A revised predictor called the net energy gain rate (NGR) is suggested by considering wind‐dependent drag coefficient based on the existing maximum potential intensity theory. A series of wind speed‐dependent NGR, known as NGR‐w, is calculated based on pretropical cyclone (TC) averaged ocean temperatures from the surface down to 120 m (at 10‐m intervals) to include the TC‐induced vertical mixing for 13 years (2004–2016) in the western North Pacific. It turns out that NGR50‐w (NGR‐w based on temperature averaged over top 50 m) has the highest correlation with 24‐hr TC intensity change compared with the commonly used sea surface temperature‐based intensification potential (POT), depth‐averaged temperature‐based POT (POTDAT), and constant drag coefficient in the NGR. To demonstrate the effectiveness of NGR50‐w, we designed and conducted experiments for training (2004–2014) and testing (2015–2016). The model with NGR50‐w shows greater skill than does the model with POTDAT or POT by reducing prediction errors by about 16%.
This study introduces an unequally weighted technique for Multi-model Ensemble (MME) forecasting for western North Pacific Tropical Cyclone (TC) tracks. Weights are calculated by partial least square regression, and members are selected by paired t-test. The performances for shorter forecast time ranges, such as 24, 48 and 72 h, are examined in order to improve the MME model, in which the weights for members are equally assigned. For longer forecast time ranges, such as 96 and 120 h, weights for MME members are thought to be less reliable, since the modeling is more likely to be influenced by the climate variability in the data period. A combination of both techniques for the shorter and the longer forecast time ranges is suggested as an alternative MME forecast procedure in operational meteorological agencies.
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