Improved Hurricane Track Forecasting from the Continuous Assimilation of High Quality Satellite Wind Data

Abstract Despite recent improvements in the accuracy of hurricane track forecasts, mean position errors still remain unacceptably large. For example, recurvature is captured poorly by forecast models and can produce excessively large position errors. This study addresses the problem of hurricane track forecasting in three ways. First, the initial conditions for the forecast model are augmented by a dense coverage of high spatial and temporal resolution satellite-derived wind vectors. Second, to gauge the extent to which this additional four-dimensional detail of the atmospheric structure can be exploited, three distinct types of data assimilation methods are examined. These are 1) conventional (intermittent, cycled) 6-h assimilation, 2) nudging over a 12- or 24-h period up to the initial time, and 3) recently developed barotropic and four-dimensional variational assimilation schemes, also over a 12- or 24-h period. The nudging and variational methods are continuous assimilation procedures and incorporate ...