Application of scale-selective data assimilation to seasonal simulation of tropical cyclones

To improve the seasonal simulation of tropical cyclones, large-scale wind components from global analysis or forecasting are ingested into a regional forecasting model using a scale-selective data assimilation scheme. This scale-selective data assimilation scheme involves a low-passed filter and a 3-dimensional variational data assimilation approach. The low-passed filter is used to perform the scale separation of the wind components from the global analysis/forecasting as well as the regional model forecast. Then the large-scale wind components from the global analysis/forecasting are assimilated into the regional forecast model using 3-dimensional variational data assimilation method. This scheme is applied to a case study of summer 2005 over the regions of the Atlantic and the eastern US. The results show that the assimilation of large-scale wind components from the global GFS reanalysis improves the large-scale environmental circulation and leads to a more accurate seasonal simulation of tropical cyclones.

Keywords: Scale-selective Data Assimilation, Tropical Cyclones, Global Model, Regional Climate Model, Seasonal Simulation