Catherine O'Beirne: Applications of Decadal Predictions

Fishery sector is of vast importance to the Irish economy. In 2019 it has generated €577 million and employed 16 thousand. The ability to predict changes in the future stock will support adaptation and fish stock management. In decadal climate prediction, initialized predictions have demonstrated improved prediction skill for the North Atlantic. The different stages of fish development are dependent on oceanic variables like temperature and variability and investigating decadal prediction skill for those variables will allow me to make statements on potential changes in fish stock.

After completing a B.A. in Environmental Science at Trinity College Dublin in 2016 and an M.Sc. in Climate Change at Maynooth University in 2018. I am currently a 3rd year PhD candidate at Maynooth University. The area of focus is on understanding Atlantic variability and its connection to the Irish shelf advancing knowledge of Irish sea-level change in an Atlantic context; development of predictive capacity on decadal timescales for the North Atlantic; and how these predictions be applied for stakeholder needs.

With the aim being to improve decadal prediction skill in the Northeast Atlantic. For this we apply ensemble subsampling, a process that selects those ensemble members for creating a subsampled ensemble mean, which perform best under evaluation by physically based statistical predictors. Climate modes, like Subpolar Gyre (SPG) and the Atlantic Multidecadal Variability (AMV), interact with our region of interest and therefore we will use those to inform us about our subsampling decisions. Applying this methodology on seasonal scales has demonstrated improved prediction skill for other climate modes.