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Arguably, the most conspicuous evidence for anthropogenic climate change lies in the Arctic Ocean. For example, the summer-time Arctic sea ice extent has declined over the last 40 years and the Arctic Ocean freshwater storage has increased over the last 30 years. Coupled climate models project that this extra freshwater will pass Greenland to enter the sub-polar North Atlantic Ocean (SPNA) in the coming decades. Coupled climate models also project that the Atlantic Meridional Overturning Circulation (AMOC) will weaken in the twenty-first century, associated with SPNA buoyancy increases. Yet, it remains unclear when the Arctic anthropogenic freshening signal will be detected in the SPNA, or what form the signal will take. Therefore, this article reviews and synthesizes the state of knowledge on Arctic Ocean and SPNA salinity variations and their causes. This article focuses on the export processes in data-constrained ocean circulation model hindcasts. One challenge is to quantify and understand the relative importance of different competing processes. This article also discusses the prospects to detect the emergence of Arctic anthropogenic freshening and the likely impacts on the AMOC. For this issue, the challenge is to distinguish anthropogenic signals from natural variability.

This article is part of a discussion meeting issue ‘Atlantic overturning: new observations and challenges’.

 

Southern Ocean surface cooling and Antarctic sea ice expansion from 1979 through 2015 have been linked both to changing atmospheric circulation and melting of Antarctica's grounded ice and ice shelves. However, climate models have largely been unable to reproduce this behavior. Here we examine the contribution of observed wind variability and Antarctic meltwater to Southern Ocean sea surface temperature (SST) and Antarctic sea ice. The free‐running, CMIP6‐class GISS‐E2.1‐G climate model can simulate regional cooling and neutral sea ice trends due to internal variability, but they are unlikely. Constraining the model to observed winds and meltwater fluxes from 1990 through 2021 gives SST variability and trends consistent with observations. Meltwater and winds contribute a similar amount to the SST trend, and winds contribute more to the sea ice trend than meltwater. However, while the constrained model captures much of the observed sea ice variability, it only partially captures the post‐2015 sea ice reduction.

 

Arctic Ocean gateway fluxes play a crucial role in linking the Arctic with the global ocean and affecting climate and marine ecosystems. We reviewed past studies on Arctic–Subarctic ocean linkages and examined their changes and driving mechanisms. Our review highlights that radical changes occurred in the inflows and outflows of the Arctic Ocean during the 2010s. Specifically, the Pacific inflow temperature in the Bering Strait and Atlantic inflow temperature in the Fram Strait hit record highs, while the Pacific inflow salinity in the Bering Strait and Arctic outflow salinity in the Davis and Fram straits hit record lows. Both the ocean heat convergence from lower latitudes to the Arctic and the hydrological cycle connecting the Arctic with Subarctic seas were stronger in 2000–2020 than in 1980–2000. CMIP6 models project a continuing increase in poleward ocean heat convergence in the 21st century, mainly due to warming of inflow waters. They also predict an increase in freshwater input to the Arctic Ocean, with the largest increase in freshwater export expected to occur in the Fram Strait due to both increased ocean volume export and decreased salinity. Fram Strait sea ice volume export hit a record low in the 2010s and is projected to continue to decrease along with Arctic sea ice decline. We quantitatively attribute the variability of the volume, heat, and freshwater transports in the Arctic gateways to forcing within and outside the Arctic based on dedicated numerical simulations and emphasize the importance of both origins in driving the variability. 

We identified the nature and driving mechanisms of subinertial variability (variability at a time scale of several days) in four fjords in Southeast Greenland, in three high‐resolution numerical simulations. We find two dominant frequency ranges in along‐fjord velocity, volume transport of Atlantic Water, and along‐fjord heat transport: one around 2–4 days and one around 10 days. The higher frequency is most prominent in the two smaller fjords (Sermilik Fjord and Kangerdlugssuaq Fjord), while the lower frequency peak dominates in the larger fjords (Scoresby Sund and King Oscar Fjord). The cross‐fjord structure of variability patterns is determined by the fjord's dynamic width, while the vertical structure is determined by the stratification in the fjord. The dominant frequency range is a function of stratification and fjord length, through the travel time of resonant internal Kelvin waves. We find that the subinertial variability is the imprint of Coastal Trapped Waves, which manifest as Rossby‐type waves on the continental shelf and as internal Kelvin‐type waves inside the fjords. Between 50% and 80% of the variability in the fjord is directly forced by Coastal Trapped Waves propagating in from the shelf, with an additional role played by alongshore wind forcing on the shelf.

 

Abstract. Use of an ocean parameter and state estimation framework – such as the Estimating the Circulation and Climate of the Ocean (ECCO) framework – could provide an opportunity to learn about the spatial distribution of the diapycnal diffusivity parameter (κρ) that observations alone cannot due to gaps in coverage. However, we show that the inclusion of misfits to observed physical variables – such as in situ temperature, salinity, and pressure – currently accounted for in ECCO is not sufficient, as κρ from ECCO does not agree closely with any observationally derived product. These observationally derived κρ products were inferred from microstructure measurements, derived from Argo and conductivity–temperature–depth (CTD) data using a strain-based parameterization of fine-scale hydrographic structure, or calculated from climatological and seafloor data using a parameterization of tidal mixing. The κρ products are in close agreement with one another but have both measurement and structural uncertainties, whereas tracers can have relatively small measurement uncertainties. With the ultimate goal being to jointly improve the ECCO state estimate and representation of κρ in ECCO, we investigate whether adjustments in κρ due to inclusion of misfits to a tracer – dissolved oxygen concentrations from an annual climatology – would be similar to those due to inclusion of misfits to observationally derived κρ products. We do this by performing sensitivity analyses with ECCO. We compare multiple adjoint sensitivity calculations: one configuration uses misfits to observationally derived κρ, and the other uses misfits to observed dissolved oxygen concentrations. We show that adjoint sensitivities of dissolved oxygen concentration misfits to the state estimate's control space typically direct κρ to improve relative to the observationally derived values. These results suggest that the inclusion of oxygen in ECCO's misfits will improve κρ in ECCO, particularly in (sub)tropical regions. 

Abstract Ocean currents along the southeast Greenland coast play an important role in the climate system. They carry dense water over the Denmark Strait sill, freshwater from the Arctic and the Greenland Ice Sheet into the subpolar ocean, and warm Atlantic Ocean water into Greenland’s fjords, where it can interact with outlet glaciers. Observational evidence from moorings shows that the circulation in this region displays substantial subinertial variability (typically with periods of several days). For the dense water flowing over the Denmark Strait sill, this variability augments the time-mean transport. It has been suggested that the subinertial variability found in observations is associated with coastal trapped waves, whose properties depend on bathymetry, stratification, and the mean flow. Here, we use the output of a high-resolution realistic simulation to diagnose and characterize subinertial variability in sea surface height and velocity along the coast. The results show that the subinertial signals are coherent over hundreds of kilometers along the shelf. We find coastal trapped waves on the shelf and along the shelf break in two subinertial frequency bands—at periods of 1–3 and 5–18 days—that are consistent with a combination of mode-I waves and higher modes. Furthermore, we find that northeasterly barrier winds may trigger the 5–18-day shelf waves, whereas the 1–3-day variability is linked to high wind speeds over Sermilik Deep. 

Abstract Computational oceanography is the study of ocean phenomena by numerical simulation, especially dynamical and physical phenomena. Progress in information technology has driven exponential growth in the number of global ocean observations and the fidelity of numerical simulations of the ocean in the past few decades. The growth has been exponentially faster for ocean simulations, however. We argue that this faster growth is shifting the importance of field measurements and numerical simulations for oceanographic research. It is leading to the maturation of computational oceanography as a branch of marine science on par with observational oceanography. One implication is that ultraresolved ocean simulations are only loosely constrained by observations. Another implication is that barriers to analyzing the output of such simulations should be removed. Although some specific limits and challenges exist, many opportunities are identified for the future of computational oceanography. Most important is the prospect of hybrid computational and observational approaches to advance understanding of the ocean. 

Abstract The Denmark Strait Overflow (DSO) is an important contributor to the lower limb of the Atlantic meridional overturning circulation (AMOC). Determining DSO formation and its pathways is not only important for local oceanography but also critical to estimating the state and variability of the AMOC. Despite prior attempts to understand the DSO sources, its upstream pathways and circulation remain uncertain due to short-term (3–5 days) variability. This makes it challenging to study the DSO from observations. Given this complexity, this study maps the upstream pathways and along-pathway changes in its water properties, using Lagrangian backtracking of the DSO sources in a realistic numerical ocean simulation. The Lagrangian pathways confirm that several branches contribute to the DSO from the north such as the East Greenland Current (EGC), the separated EGC (sEGC), and the North Icelandic Jet (NIJ). Moreover, the model results reveal additional pathways from south of Iceland, which supplied over 16% of the DSO annually and over 25% of the DSO during winter of 2008, when the NAO index was positive. The southern contribution is about 34% by the end of March. The southern pathways mark a more direct route from the near-surface subpolar North Atlantic to the North Atlantic Deep Water (NADW), and needs to be explored further, with in situ observations.