Initialization and simulation of a landfalling typhoon using a variational bogus mapped data assimilation (BMDA)
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Recently, a new data assimilation method called “3dimensional variational data assimilation of mapped observation (3DVM)” has been developed by the authors. We have shown that the new method is very efficient and inexpensive compared with its counterpart 4dimensional variational data assimilation (4DVar). The new method has been implemented into the Penn State/NCAR mesoscale model MM5V1 (MM5_3DVM). In this study, we apply the new method to the bogus data assimilation (BDA) available in the original MM5 with the 4DVar. By the new approach, a specified sealevel pressure (SLP) field (bogus data) is incorporated into MM5 through the 3DVM (for convenient, we call it variational bogus mapped data assimilation – BMDA) instead of the original 4DVar data assimilation. To demonstrate the effectiveness of the new 3DVM method, initialization and simulation of a landfalling typhoon – typhoon Dan (1999) over the western North Pacific with the new method are compared with that with its counterpart 4DVar in MM5. Results show that the initial structure and the simulated intensity and track are improved more significantly using 3DVM than 4DVar. Sensitivity experiments also show that the simulated typhoon track and intensity are more sensitive to the size of the assimilation window in the 4DVar than that in the 3DVM. Meanwhile, 3DVM takes much less computing cost than its counterpart 4DVar for a given time window.
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 Title
 Initialization and simulation of a landfalling typhoon using a variational bogus mapped data assimilation (BMDA)
 Journal

Meteorology and Atmospheric Physics
Volume 98, Issue 34 , pp 269282
 Cover Date
 20071201
 DOI
 10.1007/s0070300702654
 Print ISSN
 01777971
 Online ISSN
 14365065
 Publisher
 SpringerVerlag
 Additional Links
 Topics
 Authors
 Author Affiliations

 A1. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
 A2. Institute of Sciences, University of Science and Technology of the Chinese People’s Liberation Army, Nanjing, China
 A3. International Pacific Research Center and Department of Meteorology, University of Hawaii at Manoa, Honolulu, HI, USA