Super-ensemble forecasts and resulting acoustic sensitivities in shallow waters

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, the presence of small-scales processes, the lack of real-time data, and the limited skill of operational models at the meso-scale have so far limited the application of SE methods for acoustic Rapid Environmental Assessment purposes. In the framework of the BP07 experiment conducted South East of Elba, sound speed prediction skills of various SE techniques combining operational model outputs and in-situ measurements are assessed. Results suggest that SE-based predictions provide more robust 24 h forecasts. A detailed acoustic propagation sensitivity study at different frequencies and ranges also reviews the potential of these predictions for acoustic inversion and tomography efforts.