Cloud and water vapour motion vectors in tropical cyclone track forecasting — A review

Abstract

Tropical cyclone track prediction remains a vexing problem in meteorology, particularly for numerical weather prediction. While there has been significant improvement in forecast skill in recent years, errors in prognosis, particularly for recurving cyclones still remain unacceptably high. Consistent with track prediction being to a significant extent an initial value problem, there has been, in recent years, cogent evidence that, a combination of high resolution numerical modelling, the use of appropriate assimilation techniques and the exploitation of high spatial and temporal resolution observations can improve the accuracy of tropical cyclone forecasts. Before landfall, tropical cyclones have their genesis and move over the data-sparse tropical oceans. Here the prediction of their movement is an application for which remotely sensed data are quintessential. In this context, this paper examines the increasingly important contribution of cloud and water vapour motion vectors to tropical cyclone prediction and evaluates their import to accurate prediction in terms of both the numerical modelling characteristics and the data assimilation techniques employed. Overall, it is shown that cloud and water vapour drift winds have made a significant contribution to the tropical cyclone track forecasting problem when used with conventional intermittent assimilation techniques, such as 6-hourly cycling, and, more recently, with continuous assimilation techniques such as 3- and 4-dimensional variational assimilation. These continuous assimilation schemes appear to have the potential to use near continuous asynoptic wind data in the most effective way.