Authors: Heather Regan (LOPS, Ifremer, Brest, France), in collaboration with Camille Lique and Claude Talandier (LOPS), Thomas Armitage (JPL) and Gianluca Meneghello (MIT)

Ice shelves in West Antarctica are thinning at an increasing rate due to the inflow of relatively warm Circumpolar Deep Water into the ice shelf cavities. This warm water from off the continental shelf flows southward towards the ice shelves through submarine troughs incised into the continental shelf. Observations in front of Getz Ice Shelf suggest that 90% of the volume transport and 65% of the temperature transport is linked to the barotropic component of the southward current which follows f/H-contours.

Monitoring the Arctic Sea Surface Salinity (SSS) from space is crucial to understand the global water cycle and the ocean dynamics is limited due to nonhomogeneous and sparse in situ data. Two gridded satellite SSS products have been derived from European Space Agency’s Soil Moisture and Ocean Salinity mission (SMOS). The uncertainties of these two SSS products in the Arctic are quantified against other two SSS products in the Copernicus Marine Environment Monitoring Services and other in situ datasets.

In order to assure the security of navigation and offshore activities scientists have to predict with precision the type and the location of sea ices. Getting information about cold intensity and ocean-atmosphere dynamics of these polar regions are also motivations. The ways to describe sea ices are numerous but this article focuses only on type.

Over recent years, the vision of Open Science has emerged as a new paradigm of transparent, data-driven science capable of accelerating competitiveness and innovation. The embodiment of this vision in Europe is the European Open Science Cloud (EOSC), first proposed by the European Commission in April 2016 as part of the Communication on the ‘European Cloud Initiative’, one of the pillars of the Digital Single Market Strategy.

Numerical models solved on adaptive moving meshes have become increasingly prevalent in recent years. Motivating problems include the study of fluids in a Lagrangian frame and the presence of highly localized structures such as shock waves or interfaces. In the former case, Lagrangian solvers move the nodes of the mesh with the dynamical flow; in the latter, mesh resolution is increased in the proximity of the localized structure. Mesh adaptation can include remeshing, a procedure that adds or removes mesh nodes according to specific rules reflecting constraints in the numerical solver.

In the first part of this presentation I will give an overview over the high-resolution studies and capabilities, the Climate Prediction and Dynamics Group has been working with so far. This part will highlight results from projects during the last years. Among these are the successful studies for the Bergen harbour authority, the TRAKT-2018 project and the study on the mitigation of domestic-wood-heating related pollution.

Repeated climate stress events may cause fundamental shifts in species compositions or ecosystem functioning. However, few studies document such shifts. One reason for higher stability of ecosystems than previously expected may be ecological stress memory of vegetation. The study of memory effects of large-scale vegetation may therefore aid in predictions of future changes in biome distributions and resilience assessments on ecosystem or even species level. Such information is invaluable for management oriented decision support systems.