Since historical wind radii are generally of poor quality and temporally and spatially inhomogeneous, this study uses a satellite-based tropical cyclone size estimates that are both temporally and spatially homogeneous as a basis for prediction. The satellite-based TC sizes that are scaled by climatology as a function of intensity (FR5) are used as the independent variable (predicant) in the statistical-dynamical scheme and predictors are derived from the Statistical Hurricane Intensity Prediction Scheme (SHIPS) large-scale environmental diagnostics. Using the predicted FR5 and the predicted intensity (e.g., from SHIPS), forecast of TC size estimates is obtained. Azimuthally averaged wind radii can then be estimated from statistical relationships between TC size and azimuthally averaged Atlantic and East Pacific best tracked wind radii. Asymmetries are applied using relationships from the wind radii Climatology and Persistence (CLIPER) statistical model, which are a function of storm motion and latitude, to provide wind radii in all quadrants. Finally, given storm motion, intensity, and wind radii, estimates of MSLP are then also estimated using the Knaff/Zehr/Courtney methodology.
Specifics about the data sets, the statistical model formulation, the statistical TC size and wind radii relationships, as well as vortex model development and assumptions will be presented in this talk. In addition, details of the environmental and climatological factors important for TC size and thus for wind radii variations will also be discussed, highlighting differences between the global tropical cyclone basins. Finally, some verification statistics will be presented for the North Atlantic and East Pacific basins, where best tracked wind radii are available.
Disclaimer: The views, opinions, and findings contained in this report are those of the authors and should not be construed as an official National Oceanic and Atmospheric Administration or U.S. Government position, policy, or decision. This research was sponsored by the GOES-R project office and the Joint Hurricane Testbed.