Effects of 4-dimension variational data assimi-lation (4DVAR) with multifold observed data on the typhoontrack forecast are studied, by using the MM5V3 model, theRTTOVS-5 model and their adjoint models. The data usedf...Effects of 4-dimension variational data assimi-lation (4DVAR) with multifold observed data on the typhoontrack forecast are studied, by using the MM5V3 model, theRTTOVS-5 model and their adjoint models. The data usedfor assimilation include large-scale background fields data,bogus data, cloud-derived wind data, satellite inverse data,and high resolution infrared radiation sounder data (HIRS).There are 5 typhoon cases are used to perform the numericalexperiments and assimilation experiments. The numericalresults show that with 4DVAR the initial fields can be greatlyimproved and the initial typhoon structure can be clearlydescribed.展开更多
文摘Effects of 4-dimension variational data assimi-lation (4DVAR) with multifold observed data on the typhoontrack forecast are studied, by using the MM5V3 model, theRTTOVS-5 model and their adjoint models. The data usedfor assimilation include large-scale background fields data,bogus data, cloud-derived wind data, satellite inverse data,and high resolution infrared radiation sounder data (HIRS).There are 5 typhoon cases are used to perform the numericalexperiments and assimilation experiments. The numericalresults show that with 4DVAR the initial fields can be greatlyimproved and the initial typhoon structure can be clearlydescribed.
