Open AccessAdaptive Soil Moisture Profile Filtering for Horizontal Information Propagation in the Independent Column-Based CLM2.0
Author(s) -
Gabriëlle J. M. De Lannoy,
Paul R. Houser,
Niko Verhoest,
Valentijn R. N. Pauwels
Publication year - 2009
Publication title -
journal of hydrometeorology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.733
H-Index - 123
eISSN - 1525-755X
pISSN - 1525-7541
DOI - 10.1175/2008jhm1037.1
Subject(s) - data assimilation , covariance , ensemble kalman filter , a priori and a posteriori , mathematics , water content , environmental science , statistics , kalman filter , soil science , meteorology , extended kalman filter , geology , geography , philosophy , geotechnical engineering , epistemology
Data assimilation aims to provide an optimal estimate of the overall system state, not only for an observed state variable or location. However, large-scale land surface models are typically column-based and purely random ensemble perturbation of states will lead to block-diagonal a priori (or background) error covariance. This facilitates the filtering calculations but compromises the potential of data assimilation to influence (unobserved) vertical and horizontal neighboring state variables. Here, a combination of an ensemble Kalman filter and an adaptive covariance correction method is explored to optimize the variances and retrieve the off-block-diagonal correlations in the a priori error covariance matrix. In a first time period, all available soil moisture profile observations in a small agricultural field are assimilated into the Community Land Model, version 2.0 (CLM2.0) to find the adaptive second-order a priori error information. After that period, only observations from single individual soil profiles are assimilated with inclusion of this adaptive information. It is shown that assimilation of a single profile can partially rectify the incorrectly simulated soil moisture spatial mean and variability. The largest reduction in the root-mean-square error in the soil moisture field varies between 7% and 22%, depending on the soil depth, when assimilating a single complete profile every two days during three months with a single time-invariant covariance correction