Assessing Meteo-HySEA performance for Adriatic meteotsunami events

Abstract

Abstract Meteotsunamis are anomalous sea-level oscillations driven by atmospheric disturbances, which can lead to hazardous coastal flooding through resonance with local bathymetry and harbor geometries. Accurately reproducing both atmospheric forcing and harbor resonance is thus essential for realistic meteotsunami modeling. This study evaluates the performance of the newly developed Meteo-HySEA model against the state-of-the-art AdriSC-ADCIRC system for meteotsunami simulations in the Adriatic Sea. Three well-documented events (2014, 2017, 2020), mostly driven by pressure disturbances, are simulated with high-resolution atmosphere-ocean models and evaluated against available tide-gauge and microbarograph observations. For these events, to ensure a consistent and realistic evaluation of the model performance, no correction or tuning of the atmospheric forcing is applied. Consequently, both meteotsunami modeling systems are affected by limitations in reproducing the atmospheric forcing, particularly the underestimation of pressure disturbances. Overall, Meteo-HySEA successfully reproduces the timing and spatial variability of sea-level oscillations and generally yields higher amplitudes than AdriSC-ADCIRC. However, it tends to overestimate dominant wave periods, especially in semi-enclosed basins. Additionally, to further discuss the differences between the two meteotsunami models, synthetic pressure disturbances are used to reproduce the highest sea-level impacts in three harbors along the Croatian coast. This systematic and reproducible assessment of model response to well-characterized pressure disturbances further reveals differences in oscillation persistence between the two models and highlights uncertainties in the representation of resonance and energy dissipation processes. The present comparison demonstrates the capability of Meteo-HySEA to capture key features of meteotsunami dynamics with rapid high-resolution multi-grid simulations including coastal inundation. This makes Meteo-HySEA particularly well suited for operational forecasting and early warning applications.