Numerical Weather Prediction (NWP) models and AI to predict extreme weather events
We use state-of-the-art NWP models in synergy with data-driven AI-based algorithms to obtain weather forecasts of extreme events with unprecedented accuracy
We use state-of-the-art NWP models in synergy with data-driven AI-based algorithms to obtain weather forecasts of extreme events with unprecedented accuracy
We use state-of-the-art NWP models to obtain HRES climate projections of atmospheric fields (e.g. precipitations and winds) by 2100
We use state-of-the-art NWPs in concert with data-driven AI-based algorithms to obtain accurate weather forecasts of green sources (wind, solar, waves)
We use state-of-the-art air-quality models in concert with data-driven AI-based algorithms to obtain calibrated prediction for pollutant concentrations
Understanding the Impact of a changing climate on coastal risks and vulnerability
Investigating the effects of mixing and dispersion processes in the ocean for environmental engineering challenges, from oil spills to microplastics
Investigating the Characteristics and Impacts of Extreme Wave Events, and Developing Strategies for the Design of Robust Coastal Structures
Coastal Morphodynamics and Evolution: Investigating the Dynamic
Interactions between the Ocean, Atmosphere, and Land in Coastal
Environments
Coastal environment monitoring, Citizen Science Project
| Title | Year | Author | Venue |
|---|---|---|---|
| Environmental Contour Assessment for Floating Offshore Wind Turbines Installation in the Mediterranean Sea | 2025 | Marchelli Elisa; De Leo Francesco; Besio Giovanni; Rizzo Cesare Mario | 21101368102 |
| THE LEARNED RANGE TEST METHOD FOR THE INVERSE INCLUSION PROBLEM* | 2025 | Sun S.; Alberti Giovanni | SIAM JOURNAL ON APPLIED MATHEMATICS |
| A novel AI-assisted forecasting strategy reveals the energy imbalance sign for the day-ahead electricity market | 2024 | Carnevale Daniele; Cavaiola Mattia; Mazzino Andrea | ENERGY REPORTS |
| AI-based solutions for autonomous underwater observing systems and science discovery | 2024 | Marini Simone; LAGOMARSINO ONETO Daniele; Cavaiola Mattia; Aguzzi Jacopo; D’Agostino Daniele | 10/04/2024 |
| Anomaly detection in feature space for detecting changes in phytoplankton populations | 2024 | Ciranni M.; Odone F.; Pastore V. P. | FRONTIERS IN MARINE SCIENCE |
This dataset provides bias-adjusted wave data for 15 buoy locations along the Italian coastline, together with bias-corrected historical and future wave projections. The dataset includes corrections applied to multiple reanalysis and model sources—ERA5, CMEMS, MeteOcean-UniGe 10 km regular grid, and MeteOcean-UniGe unstructured grid.
MeteOcean wave climate and extremes statistics in the Mediterranean Sea
MeteOcean 2D wave spectra statistics in the Mediterranean Sea
Wave System distribution in the Mediterranean Sea