Development of an Operational Hybrid Data Assimilation System at KIAPS

• Published in: Asia-Pacific journal of atmospheric sciences Vol. 54; no. Suppl 1; pp. 319 - 335
• Main Authors: Kwon, In-Hyuk, Song, Hyo-Jong, Ha, Ji-Hyun, Chun, Hyoung-Wook, Kang, Jeon-Ho, Lee, Sihye, Lim, Sujeong, Jo, Youngsoon, Han, Hyun-Jun, Jeong, Hanbyeol, Kwon, Hui-Nae, Shin, Seoleun, Kim, Tae-Hun
• Format: Journal Article
• Language: English
• Published: Seoul Korean Meteorological Society 01.06.2018; Springer Nature B.V; 한국기상학회
• Subjects: Atmospheric Sciences; Climatology; Data; Data assimilation; Data collection; Earth and Environmental Science; Earth Sciences; Ensemble forecasting; Geophysics/Geodesy; Humidity; Illustrations; Ingestion; Kalman filters; Moisture; Radiance; Satellite observation; Satellites; Stratosphere; Weather forecasting; 대기과학; ensemble-variational hybridization; operational data assimilation; coupling strategy for hybrid systems; Numerical weather prediction; satellite observation assimilation
• ISSN: 1976-7633; 1976-7951
• DOI: 10.1007/s13143-018-0029-8

This study introduces the operational data assimilation (DA) system at the Korea Institute of Atmospheric Prediction Systems (KIAPS) to the numerical weather prediction community. Its development history and performance are addressed with experimental illustrations and the authors’ previously published studies. Milestones in skill improvements include the initial operational implementation of three-dimensional variational data assimilation (3DVar), the ingestion of additional satellite observations, and changing the DA scheme to a hybrid four-dimensional ensemble-variational DA using forecasts from an ensemble based on the local ensemble transform Kalman filter (LETKF). In the hybrid system, determining the relative contribution of the ensemble-based covariance to the resultant analysis is crucial, particularly for moisture variables including a variety of horizontal scale spectra. Modifications to the humidity control variable, partial rather than full recentering of the ensemble for humidity further improves moisture analysis, and the inclusion of more radiance observations with higher-level peaking channels have significant impacts on stratosphere temperature and wind performance. Recent update of the operational hybrid DA system relative to the previous 3DVar system is described for detailed improvements with interpretation.