LIDA: A Land Integrated Data Assimilation Framework for Mapping Land Surface Heat and Evaporative Fluxes by Assimilating Space-Borne Soil Moisture and Land Surface Temperature

摘要

Land surface heat and evaporative fluxes exchanged between the land and atmosphere play a crucial role in the terrestrial water and energy balance. Regional mapping of these fluxes is hampered by the lack of in situ measurements (with the required coverage and duration) and the high spatial heterogeneity. In this paper, we propose a Land Integrated Data Assimilation framework (LIDA) based on the variational data assimilation technique to estimate the key parameters of surface heat and evaporative fluxes by jointly assimilating Soil Moisture Active Passive (SMAP) data and Geostationary Operational Environmental Satellite (GOES) surface temperature data into a coupled parsimonious land water and energy balance model. The method is implemented over an area of 31,500 km(2) in the U.S. Southern Great Plains, and its performance is evaluated through consistency tests, comparison tests, and uncertainty analyses. The maps of retrieved heat and evaporative fluxes are used to analyze a range of feedback mechanisms in land-atmosphere interaction, such as the dependence of evapotranspiration on vegetation and water availability.Key PointsA Land Integrated Data Assimilation framework (LIDA) based on the variational data assimilation technique is proposed LIDA maps surface heat and evaporative fluxes over the U.S. Southern Great Plains by assimilating GOES LST and SMAP SM LIDA estimates the uncertainty of estimated parameters, hence fluxes, by calculating the error covariance matrix of parameters