The opponents were Dr. Iuliia Polkova (Universität Hamburg) and Dr. Jon Robson (University of Reading). The committee leader was Helge Drange (UiB) and the disputas leader was Elin Darelius (UiB). Her doctoral advisors were Helene R. Langehaug (NERSC), Marius Årthun (UiB), and Tor Eldvik (UiB).
Important Climate Predictions
In select regions across the globe, it is now possible to forecast climate changes up to a decade in advance. This remarkable advancement allows for the prediction of whether the upcoming years will be notably warm and rainfall-rich. This critical information regarding precipitation levels and temperature holds profound significance for a range of industries and decision-makers, including the fisheries, power companies, and agricultural sectors.
High Predictability in Subpolar North Atlantic
Subpolar areas in the North Atlantic emerge as regions characterized by exceptional predictability and significant influence on the climate in Western Europe.
Leilane Passos utilized the Norwegian climate prediction model and observational data to delve into three distinct aspects. These encompass the effects of various data assimilation methods (the incorporation of observations into a model) on prediction accuracy in the North Atlantic and Arctic regions, the interactions between diverse physical mechanisms that underlie long-term predictability (spanning decades), and how data assimilation in the ocean enhances climate forecasting for Europe.
The findings within her doctoral dissertation contribute significantly to the development of dynamic forecasting systems, paving the way for their operational implementation in the near future.
Personal profile:
Born and raised in Vitória, Brazil, Leilane holds a master's degree in Physical Oceanography from the University of São Paulo. In 2019, she commenced her doctoral journey in climate dynamics at the Geophysical Institute, University of Bergen. During this period, she was also associated with the Bjerknes Center for Climate Research.