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 a...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.展开更多
文摘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.
