Super-Ensemble Forecasts and Resulting Acoustic Sensitivities in Shallow Waters

摘要: Abstract Multi-model Super-Ensembles (SE) which optimally combine different models, have been shown to significantly improve atmospheric weather and climate predictions. In the highly dynamic coastal ocean, presence of small-scales processes, lack real-time data, limited skill operational models at meso-scale so far application SE methods for acoustic Rapid Environmental Assessment purposes. framework BP07 experiment conducted South East Elba, sound speed prediction skills various techniques combining model outputs in-situ measurements are assessed. Results suggest that SE-based predictions provide more robust 24 h forecasts. A detailed propagation sensitivity study frequencies ranges also reviews potential these inversion tomography efforts.