Verri Giorgia

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Verri Giorgia

Via Marco Biagi 5 – 73100 Lecce, Italy

(+39) 0832 1902411

[email protected]

Dr. Giorgia Verri is a Scientist working at CMCC Foundation since 2012. Since 2023 she has been leading the Coastal Earth System Modeling and Climate Research Unit at GOCO Division.

She holds a M.Sc. Degree in Physics at the University of Salento, obtained in 2009. She holds a II level Master in Energy Efficiency and Renewable Energies, obtained in 2011 at La Sapienza University in Rome and gained experince in the framework of meteorological modeling systems for wind energy forecasting of private companies.

In 2016 she got a Ph.D. in Environmental Science at the University of Bologna with a thesis titled “Predictability studies for Regions of freshwater influence”. She spent visiting periods at National Centre for Atmospheric Research working on modeling both inland and marine waters at mesoscales with a focus on their link in the estuarine areas. She developed a column-only Estuarine Box Model
(https://www.estuaryboxmodel.org), with both physics-based and ML-based approaches, to properly represent the net river release in terns of volume flux, temperature and salinity and to estimate the salt wedge intrusion length for multiple purposes. She is currently involved in exploiting the numerical and physical capabilities of a Galerkin finite-element model based on SHYFEM MPI code.

She is a lecturer of the PHD Program Future Earth at the University of Bologna where she held a Numerical Modeling Specialised Course on the Hydrosphere and the link between terrestrial and marine waters. She is ECOPs member of the United Nation Program CoastPredict.

Her research activities aim at investigating: (a) the link between inland and marine water working with both finite difference and finite elements models, (b) novel approaches for representing the estuarine water exchange and the dynamics of these transitional systems by merging physically-based and ML-based methods, (c) coupled/seamless modeling of the coastal water cycle to serve short-term prediction to climate projections with dynamical/statistical downsacling strategy

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