Machine Learning methods for the Atmosphere, the Ocean, and the Seabed

Understanding, observing, and forecasting the environment are all essential step to support a more sustainable interactions between human activities and the environment. Several areas of environmental modelling and classical analysis can be beneficial from the application of novel approach such as Machine Learning techniques. In particular, we are currently working on multiple areas for the development of machine learning techniques to be applied for (1) the modeling of the convection permitting dynamical model for precipitation forecasting, (2) data interpolation for ocean observing systems, in particular using data collected with ARGO floats, and (3) the automatic classification of seabeds for the assessment of geological hazards. Here we detail the current state of the projects in those area and directions for future research.