HR: 1340h
AN: H33C-0478    [Abstracts]
TI: Assimilating Terrestrial Hydrologic Fluxes Into Land Surface Models Using Remote Sensing Data Products
AU: Kumar, P
EM: kumar1@uiuc.edu
AF: Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N Mathews Avenue, Urbana, IL 61801 United States
AU: * Chintalapati, S
EM: chintala@uiuc.edu
AF: Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N Mathews Avenue, Urbana, IL 61801 United States
AB: The state of the land surface plays a critical role in the land-atmosphere interactions, through the dynamic evolution of moisture and energy fluxes at the land surface. The current generation of Land Surface Models (LSMs) estimating these fluxes, however sophisticatedly parameterized they might be, are still constrained by the underlying approximate model physics. With the advent of a variety of land surface remote sensing (LSRS) data products, better estimations of the dynamic state can be obtained by integrating (assimilating) these LSRS products into the predictive models. Numerous techniques at various levels of sophistication have been developed for assimilating remotely sensed near surface soil moisture into LSMs, based on the knowledge about the errors in the model predictions and observations, to update the soil moisture profile and associated fluxes. Though a lot of research is being done to obtain remotely sensed near surface soil moisture as a reliable data product, the current coverage and spatial and temporal scales of the same have limited applications in land surface modeling. However, several other LSRS products are available as reliable global coverage data at desired spatial and temporal scales, which can be incorporated either directly or indirectly into LSMs to obtain reliable estimates of moisture and energy fluxes. In the present work, we use LSRS products which have been derived from radiation measurements by MODIS (MODerate-resolution Imaging Spectrometer) instrument flying on Terra and Aqua satellite platforms. The LSRS products are: Land Surface Temperature (LST), Surface Albedo, Vegetation Indices (NDVI/EVI), Fractional Vegetation Cover and Leaf Area Index (LAI). We use these data products and other boundary layer variables, as surrogate data to provide an index to the energy fluxes, using the Surface Energy Balance System (SEBS) framework, which is then used to update the soil moisture profile and associated fluxes at relevant scales. The SEBS framework [Su et al., 2001; Li et al., 2003] will be used in conjunction with LSM, so as to take advantage of the more accurate parameterization from SEBS and the underlying physics representation in LSM, thus developing a blended system.
DE: 3322 Land/atmosphere interactions
DE: 3360 Remote sensing
DE: 1800 HYDROLOGY
DE: 1818 Evapotranspiration
DE: 1833 Hydroclimatology
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting