Objective identification of annular hurricanes using GOES and reanalysis data

An objective technique using GOES infrared imagery and environmental reanalysis data is developed for identifying annular hurricanes. Annular hurricanes are a category of tropical cyclone characterized in infrared imagery by a large circular eye feature surrounded by a nearly uniform ring of deep convection and a distinct lack of deep convection features outside this ring (Knaff et al. 2004). They have also been shown to exist in only specific environmental conditions favorable for the development and maintenance of robust, axisymmetric hurricanes. If the environmental conditions are maintained, the annular phase can persist for days, which thus potentially leads to large intensity forecast errors. The ability to objectively identify annular hurricanes, therefore, will reduce these forecast errors.

The proposed technique applies discriminant analysis to determine which environmental variables and IR characteristics are the best predictors of identifying annular hurricanes. The environmental parameters are those used to develop the SHIPS model determined from reanalysis fields for the period 1982-2004 and the IR characteristics are from GOES imagery for the period 1995-2004.