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This article in VZJ

  1. Vol. 12 No. 3
     
    Received: May 15, 2012
    Published: January 28, 2013


    * Corresponding author(s): hanxj@lzb.ac.cn
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doi:10.2136/vzj2012.0072

Joint Assimilation of Surface Temperature and L-Band Microwave Brightness Temperature in Land Data Assimilation

  1. Xujun Han ,
  2. Harrie-Jan Hendricks Franssenb,
  3. Xin Lia,
  4. Yanlin Zhanga,
  5. Carsten Montzkab and
  6. Harry Vereeckenb
  1. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu 730000, PR China
    Forschungszentrum Jülich, Agrosphere (IBG 3), Leo-Brandt-Strasse, 52425 Jülich, Germany

Abstract

Brightness temperature and land surface temperature are two important remote sensing assimilation data sources. Several land data assimilation experiments were proposed to evaluate the impact of their joint assimilation on the soil moisture and soil temperature profiles, and characterization of surface fluxes

Soil moisture and soil temperature are tightly coupled variables in land surface models. The objective of this study was to evaluate the impact of the joint assimilation of soil moisture and land surface temperature data in a land surface model on soil moisture and soil temperature characterization. Three synthetic tests evaluated the joint assimilation of surface temperature (measured by MODIS) and brightness temperature (from L-band) into the Community Land Model using the local ensemble transform Kalman filter (LETKF). The following three tests were performed for dry and wet conditions: (i) assimilating surface temperature observations only; (ii) assimilating brightness temperature observations only; and (iii) assimilating both surface temperature and brightness temperature observations. The results show that the joint assimilation of surface temperature and brightness temperature results in the best characterization of soil moisture and soil temperature profiles under dry conditions. The assimilation of surface temperature contributed to an improved characterization of soil moisture profiles under dry conditions. For the dry period, brightness temperature assimilation resulted in improved prediction of sensible and latent heat fluxes, whereas surface temperature assimilation improved only the prediction of latent heat flux. Under wet conditions, the joint assimilation scheme cannot outperform the single brightness temperature assimilation. Neither the estimation of soil moisture and soil temperature profiles nor the estimates of the turbulent fluxes were improved by joint assimilation (compared with assimilation of brightness temperature only) under wet conditions.

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Copyright © 2013. Copyright © by the Soil Science Society of America, Inc.