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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/gmd-2018-273
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2018-273
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model evaluation paper 09 Jan 2019

Submitted as: model evaluation paper | 09 Jan 2019

Assimilation of SCATSAR Soil Wetness Index in SURFEX 8.0 to improve weather forecasts

Stefan Schneider1 and Bernhard Bauer-Marschallinger2 Stefan Schneider and Bernhard Bauer-Marschallinger
  • 1ZAMG, Vienna, 1190, Austria
  • 2TU Wien, Vienna, 1040, Austria

Abstract. To date, in numerical weather prediction models it has only been possible to assimilate surface soil moisture data. Due to the structure of this surface soil layer in soil models, the effect of the assimilation vanishes fast. This results in a small impact on model performance. Here we present a combination of two new developments to overcome this problem. On the one hand, a new satellite based soil moisture data set is assimilated that combines the advantages of two different sensors (MetOp ASCAT and Sentinel-1 SAR) and the so-called T-value approach to estimate the soil moisture content of deeper soil layers. On the other hand, an advanced version of the well-established SURFEX soil model data assimilation software is used to ingest this new data source for improved short-range weather forecasts. Comparisons of the two data sets from satellite and soil model indicate that the estimation of deep soil moisture from superficial measurements produces reasonable estimates down to 0.5 m. Assimilation experiments with a simplified Extended Kalman Filter for a model domain covering Austria shows the benefit of this new combination with improved verification scores for temperature and relative humidity forecasts at 2 m above ground.

Stefan Schneider and Bernhard Bauer-Marschallinger
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Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Stefan Schneider and Bernhard Bauer-Marschallinger
Stefan Schneider and Bernhard Bauer-Marschallinger
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Latest update: 06 Dec 2019
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Short summary
This paper investigates the question if satellite-measured soil moisture data are useful to improve weather forecasts. To answer this question, historical forecasts are re-computed with and without this additional data source and compared against measurements from weather stations. This test shows an positive impact of using soil moisture data which indicates that they should be used operationally in regional weather forecast models.
This paper investigates the question if satellite-measured soil moisture data are useful to...
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