Comparing Limited-Area 3DVAR and Hybrid Variational-Ensemble Data Assimilation Methods for Typhoon Track Forecasts: Sensitivity to Outer Loops and Vortex Relocation

The Weather Research and Forecasting Model (WRF) hybrid variational-ensemble data assimilation (DA) algorithm was used to initialize WRF model forecasts of three tropical cyclones (TCs). The hybrid-initialized forecasts were compared to forecasts initialized by WRF's three-dimensional variation...

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Bibliographic Details
Published in:Monthly weather review 2013-12, Vol.141 (12), p.4350-4372
Main Authors: SCHWARTZ, Craig S, ZHIQUAN LIU, HUANG, Xiang-Yu, KUO, Ying-Hwa, FONG, Chin-Tzu
Format: Article
Language:English
Subjects:
Algorithms
Climatology
Cyclones
Data assimilation
Data collection
Earth, ocean, space
Exact sciences and technology
Experiments
External geophysics
Hurricanes
Kalman filters
Localization
Mathematical models
Meteorology
Methods
Optimization
Relocation
Software
Studies
Three dimensional
Tropical cyclones
Typhoons
Variables
Weather
Weather forecasting
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Summary:The Weather Research and Forecasting Model (WRF) hybrid variational-ensemble data assimilation (DA) algorithm was used to initialize WRF model forecasts of three tropical cyclones (TCs). The hybrid-initialized forecasts were compared to forecasts initialized by WRF's three-dimensional variational (3DVAR) DA system. An ensemble adjustment Kalman filter (EAKF) updated a 32-member WRF-based ensemble system that provided flow-dependent background error covariances for the hybrid. The 3DVAR, hybrid, and EAKF configurations cycled continuously for 3.5 weeks and produced new analyses every 6 h that initialized 72-h WRF forecasts with 45-km horizontal grid spacing. Additionally, the impact of employing a TC relocation technique and using multiple outer loops (OLs) in the 3DVAR and hybrid minimizations were explored.
ISSN:0027-0644
1520-0493
DOI:10.1175/mwr-d-13-00028.1