Towards a Kalman Filter based soil moisture analysis system for the operational ECMWF Integrated Forecast System

This paper presents the future European Centre for Medium‐Range Weather Forecasts soil moisture analysis system based on a point‐wise Extended Kalman Filter (EKF). The performance of the system is evaluated against the current operational Optimal Interpolation (OI) system. Both systems use proxy obs...

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Bibliographic Details
Published in:Geophysical research letters 2009-05, Vol.36 (10), p.n/a
Main Authors: Drusch, M., Scipal, K., de Rosnay, P., Balsamo, G., Andersson, E., Bougeault, P., Viterbo, P.
Format: Article
Language:English
Subjects:
Air temperature
Atmosphere
Atmospheric sciences
data assimilation
Earth sciences
Earth, ocean, space
Evaporation
Exact sciences and technology
Hydrology
Land
Moisture content
Relative humidity
Remote sensing
Soil analysis
Soil moisture
Soils
Spatial analysis
Transpiration
Weather forecasting
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Summary:This paper presents the future European Centre for Medium‐Range Weather Forecasts soil moisture analysis system based on a point‐wise Extended Kalman Filter (EKF). The performance of the system is evaluated against the current operational Optimal Interpolation (OI) system. Both systems use proxy observations, i.e., 2 m air temperature and relative humidity. The spatial structure of the analysis increments obtained from both analyses are comparable. However, the EKF‐based increments are generally higher for the top soil layers then for the bottom layer. This gradient better reflects the underlying hydrological processes in that the strongest interaction between soil moisture and bare soil evaporation and transpiration through vegetation should occur in top layers where most of the roots are located. The impact on the forecast skill, e.g., air temperature at 2 m and 500 hPa height, is neutral. The new EKF surface analysis system offers a range of further development options for the exploitation of satellite observations for the initialization of the land surface in Numerical Weather Prediction.
ISSN:0094-8276
1944-8007
DOI:10.1029/2009GL037716