A Simple Model for Predicting Tropical Cyclone Minimum Central Pressure from Intensity and Size Weather and Forecasting

Minimum central pressure (Pmin) is an integrated measure of the tropical cyclone wind field and is known to be a useful indicator of storm 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, a radius of 34-kt (1 kt ≈ 0.51 m s−1) winds (R34kt), storm center latitude, and the environmental pressure. An empirical model for the pressure deficit is first developed that takes as predictors specific combinations of these quantities that are derived directly from theory based on gradient wind balance and a modified Rankine-type wind profile known to capture storm structure inside of R34kt. Model coefficients are estimated using data from the southwestern North Atlantic and eastern North Pacific from 2004 to 2022 using aircraft-based estimates of Pmin, extended best track data, and estimates of environmental pressure from Global Forecast System (GFS) analyses. The model has a near-zero conditional bias even for low Pmin, explaining 94.2% of the variance. Performance is superior to a variety of other model formulations, including a standard wind–pressure model that does not account for storm size or latitude (89.2% variance explained). Model performance is also strong when applied to high-latitude data and data near coastlines. Finally, the model is shown to perform comparably well in an operation-like setting based solely on routinely estimated variables, including the pressure of the outermost closed isobar. Case study applications to five impactful historical storms are discussed. Overall, the model offers a simple, fast, physically based prediction for Pmin for practical use in operations and research.