Tropical Cyclogenesis Prediction

Cloud Cluster
Development of tropical disturbances like this one is difficult to predict


The formation of a tropical cyclone is difficult to predict accurately because of several reasons: there is a small amount of observational data in areas where tropical cyclones form, the small-scale nature of the important processes is unable to be resolved in present day numerical models, and there is still a lack of adequate understanding of the physics of development. However, it has long been well known that there are several larger-scale factors that affect the probability of formation, such as sea surface temperature, vertical wind shear, and the humidity of the atmosphere (e.g. Gray 1968). It is thus not too surprising that statistical approaches to tropical cyclone formation ("tropical cyclogenesis") which approach the problem from the synoptic scale have shown more skill than dynamical models (Hennon and Hobgood 2003, Schumacher et al. 2009).

Our research group at UNC Asheville is continuing to improve upon earlier efforts at tropical cyclogenesis prediction. We approach the problem from a "cloud cluster centered" view by tracking potential tropical cyclones and calculating a series of predictors that have been shown to be correlated with development. We have used an automated, objective cloud cluster tracker, to compile thousands of cloud cluster case studies that can be used for cyclogenesis studies.

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  • Gray, W.M., 1968: Global view of the origin of tropical disturbances and storms. Monthly Weather Review,96,669-700.

  • Schumacher, A.B., M. DeMaria, and J.A. Knaff, 2009: Objective estimation of the 24-hour probability of tropical cyclone formation. Weather and Forecasting, 24, 456-471.

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