Using the Ensemble Kalman Filter for Arctic sea ice forecasting: Towards a fully Lagrangian approach
The changing polar climate conditions have provided a new impetus for reliable predictions in these regions on timescales of days to decades. With increasing Arctic marine access, numerous stakeholders are in increasing need of coupled ice-ocean predictions to support for example, shipping operations, resource extraction and wildlife management concerns. Different stakeholder interests imply a need for forecasts on different temporal and spatial scales. For example, offshore operations require near-term (less than a week) and local predictions of ice and ocean conditions for operators working in the region but also require longer term (seasonal to decadal) information to inform future shipping routes and new port infrastructure needs. The presentation will review the status and perspectives of ocean and sea ice modeling and data assimilation for the Arctic and some reflection on whether data assimilation belongs to artificial intelligence or not.