The Arctic Ocean is of central importance for the global climate and ecosystem. It is a region undergoing rapid climate change, with a dramatic decrease in sea ice cover over recent decades. Surface advective pathways connect the transport of nutrients, freshwater, carbon and contaminants with their sources and sinks. Pathways of drifting material are deformed under velocity strain, due to atmosphere-ocean-ice coupling. Deformation is largest at fine space- and time-scales and is associated with a loss of potential predictability, analogous to weather often becoming unpredictable as synoptic-scale eddies interact and deform. However, neither satellite observations nor climate model projections resolve fine-scale ocean velocity structure. Here, we use a high-resolution ocean model hindcast and coarser satellite-derived ice velocities, to show: that ensemble-mean pathways within the Transpolar Drift during 2004–14 have large interannual variability and that both saddle-like flow structures and the presence of fine-scale velocity gradients are important for basin-wide connectivity and crossing time, pathway bifurcation, predictability and dispersion.

Abstract. Scientific evidence is critical to underpin the decisions associated with shoreline management, to build climate-resilient communities and infrastructure. We explore the role of waves, storm surges and sea level rise for the Caribbean region with a focus on coastal impacts in the eastern Caribbean islands. We simulate past extreme events and a worst-case scenario, modelling the storm surges and waves, suggesting a storm surge might reach 1.5 m, depending on the underwater topography. Coastal wave heights of up to 12 m offshore and up to 5 m near the coast of St Vincent are simulated with a regional wave model. We deliver probabilistic sea level projections for 2100, with a low-probability–high-impact estimate of possible sea level rise up to 2.2 m, exceeding the 1.8 m global estimate for the same scenario. We introduce a combined vulnerability index, which allows for a quantitative assessment of relative risk across the region, showing that sea level rise is the most important risk factor everywhere but wave impacts are important on windward coasts, increasing to the north, towards the main hurricane track. Our work provides quantitative evidence for policy-makers, scientists and local communities to actively prepare for and protect against climate change.

Abstract. Scientific evidence is critical to underpin the decisions associated with shoreline management, to build climate resilient communities and infrastructure. We explore the role of waves, storm surges and sea level rise for the Caribbean region with a focus on coastal impacts in the eastern Caribbean islands. We simulate past extreme events and a worst-case scenario, modelling the storm surges and waves, suggesting a storm surge might reach 1.5 m, depending on the underwater topography. Coastal wave heights up to 12 m offshore and up to 5 m near the coast of St Vincent are simulated with a regional wave model. We deliver probabilistic sea level projections for 2100, with a low probability/high impact estimate of possible sea level rise up to 2.2 m, exceeding the 1.8 m global estimate for the same scenario. We introduce a Combined Vulnerability Index, which allows a quantitative assessment of relative risk across the region, showing that sea level rise is the most important risk factor everywhere, but wave impacts are important on windward coasts, increasing to the north, towards the main hurricane track. Our work provides quantitative evidence for policy makers, scientists, and local communities to actively prepare for and protect against climate change.

A growing number of studies are concluding that the resilience of the Arctic sea ice cover in a warming climate is essentially controlled by its thickness. Satellite radar and laser altimeters have allowed us to routinely monitor sea ice thickness across most of the Arctic Ocean for several decades. However, a key uncertainty remaining in the sea ice thickness retrieval is the error on the sea surface height (SSH) which is conventionally interpolated at ice floes from a limited number of lead observations along the altimeter's orbital track. Here, we use an objective mapping approach to determine sea surface height from all proximal lead samples located on the orbital track and from adjacent tracks within a neighborhood of 30-220 (mean 105) km. The patterns of the SSH signal's zonal, meridional, and temporal decorrelation length scales are obtained by analyzing the covariance of historic CryoSat-2 Arctic lead observations, which match the scales obtained from an equivalent analysis of high-resolution sea ice-ocean model fields. We use these length scales to determine an optimal SSH and error estimate for each sea ice floe location. By exploiting leads from adjacent tracks, we can increase the sea ice radar freeboard precision estimated at orbital crossovers by up to 20%. In regions of high SSH uncertainty, biases in CryoSat-2 radar freeboard can be reduced by 25% with respect to coincident airborne validation data. The new method is not restricted to a particular sensor or mode, so it can be generalized to all present and historic polar altimetry missions.Plain Language Summary Arctic Ocean sea ice thickness has been estimated with satellite altimeters for several decades by stitching together observations of the sea level at open water leads or 'cracks' in the ice. The height difference between the sea ice surface and sea level, known as the freeboard, can then be converted to an estimate for the ice thickness. However, open water lead observations can be hundreds of kilometers apart along the satellite's orbit, so here we apply a method that also uses leads on nearby orbits to improve the sea level estimate at ice-covered locations. This requires us to understand how rapidly the Arctic sea level varies over space and time, which we do use ESA's CryoSat-2 satellite radar altimeter. With an optimal processing method that exploits 10-100s of times more observations than normal, we can improve the precision of the sea level estimated 'under' sea ice. Up to 25% improvement in sea ice freeboard indicates that the new method could upgrade current and historic altimetry-derived Arctic sea ice thickness records.

Sea ice retreat and opening of large, previously ice-covered areas of the Arctic Ocean to wind and ocean waves is leading to large changes in the sea ice state. The Arctic sea ice cover is becoming more fragmented and mobile, with large regions of ice cover projected to evolve into a marginal ice zone (MIZ). Fragmented sea ice has different dynamics, necessitating changes in sea ice model rheology. The objective of this study is to improve sea ice dynamics in models for forecasting and climate projections. We introduce granular behaviour in the ice dynamics and assess the impact on sea ice behaviour. For this purpose we have implemented a seamless rheology for MIZ and pack ice in an idealised sea ice and ocean model. The study compares the effect of the combined rheology with that of the standard elastic-viscous-plastic (EVP) rheology. The main effect of granular behaviour in ice rheology is on internal ice pressure. The jostling of the floes causes divergence of the sea ice cover. Sea ice viscosities are only weakly impacted. In idealised simulations the new sea ice rheology results in widening of the MIZ and a more diffuse ice edge in a stand-alone set-up. Oceanic feedbacks counteract and can undo this effect. The resolution of the simulation modifies the effect of the rheology: a rheology that accounts for granular effects offers better convergence of the solution than the