A Simple Model for Predicting the Tropical Cyclone Minimum Central Pressure from Intensity and Size (Invited Presentation)

Minimum central pressure (Pmin) is an integrated measure of the tropical cyclone wind field that is an excellent indicator of its damage potential. A simple model that predicts Pmin from routinely-estimated quantities, including storm size, would be of great value. Here we present a simple linear empirical model for predicting Pmin from maximum wind speed, the radius of 34-knot winds (R34kt), and storm-center latitude, and the pressure of outermost closed isobar. Model predictors are combinations of these quantities that are derived directly from gradient wind balance applied to a simple modified-Rankine-type wind profile recently shown to reproduce well storm structure inside of R34kt. The model is fit to data from the southwestern North Atlantic and Eastern North Pacific 2004--2022 using aircraft-based estimates of the minimum pressure, Extended Best Track data, and estimates of environmental pressure from GFS analysis. The model has near-zero conditional bias and explains 97.1% of the variance, which is superior to a variety of other model formulations, including a standard wind-pressure model that does not account for storm size or latitude (91.0%). Model performance is strong for out-of-sample applications, including high-latitude storms and storms near coastlines. Finally, the model is shown to perform comparably well in an operations-like setting based solely on routinely-estimated variables from Extended Best Track data including the pressure of outermost closed isobar. Overall, the model offers a simple and fast prediction for Pmin that can be used operationally and in risk models.