The findings of their research was recently published in the journal "Frontiers in Marine Science" under the headline "Conceptual Design of Extreme Sea-Level Early Warning Systems Based on Uncertainty Quantification and Engineering Optimization Methods".
The authors analyse possible applications of this concept on other coastal hazards that can cause losses of human lives and damage up to several billion euros.
"Coastal hazards linked to extreme sea-level events are projected to have a direct impact (by flooding) on 630 million of people by year 2100. Numerous operational forecasts already provide coastal hazard assessments around the world. However, they are largely based on either deterministic tools (e.g., numerical ocean and atmospheric models) or ensemble approaches which are both highly demanding in terms of high-performance computing (HPC) resources," reads the article.
"Through a robust learning process, we propose conceptual design of an innovative architecture for extreme sea-level early warning systems based on uncertainty quantification/reduction and optimization methods. This approach might be cost-effective in terms of real-time computational needs while maintaining reliability and trustworthiness of the hazard assessments," say the authors.
The presented research was funded through Croatian Science Foundation (project ADIOS, Grant IP-2016-06-1955) and European Centre for Middle-range Weather Forecast (ECMWF) special project "Using stochastic surrogate methods for advancing toward reliable meteotsunami early warning systems," the journal notes.
The authors of the article are Cléa Denamiel, Xun Huan and Iivica Vilibić.