Associate Visiting Professor

Luglio 2013

During the stay in Columbia University it has been carried out an investigation on the future patterns of daily temperature, precipitation and sea level in different coastal regions , under global warming scenario simulated by CGMs, in order to provide the input data for performing hydrodynamics/morphodynamics analysis of surface and groundwater flows in such regions. The research is address to the development and application of statistical downscaling approaches, as Hidden Markov Model and Non-homogeneous Hidden Markov model, Artificial Neural Network and combined approaches; these approaches are applied to a number of regions as South Florida, Tanzania and Piana Pontina. Further it has been developped a statistical forecast model for Tropical Cyclone Rainfall and flood events for the Hudson River, New York City area. Specifically the aim is the construction of a system of statistical models able to translates the attributes of a tropical cyclone to rainfall intensity at selected stations within the watershed of Hudson River and to transforms, , the rainfall intensities, calculated for the ensemble of the stations, to the streamflows at specific points of the tributaries of the Hudson River, to use as inputs in a hydrodynamic model that includes storm surge dynamics for the simulation of coastal flooding along the Hudson River.