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http://dx.doi.org/10.9766/KIMST.2018.21.3.403

Development of the Three-Dimensional Variational Data Assimilation System for the Republic of Korea Air Force Operational Numerical Weather Prediction System  

Noh, Kyoungjo (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University)
Kim, Hyun Mee (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University)
Kim, Dae-Hui (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University)
Publication Information
Journal of the Korea Institute of Military Science and Technology / v.21, no.3, 2018 , pp. 403-412 More about this Journal
Abstract
In this study, a three-dimensional variational(3DVAR) data assimilation system was developed for the operational numerical weather prediction(NWP) system at the Republic of Korea Air Force Weather Group. The Air Force NWP system utilizes the Weather Research and Forecasting(WRF) meso-scale regional model to provide weather information for the military service. Thus, the data assimilation system was developed based on the WRF model. Experiments were conducted to identify the nested model domain to assimilate observations and the period appropriate in estimating the background error covariance(BEC) in 3DVAR. The assimilation of observations in domain 2 is beneficial to improve 24-h forecasts in domain 3. The 24-h forecast performance does not change much depending on the estimation period of the BEC in 3DVAR. The results of this study provide a basis to establish the operational data assimilation system for the Republic of Korea Air Force Weather Group.
Keywords
Air Force Operational Numerical Weather Prediction System; WRF 3DVAR; Background Error Covariance;
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Times Cited By KSCI : 3  (Citation Analysis)
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