Seasonal forecasting of tropical storm frequency using a multi‐model ensemble

Abstract

SUMMARYThe skill of seven coupled ocean-atmosphere models to predict the frequency of tropical storms from 1987 to 2001 has been assessed using a procedure for tracking model tropical storms. The tropical storm tracker takes account of the difference of atmospheric horizontal resolution between the different models. Results indicate that the models display some skill in predicting the interannual variability of tropical storms over the Atlantic, the eastern North Pacific, the western North Pacific, the Australian basin and the South Pacific. A simple multimodel forecast has been built by adding all the seven ensemble forecasts together after calibration. The skill of the simple multi-model system is overall better than the skill of any individual model. Over a specific basin, combining several models leads to better forecasts than the best individual model. This indicates that the multimodel approach could benefit the dynamical seasonal forecast of tropical storms.This conclusion is also valid for a longer time period . However, the individual models and the simple multi-model display less skill in predicting the interannual variability of tropical storms in the earlier decades.

Hurricanes in an aquaplanet world: Implications of the impacts of external forcing and model horizontal resolution

“…The criteria in the code were originally designed for the very high resolutions of 1/6 ($18 km). Therefore for the multiscale simulations in this study, we adopt the thresholds of the tracking criteria used for simulations at 1 -1.5 (approximately T85) resolution from the studies of Vitart and Stockdale [2001], Vitart et al [2003], and Vitart [2006]. These studies serve as the basis for GFDL's storm-tracking algorithm.…”

Risk and uncertainty in hydrometeorological hazards

“…The mean of an MME is often found to outperform the individual members (e.g. Hagedorn et al, 2005;Vitart, 2006), increasingly so with ensemble size (e.g. Ferro et al, 2008), though it does not outperform the best member.…”

Seasonal climate forecasting

“…In the case of hurricanes this implies that instead of providing the track and intensity of an individual track, seasonal forecasts may provide the level of hurricane activity in relation to past distribution (e.g. Vitart, 2006). In summary, in order to be able to extract potentially useful information, the longer the lead time the larger the averaging time and the larger the spatial area needs to be.…”