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Short time augmented extended Kalman filter for soil analysis: a feasibility study

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Abstract

This paper presents a soil analysis scheme based on an extended Kalman filter (EKF), the short time augmented extended Kalman filter (STAEKF), where the model parameters are estimated along with the system state. We use an off-line version of the interaction soil-biosphere-atmosphere model for the assimilation of screen-level temperature and relative humidity. The leaf area index, the albedo, and the minimum stomatal resistance are estimated with the STAEKF. Results show that the STAEKF gives encouraging results and indicate the benefit of the simultaneous estimation of the state and parameters in soil data assimilation. Copyright © 2012 Royal Meteorological Society

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