Further Improvements to the Statistical Hurricane Intensity Prediction Scheme Using Tropical Cyclone Rainfall and Structural Features

Abstract

AbstractThe Statistical Hurricane Intensity Prediction Scheme (SHIPS) is a multiple regression model for forecasting tropical cyclone (TC) intensity [both central pressure (Pmin) and maximum wind speed (Vmax)]. To further improve the accuracy of the Japan Meteorological Agency version of SHIPS, five new predictors associated with TC rainfall and structural features were incorporated into the scheme. Four of the five predictors were primarily derived from the hourly Global Satellite Mapping of Precipitation (GSMaP) reanalysis product, which is a microwave satellite-derived rainfall dataset. The predictors include the axisymmetry of rainfall distribution around a TC multiplied by ocean heat content (OHC), rainfall areal coverage, the radius of maximum azimuthal mean rainfall, and total volumetric rain multiplied by OHC. The fifth predictor is the Rossby number. Among these predictors, the axisymmetry multiplied by OHC had the greatest impact on intensity change, particularly, at forecast times up to 42 h. The forecast results up to 5 days showed that the mean absolute error (MAE) of the Pmin forecast in SHIPS with the new predictors was improved by over 6% in the first half of the forecast period. The MAE of the Vmax forecast was also improved by nearly 4%. Regarding the Pmin forecast, the improvement was greatest (up to 13%) for steady-state TCs, including those initialized as tropical depressions, with slight improvement (2%?5%) for intensifying TCs. Finally, a real-time forecast experiment utilizing the hourly near-real-time GSMaP product demonstrated the improvement of the SHIPS forecasts, confirming feasibility for operational use.