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Numerical Experiments for Typhoon Dan Incorporating AMSU-A Retrieved Data with 3DVM


doi: 10.1007/s00376-008-0692-2

  • Two sets of assimilation experiments on a landfalling typhoon---Typhoon Dan (1999) over the western North Pacific were designed to compare the performances of two kinds of variational data assimilation schemes that are the 3-Dimensional Variational data assimilation of Mapped observation (3DVM) and the 4-dimensional variational data assimilation (4DVar). Results show that: (1) both the 3DVM and 4DVar successfully improved the simulations of typhoon intensity and track incorporating the satellite AMSU-A retrieved temperature and wind data into the initial conditions, and the 3DVM more significantly due to the flow-dependent of background error covariance matrix and observation error covariance matrix like 3-dimensional variational data assimilation (3DVar) circle; (2) inclusions of extra model integration iterations at each observation time in the 3DVM make it more consistent with prediction model; (3) the 3DVM is much more time-saving due to the exclusion of the adjoint technique in it.
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Manuscript History

Manuscript received: 10 July 2008
Manuscript revised: 10 July 2008
通讯作者: 陈斌, bchen63@163.com
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Numerical Experiments for Typhoon Dan Incorporating AMSU-A Retrieved Data with 3DVM

  • 1. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029; Institute of Sciences, PLA University of Science and Technology, Nanjing 2;State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029

Abstract: Two sets of assimilation experiments on a landfalling typhoon---Typhoon Dan (1999) over the western North Pacific were designed to compare the performances of two kinds of variational data assimilation schemes that are the 3-Dimensional Variational data assimilation of Mapped observation (3DVM) and the 4-dimensional variational data assimilation (4DVar). Results show that: (1) both the 3DVM and 4DVar successfully improved the simulations of typhoon intensity and track incorporating the satellite AMSU-A retrieved temperature and wind data into the initial conditions, and the 3DVM more significantly due to the flow-dependent of background error covariance matrix and observation error covariance matrix like 3-dimensional variational data assimilation (3DVar) circle; (2) inclusions of extra model integration iterations at each observation time in the 3DVM make it more consistent with prediction model; (3) the 3DVM is much more time-saving due to the exclusion of the adjoint technique in it.

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