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Open AccessArticle

Short-Range Numerical Weather Prediction of Extreme Precipitation Events Using Enhanced Surface Data Assimilation

Swedish Meteorological and Hydrological Institute, 601 76 Norrköping, Sweden
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Atmosphere 2019, 10(10), 587; https://doi.org/10.3390/atmos10100587
Received: 22 August 2019 / Revised: 23 September 2019 / Accepted: 24 September 2019 / Published: 27 September 2019
A limited-area kilometre scale numerical weather prediction system is applied to evaluate the effect of refined surface data assimilation on short-range heavy precipitation forecasts. The refinements include a spatially dependent background error representation, use of a flow-dependent data assimilation technique, and use of data from a satellite-based scatterometer instrument. The effect of the enhancements on short-term prediction of intense precipitation events is confirmed through a number of case studies. Verification scores and subjective evaluation of one particular case points at a clear impact of the enhanced surface data assimilation on short-range heavy precipitation forecasts and suggest that it also tends to slightly improve them. Although this is not strictly statistically demonstrated, it is consistent with the expectation that a better surface state should improve rainfall forecasts. View Full-Text
Keywords: numerical weather prediction; surface data assimilation; Kalman filter; scatterometer; severe weather numerical weather prediction; surface data assimilation; Kalman filter; scatterometer; severe weather
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Lindskog, M.; Landelius, T. Short-Range Numerical Weather Prediction of Extreme Precipitation Events Using Enhanced Surface Data Assimilation. Atmosphere 2019, 10, 587.

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