Stochastic Surrogate Model for Meteotsunami Early Warning System in the Eastern Adriatic Sea. Issue 11 (30th November 2019) - Denamiel, Cléa; Šepić, Jadranka; Huan, Xun; Bolzer, Célia; Vilibić, Ivica
Abstract: The meteotsunami early warning system prototype using stochastic surrogate approach and running operationally in the eastern Adriatic Sea is presented. First, the atmospheric internal gravity waves (IGWs) driving the meteotsunamis are either forecasted with state‐of‐the‐art deterministic models at least a day in advance or detected through measurements at least 2 hr before the meteotsunami reaches sensitive locations. The extreme sea‐level hazard forecast at endangered locations is then derived with an innovative stochastic surrogate model—implemented with generalized polynomial chaos expansion (gPCE) method and synthetic IGWs forcing a barotropic ocean model—used with the input parameters extracted from deterministic model results and/or measurements. The evaluation of the system, both against five historical events and for all the detected potential meteotsunamis since late 2018 when the early warning system prototype became operational, reveals that the meteotsunami hazard is conservatively assessed but often overestimated at some locations. Despite some needed improvements and developments, this study demonstrates that gPCE‐based methods can be used for atmospherically driven extreme sea‐level hazard assessment and in geosciences in wide. Plain Language Summary: Atmospherically driven extreme sea‐level events are one of the major threats to people and assets in the coastal regions. Assessing the hazard associated with such events together with uncertainty quantification in a precise and timely manner is thus of primary importance in modern societies. In this study, an early warning system for the eastern Adriatic meteotsunamis, destructive long waves with periods from few minutes up to an hour generated by traveling atmospheric disturbances, is presented and evaluated. The system is based on state‐of‐the‐art deterministic atmospheric and ocean models as well as an innovative statistical model developed to forecast the meteotsunami hazard. The evaluation reveals that the meteotsunami hazard is conservatively assessed but often overestimated. This study demonstrates that the presented methodology can be used for extreme sea‐level hazard assessment and in general for hazard studies in geosciences. Key Points: Design and evaluation of an innovative meteotsunami early warning system prototype using stochastic surrogate approach Forecast of the atmospheric internal gravity waves driving meteotsunami events with deterministic state‐of‐the‐art models Stochastic surrogate model based on generalized polynomial chaos expansion methods and running at nearly no computational cost