Meteotsunami prediction in km-scale regional systems coupled at high frequency

Abstract. Meteorological tsunamis, or meteotsunamis, are anomalous waves triggered by atmospheric disturbances such as thunderstorms, gravity waves, squalls, or cyclones. While meteotsunamis have been studied extensively in regions like the Mediterranean and the United States, research in the Northwest European shelf remains limited, as meteotsunamis were considered rare and low-risk until recently. New evidence suggests they are often undetected due to insufficient tide gauge resolution. Reports indicate that meteotsunamis pose risks to infrastructure and have caused fatalities in the United Kingdom.

This study evaluates the capability of the Met Office's atmosphere-ocean-wave regional coupled model (UKC4) and Météo-France’s atmosphere-ocean regional coupled model (AROBASE) to capture and predict meteotsunamis. Configured at km-scale and with 10-minute coupling frequency, the models were tested on the strongest meteotsunami event (up to 1 m) recorded so far in Ireland, which occurred in June 2022. The whole event lasted for hours and significantly impacted Ireland, the UK and France. This case has been widely studied but the exact atmospheric drivers of such a widespread event remain unknown. The two models are able to represent the meteotsunami: the Met Office model is more successful in the Celtic Sea around the UK, Ireland and the English Channel and the Météo-France model captures a weak signal in the Bay of Biscay and English Channel. Analysis of the atmospheric situation suggests two slow-moving low-pressure systems, with colliding cold and dry Arctic air and extremely warm and dry continental air. This generates a shallow stable layer near the surface, which gets disrupted by convective downdrafts, generating gravity waves which propagate in the stable layer at the same speed as ocean disturbance, leading to Proudman resonance and to meteotsunamis in three different countries. Finally, for the first time for this region, we show that a km-scale regional coupled ensemble can successfully forecast this meteotsunami event.