HR: 11:50h
AN: H41H-07    [PDF]
TI: Multiscale Kalman Filter for Optimal Assimilation of Near-Surface Soil Moisture into VIC-3L
AU: * Parada, L M
EM: lparada@uclink.berkeley.edu
AF: University of California, Berkeley, Civil and Environmental Engineering 631 Davis Hall, Berkeley, CA 94720 United States
AU: Liang, X
EM: liang@ce.berkeley.edu
AF: University of California, Berkeley, Civil and Environmental Engineering 631 Davis Hall, Berkeley, CA 94720 United States
AB: We undertake an alternative and novel approach to assimilation of near-surface soil moisture into land surface models by means of an extension of multiscale Kalman filtering (MKF). While most data assimilation studies rely on the assumption of spatially independent near-surface soil moisture observations to attain a computationally tractable problem, MKF allows us to explicitly and very efficiently model the spatial dependence and scaling properties of near-surface soil moisture fields. Additionally, the Expectation Maximization (EM) algorithm is used in conjunction with MKF so that the statistical parameters inherent to the assimilation algorithm may be optimally determined directly from the data at hand and allowed to vary over time. This constitutes a significant advantage since these parameters (e.g., observation and model error noise variances) largely determine the performance of the assimilation approach and have so far been most commonly prescribed heuristically and not allowed to evolve in time. We apply MKF to assimilate the near-surface soil moisture fields derived from ESTAR during the Southern Great Plains Hydrology experiment of 1997 (SGP97) into the Three-layer Variable Infiltration Capacity (VIC-3L) hydrologically based land surface model. We extensively test the relevance of using optimal statistical parameters for assimilation and thoroughly evaluate the effect that the spatial resolution of the ESTAR data has on improving the predictive capabilities of VIC-3L. The results obtained show that assimilation greatly improves the spatial structure of near-surface soil moisture as predicted by VIC-3L. Moreover, VIC-3L seems capable of conveying the assimilated information forward in time. Significant impacts on the way VIC-3L partitions energy fluxes are also observed to result from assimilation of near-surface soil moisture.
DE: 1640 Remote sensing
DE: 1836 Hydrologic budget (1655)
DE: 1866 Soil moisture
DE: 1869 Stochastic processes
DE: 1878 Water/energy interactions
SC: Hydrology [H]
MN: 2003 Fall Meeting