Weather and Climate Superensemble Forecasts from Multimodels

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The principal investigator will further explore the ensemble/superensemble approach for numerical weather prediction using forecast experiments from a range of different models. A superensemble approach performs an ensemble average after the bias of the individual member models is removed, thereby increasing the skill of the prediction above that of individual model forecasts. The PI will extend this approach by using a suite of proxy models, which is called the synthetic superensemble component, to address the issue of seasonal climate anomalies. Variants of the synthetic superensemble will be explored with regard to hurricane landfall, track and intensity, as well as heavy rain forecasts and numerical weather prediction. Graduate students will participate in this research.