Ali Aydogdu holds a PhD in physical oceanography from the Ca’ Foscari University of Venice and Euro-Mediterranean Centre on Climate Change (CMCC; Bologna) on data assimilation (DA) in regional and coastal scales. He studied variational and ensemble DA techniques as well as observation network design methodologies (OSE/OSSE). He had his post-doc at Nansen Environmental and Remote Sensing Center (NERSC; Bergen) on ensemble-based data assimilation techniques using adaptive moving mesh models with applications on Arctic sea-ice. He visited NCAR within the visitor programme of CISL before starting his current position as a research scientist at CMCC where he coordinates data assimilation activities in regional and coastal scales including Mediterannean and Black Sea MFSs involved in CMEMS MFCs. He has taken part in several European projects including SESAME, MyOcean and JERICO as well as DASIM and REDDA in collaboration with US. He is a member of the OceanPredict data assimilation task team (DA-TT). He teaches at the Università di Bologna in data assimilation.
His personal website is https://aydogduali.github.io
- Ensemble Kalman filter for nonconservative moving mesh solvers with a joint physics and mesh location update
- Probabilistic Forecasts of Sea Ice Trajectories in the Arctic: Impact of Uncertainties in Surface Wind and Ice Cohesion
- OSSE for a sustainable marine observing network in the Sea of Marmara
- Circulation of the Turkish Straits System under interannual atmospheric forcing