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Estimating the soil moisture profile by assimilating near-surface observations with the ensemble Kaiman filter (EnKF)

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Abstract

The paper investigates the ability to retrieve the true soil moisture profile by assimilating near-surface soil moisture into a soil moisture model with an ensemble Kaiman filter (EnKF) assimilation scheme, including the effect of ensemble size, update interval and nonlinearities in the profile retrieval, the required time for full retrieval of the soil moisture profiles, and the possible influence of the depth of the soil moisture observation. These questions are addressed by a desktop study using synthetic data. The “true” soil moisture profiles are generated from the soil moisture model under the boundary condition of 0.5 cm d−1 evaporation. To test the assimilation schemes, the model is initialized with a poor initial guess of the soil moisture profile, and different ensemble sizes are tested showing that an ensemble of 40 members is enough to represent the covariance of the model forecasts. Also compared are the results with those from the direct insertion assimilation scheme, showing that the EnKF is superior to the direct insertion assimilation scheme, for hourly observations, with retrieval of the soil moisture profile being achieved in 16 h as compared to 12 days or more. For daily observations, the true soil moisture profile is achieved in about 15 days with the EnKF, but it is impossible to approximate the true moisture within 18 days by using direct insertion. It is also found that observation depth does not have a significant effect on profile retrieval time for the EnKF. The nonlinearities have some negative influence on the optimal estimates of soil moisture profile but not very seriously.

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Authors and Affiliations

  1. School of Atmospheric Sciences, Lanzhou University, 730000, Lanzhou

    Zhang Shuwen & Qiu Chongjian

  2. Key Laboratory of Arid Climatic Changing and Reducing Disaster of Gansu Province, 730020, Lanzhou

    Zhang Shuwen, Li Haorui & Qiu Chongjian

  3. School of Physical Sciences and Technology, Lanzhou University, 730000, Lanzhou

    Zhang Weidong

  4. Gold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, 730000, Lanzhou

    Li Xin

Authors
  1. Zhang Shuwen
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  2. Li Haorui
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  3. Zhang Weidong
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  4. Qiu Chongjian
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  5. Li Xin
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Correspondence to Zhang Shuwen.

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Shuwen, Z., Haorui, L., Weidong, Z. et al. Estimating the soil moisture profile by assimilating near-surface observations with the ensemble Kaiman filter (EnKF). Adv. Atmos. Sci. 22, 936–945 (2005). https://doi.org/10.1007/BF02918692

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  • DOI: https://doi.org/10.1007/BF02918692

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