Assessing Meteo-HySEA Performance for Adriatic Meteotsunami Events

TL;DR

This study evaluates the GPU-accelerated Meteo-HySEA model for simulating meteotsunami events in the Adriatic Sea, comparing it with traditional CPU-based models, and highlights its potential for rapid, high-resolution early warning systems.

Contribution

It introduces and benchmarks a GPU-based meteotsunami simulation model, demonstrating significant computational efficiency gains and assessing its accuracy against existing models.

Findings

Meteo-HySEA reproduces timing and spatial variability of sea-level oscillations.

It often predicts larger amplitudes than ADCIRC.

GPU acceleration achieves order-of-magnitude speedups, enabling rapid simulations.

Abstract

Meteotsunamis are atmospherically driven sea-level oscillations that can trigger hazardous coastal flooding, particularly in resonant bays. This study assesses the GPU-based Meteo-HySEA model for meteotsunami simulation in the Adriatic Sea, benchmarking its performance against the CPU-based AdriSC-ADCIRC system. Three documented events (2014, 2017, 2020) were simulated using WRF downscaling of ERA reanalyses and validated with tide-gauge and microbarograph observations. Both models are limited by the underestimation of mesoscale pressure disturbances in the atmospheric forcing. Meteo-HySEA generally reproduces the timing and spatial variability of sea-level oscillations and often yields larger amplitudes than ADCIRC, but it tends to overestimate dominant wave periods, particularly in enclosed basins. Differences in oscillation persistence underscore the need for further validation against high-resolution tide-gauge data to assess whether Meteo-HySEA captures harbor seiches more realistically or ADCIRC better represents physical energy dissipation. Crucially, GPU acceleration provides order-of-magnitude gains in computational efficiency, enabling rapid high-resolution, multi-grid simulations including inundation, and thus offering strong potential for operational early warning.