Assimilation of 3D radar reflectivities with an ensemble Kalman filter on the convective scale
| Autor: | Theresa Bick, Hendrik Reich, Ulrich Blahak, Silke Trömel, Clemens Simmer, Klaus Stephan, Yuefei Zeng, Christoph Schraff, Harrie-Jan Hendricks Franssen, Kathrin Wapler, Roland Potthast |
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| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Atmospheric Science
010504 meteorology & atmospheric sciences Meteorology 0208 environmental biotechnology 02 engineering and technology Kalman filter Numerical weather prediction 01 natural sciences 020801 environmental engineering law.invention Noise Data assimilation Brier score law Climatology ddc:550 3D radar Environmental science Ensemble Kalman filter Radar 0105 earth and related environmental sciences |
| Zdroj: | Quarterly journal of the Royal Meteorological Society 142(696), 1490-1504 (2016). doi:10.1002/qj.2751 |
| ISSN: | 1477-870X |
| Popis: | An ensemble data assimilation system for 3D radar reflectivity data is introduced for the convection-permitting numerical weather prediction model of the COnsortium for Small-scale MOdelling (COSMO) based on the Kilometre-scale ENsemble Data Assimilation system (KENDA), developed by Deutscher Wetterdienst and its partners. KENDA provides a state-of-the-art ensemble data assimilation system on the convective scale for operational data assimilation and forecasting based on the Local Ensemble Transform Kalman Filter (LETKF). In this study, the Efficient Modular VOlume RADar Operator is applied for the assimilation of radar reflectivity data to improve short-term predictions of precipitation. Both deterministic and ensemble forecasts have been carried out. A case-study shows that the assimilation of 3D radar reflectivity data clearly improves precipitation location in the analysis and significantly improves forecasts for lead times up to 4 h, as quantified by the Brier Score and the Continuous Ranked Probability Score. The influence of different update rates on the noise in terms of surface pressure tendencies and on the forecast quality in general is investigated. The results suggest that, while high update rates produce better analyses, forecasts with lead times of above 1 h benefit from less frequent updates. For a period of seven consecutive days, assimilation of radar reflectivity based on the LETKF is compared to that of DWD's current operational radar assimilation scheme based on latent heat nudging (LHN). It is found that the LETKF competes with LHN, although it is still in an experimental phase. |
| Databáze: | OpenAIRE |
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