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공공누리This item is licensed Korea Open Government License

Title
Real Data Assimilation Using the Local Ensemble Transform Kalman Filter (LETKF) System for a Global Non-hydrostatic NWP model on the Cubed-sphere
Author(s)
신설은강지순
Publication Year
2018-06-01
Abstract
An ensemble data assimilation system using the 4-dimensional Local Ensemble Transform Kalman Filter is implemented to a global non-hydrostatic Numerical Weather Prediction model on the cubed-sphere. The ensemble data assimilation system is coupled to the Korea Institute of Atmospheric Prediction Systems Package for Observation Processing, for real observation data from diverse resources, including satellites. For computational efficiency in a parallel computing environment, we employ some advanced software engineering techniques in the handling of a large number of files. The ensemble data assimilation system is tested in a semi-operational mode, and its performance is verified using the Integrated Forecast System analysis from the European Centre for Medium-Range Weather Forecasts. It is found that the system can be stabilized effectively by additive inflation to account for sampling errors, especially when radiance satellite data are additionally used.
Keyword
Ensemble data assimilation; local ensemble transform Kalman filter (LETKF); numerical weather prediction (NWP); atmospheric global model (AGM)
Journal Title
Asia-Pacific Journal of Atmospheric Sciences
Citation Volume
54
ISSN
1976-7633
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Appears in Collections:
7. KISTI 연구성과 > 학술지 발표논문
URI
https://repository.kisti.re.kr/handle/10580/14731
http://www.ndsl.kr/ndsl/search/detail/article/articleSearchResultDetail.do?cn=NART90661782
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