Model Error Representation Using the Stochastically Perturbed Hybrid Physical-Dynamical Tendencies in Ensemble Data Assimilation System
- 주제(키워드) model error , ensemble data assimilation , stochastic perturbation , stochastic perturbed hybrid tendencies scheme , dynamical tendency , physical tendency
- 주제(기타) Chemistry, Multidisciplinary
- 주제(기타) Engineering, Multidisciplinary
- 주제(기타) Materials Science, Multidisciplinary
- 주제(기타) Physics, Applied
- 설명문(일반) [Lim, Sujeong; Park, Seon Ki] Ewha Womans Univ, Dept Climate & Energy Syst Engn, Seoul 03760, South Korea; [Lim, Sujeong; Koo, Myung-Seo; Kwon, In-Hyuk] Korea Inst Atmospher Predict Syst KIAPS, Seoul 07071, South Korea; [Park, Seon Ki] Ewha Womans Univ, Dept Environm Sci & Engn, Seoul 03760, South Korea; [Park, Seon Ki] Ewha Womans Univ, Severe Storm Res Ctr, Seoul 03760, South Korea; [Park, Seon Ki] Ewha Womans Univ, Ctr Climate Environm Change Predict Res, Seoul 03760, South Korea
- 등재 SCIE, SCOPUS
- OA유형 gold, Green Published
- 발행기관 MDPI
- 발행년도 2020
- 총서유형 Journal
- URI http://www.dcollection.net/handler/ewha/000000175400
- 본문언어 영어
- Published As http://dx.doi.org/10.3390/app10249010
초록/요약
Ensemble data assimilation systems generally suffer from underestimated background error covariance that leads to a filter divergence problem-the analysis diverges from the natural state by ignoring the observation influence due to the diminished estimation of model uncertainty. To alleviate this problem, we have developed and implemented the stochastically perturbed hybrid physical-dynamical tendencies to the local ensemble transform Kalman filter in a global numerical weather prediction model-the Korean Integrated Model (KIM). This approach accounts for the model errors associated with computational representations of underlying partial differential equations and the imperfect physical parameterizations. The new stochastic perturbation hybrid tendencies scheme generally improved the background error covariances in regions where the ensemble spread was not sufficiently expressed by the control experiment that used an additive inflation and the relaxation to prior spread method.
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