Abstract
Integrated kinetic energy (IKE) is a useful quantity that measures the size and strength of a tropical cyclone wind field. As a result, it is inherently related to the destructive potential of these powerful storms. In most current operational settings, there are limited resources designed to assess the IKE of a tropical cyclone because storm track and maximum intensity are typically prioritized. Therefore, to complement existing forecasting tools, a statistical scheme is created to project fluctuations of IKE in North Atlantic tropical cyclones for several forecast intervals out to 72 h. The resulting scheme, named Statistical Prediction of Integrated Kinetic Energy (SPIKE), utilizes multivariate normal regression models trained on environmental and storm-related predictors from all North Atlantic tropical cyclones occurring from 1990 to 2011. During this training interval, SPIKE outperforms persistence and is capable of explaining more than 80% of observed variance in total IKE values at a forecast interval of 12 h, trailing down to just below 60% explained variance at an interval of 72 h. The skill of the SPIKE model is evaluated further using bootstrapping exercises in order to gauge the predictive abilities of the statistical scheme. In addition, the performance of the SPIKE model is also evaluated for the 2012 Atlantic hurricane season, which notably falls outside of the training interval. Ultimately, the validation exercises return shared variance scores similar to those found in the training exercises, serving as a proof of concept that the SPIKE model can be used to project IKE values when given accurate predictor data.
