Further Improvement in the SHIPS Using Rainfall and Structural Features

The Statistical Hurricane Intensity Prediction Scheme (SHIPS) is a multiple regression model for forecasting tropical cyclone (TC) intensity. The version used by the Japan Meteorological Agency (JMA) includes the prediction of central pressure P_min in addition to the maximum wind speed V_max. SHIPS mainly uses predictors associated with environmental conditions. Recent studies, however, have shown that inner-core structural conditions also govern subsequent intensity change. In this study the effect of rainfall and wind structure information on SHIPS forecasts was investigated. We incorporated five new predictors associated with TC rainfall and structural features into SHIPS for the western North Pacific basin. Four of the five predictors were derived from the hourly Global Satellite Mapping of Precipitation (GSMaP) reanalysis product, which is a microwave satellite-derived rainfall dataset. The predictors include the axisymmetricity of the rainfall distribution around a TC, rainfall areal coverage, the radius of maximum azimuthal mean rainfall, and total volumetric rain. In addition, the Rossby number, defined as V_max divided by the radius of 15 m s^–1 wind and the Coriolis parameter, was incorporated. Among these predictors, the axisymmetricity had the greatest impact on intensity change, in particular, at forecast times up to 60 h. Results showed that the mean absolute error (MAE) of the P_min forecast in SHIPS with the new predictors was improved by up to about 7% in the first half of the forecast period. The MAE of V_max forecast was also improved by up to about 4%. Regarding the P_min forecast, the improvement was greatest for steady-state TCs, whereas the improvement was much less for intensifying TCs. Finally, a real-time forecast experiment demonstrated that even the use of the hourly near-real time GSMaP product could improve the accuracy of SHIPS, confirming the feasibility for operational use.