Reconstruct the Mesoscale Information of Typhoon with BDA Method Combined with AMSU-A Data Assimilation MethodReport as inadecuate

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Advances in MeteorologyVolume 2010 2010, Article ID 346516, 11 pages

Research Article

Laboratory of Military Meteorology, Institute of Meteorology, PLA University of Science and Technology, Nanjing, 211101, China

LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

Received 28 December 2009; Revised 24 March 2010; Accepted 20 April 2010

Academic Editor: Zhaoxia Pu

Copyright © 2010 Yunfeng Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper conducts the assimilating experiments and simulating experiments on typhoon -Aere- No. 0418, by use of bogus data assimilation BDA method combined with advanced microwave sounding unit-A AMSU-A data assimilation method in the fifth-generation National Center for Atmospheric Research NCAR-Penn State Mesoscale Model Version-3 MM5V3, the Radiative Transfer for TIROS-N Operational Vertical Sounder Version-7 RTTOV model, and their adjoint models. The Bogus data constructed with BDA technique are mainly located at sea level, while the peak energy contribution levels of the sounder channels selected in AMSU-A data assimilation technique are mainly located at upper troposphere. The two types of data can reconstruct the meso-scale information and improve the typhoon initial fields under the model dynamic forcing effect, respectively from the low level and the upper level of atmosphere during the assimilating process. Numerical results show that with four-dimensional variational data assimilation 4DVAR technique the circulation of initial fields is improved, the -warm core- of typhoon is enhanced, the -cloud water- phenomenon that occurs in the optimal initial fields and the numerical model is changed into -warm start- from -cold start-.

Author: Yunfeng Wang, Haiyang Zhang, Bin Wang, Yueqi Han, and Xiaoping Cheng



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