HR: 1340h
AN: H13C-0435    [Abstracts]
TI: Estimation of Rootzone Soil Moisture and Land Surface Fluxes From Reference-Level Micrometeorology and Boundary Layer Observations
AU: * Huang, H
EM: hyhuang@ucla.edu
AF: UCLA, 5732D Boelter Hall; Department Civil and Environmental Engineering, Los Angeles, CA 90095
AU: Margulis, S A
EM: margulis@seas.ucla.edu
AF: UCLA, 5732D Boelter Hall; Department Civil and Environmental Engineering, Los Angeles, CA 90095
AB: Rootzone soil moisture is the key land surface state due to its role in partitioning both the incoming radiation into latent and sensible heat fluxes and precipitation into infiltration, runoff, and subsequent evapotranspiration. These surface fluxes of moisture and energy are complex functions of uncertain atmospheric forcing and land surface characteristics (vegetation and soil properties). Because of the strong coupling between the land surface and overlying atmospheric boundary layer, valuable information about subsurface states and surface fluxes is contained in readily-available surface layer and boundary layer observations (micrometeorological temperature and humidity, radiosonde data, satellite-based soundings, etc.). In this study we apply the Ensemble Kalman Filter with a coupled land surface boundary layer model to assimilate micrometeorological and boundary layer observations to estimate rootzone soil moisture. Using the coupled model requires minimal auxiliary information and variables that are typically required as forcing for offline models can instead be assimilated, providing a further constraint on the flux estimates. The method is applied to the Central Facility region of the Southern Great Plains 1997 (SGP97) field experiment site. Synthetic experiments are performed to assess the performance of the assimilation method in both moisture-limited and energy-limited regimes and under uncertain and biased model parameters (soil hydraulic properties, vegetation characteristics, etc.) and forcing (radiation and precipitation). The ensemble approach is shown to not only provide reasonable estimates of mean rootzone soil moisture over time, but can also track its uncertainty, which is a complicated function of time as a result of model input uncertainty. By constraining the rootzone soil moisture, significant improvements in the surface turbulent fluxes are also seen. Results when assimilating the real SGP97 data also show significant improvements in rootzone soil moisture and surface flux estimates over simple forward modeling. The results from the simple coupled model used here indicate the potential for extension of this approach to large scale applications using more complex mesoscale models.
DE: 3322 Land/atmosphere interactions
DE: 3307 Boundary layer processes
DE: 1818 Evapotranspiration
DE: 1866 Soil moisture
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting