Advancing meteotsunami prediction: testing high-resolution meteotsunami models with radar-derived atmospheric forcing

Meteotsunamis, often overlooked in global disaster discussions, pose significant threats to coastal communities and infrastructure, particularly in shallow coastlines, narrow bays, and harbors. Unlike seismic tsunamis, where source parameters can typically be determined quickly following an earthquake, forecasting meteotsunamis remains challenging due to difficulties in obtaining real-time high-resolution atmospheric pressure data that contain meteotsunami source parameters. Intense short-period atmospheric pressure disturbances are typical triggers of meteotsunamis, but these small-scale pressure anomalies are often missed in observations and numerical weather forecasts. This study explores the feasibility of using weather radar reflectivity as a proxy for atmospheric pressure anomalies to enhance meteotsunami forecasting capabilities. The study employs the Method of Splitting Tsunamis (MOST) model, commonly used for seismic tsunami forecasting, across three very different regions: the East Coast of the United States, the southeastern Baltic Sea, and the Adriatic Sea (the Mediterranean). The results demonstrate that radar-based modeling successfully captures meteotsunami generation and propagation dynamics, particularly for summer events driven by mesoscale convective systems. The findings suggest that real-time meteotsunami forecasting is achievable using weather radar inputs, providing a promising approach for coastal hazard mitigation and early warning systems. However, winter meteotsunamis which are often related to extratropical cyclones and wind-driven forces, and which are superimposed on ongoing storm surges require additional modeling refinements.