This title appears in the Scientific Report :
2014
Land surface temperature assimilation and verification at Rur catchement
Land surface temperature assimilation and verification at Rur catchement
The 1 km remote sensing products of Land Surface Temperature (LST) are available operationally from MODIS (Moderate-resolution Imaging Spectroradiometer). There are four measurements per day from MODIS Terra/Aqua sensors with low measurement error (around 1 K). In this study, MODIS LST products were...
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Personal Name(s): | Han, Xujun (Corresponding Author) |
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Hendricks-Franssen, Harrie-Jan / Bogena, Heye / Vereecken, Harry | |
Contributing Institute: |
Agrosphäre; IBG-3 |
Published in: | 2014 |
Imprint: |
2014
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Conference: | TERENO International Conference 2014, Bonn (Germany), 2014-09-29 - 2014-10-02 |
Document Type: |
Conference Presentation |
Research Program: |
Terrestrial Systems: From Observation to Prediction Modelling and Monitoring Terrestrial Systems: Methods and Technologies |
Publikationsportal JuSER |
The 1 km remote sensing products of Land Surface Temperature (LST) are available operationally from MODIS (Moderate-resolution Imaging Spectroradiometer). There are four measurements per day from MODIS Terra/Aqua sensors with low measurement error (around 1 K). In this study, MODIS LST products were assimilated into the Community Land Model (CLM) to improve the soil moisture, soil temperature, latent and sensible fluxes estimation. Remote sensing of soil moisture has severe limitations for the Rur catchment given the spatially highly variable landuse distribution and coarse resolution of passive microwave remote sensing; LST assimilation could be an alternative for the improvement of soil moisture simulation given the coupled water and energy balances at the land surface. In this study the assimilation algorithm Local Ensemble Transform Kalman Filter (LETKF) with the state augmentation method is used. Vegetation and soil properties are also updated in some simulation scenarios. Besides soil temperature, also soil moisture is explicitly updated by LETKF on the basis of the LST-measurements. The atmospheric forcing data, vegetation properties (leaf area index, etc.) and soil properties (sand and clay fraction, etc.) are randomized to represent the model uncertainties. The assimilation results were evaluated against measured soil moisture, soil temperature and latent and sensible heat fluxes obtained for the Eifel/Lower Rhine Valley Observatory of TERENO. |