Evaporative Fraction (ratio of latent heat flux to sum of latent and sensible heat fluxes) dependence on soil moisture. Evaporative Fraction is a key closure function for surface and subsurface heat and moisture dynamics. With remote sensing data the dependence of this function on governing soil and vegetation characteristics is established.