Laurent Bertino

Laurent Bertino is an applied mathematician with 20 years of experience in data assimilation and ocean modelling and various other models. He obtained his PhD in geostatistics from the Ecole des Mines de Paris, France in 2001, and is now leading the Data Assimilation Group at the Nansen Center.

Bertino develops and improves ways to replicate and predict what happens in the ocean, with a special focus on the Arctic. His present interests lie in the interplay of data assimilation and machine learning as well as the monitoring and prediction of sea ice and icebergs. He uses his expertise in sequential data assimilation methods like the Ensemble Kalman Filter.

Numerical model simulations are hypothetical outcomes of the dynamics of a system, but do not usually match reality. Data assimilation techniques keep these simulations on track by including a regular flow of data from satellites and in-situ sensors. For example, data assimilation is able to correct the position of the ice edge and the location of ocean eddies. This allows to initialise skilful numerical predictions. One example of his work is the development and operation of the TOPAZ sea-ice and ocean forecasting system – including ocean primary production – from its first demonstration in January 2003 to its inclusion in the European services providing operational oceanography data: the Copernicus Marine Service.

Bertino has led several projects applying ensemble data assimilation methods in collaboration with other disciplines, for example to soil moisture, snow depletion and volcanic ash transport. He has also led two European projects dedicated to sea-ice forecasting and the interaction of waves and sea ice. He has also managed industry-driven modelling studies in the South China Sea, in the Gulf of Mexico, and in the Barents and Kara Seas. The purposes of these studies were for example to evaluate the consequences of hurricanes or to evaluate design criteria of offshore assets.