With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

Deep and bottom water formation are crucial components of the global ocean circulation, yet they were poorly represented in the previous generation of climate models. We here quantify biases in Antarctic Bottom Water (AABW) and North Atlantic Deep Water (NADW) formation, properties, transport, and global extent in 35 climate models that participated in the latest Climate Model Intercomparison Project (CMIP6). Several CMIP6 models are correctly forming AABW via shelf processes, but 28 models in the Southern Ocean and all 35 models in the North Atlantic form deep and bottom water via open-ocean deep convection too deeply, too often, and/or over too large an area. Models that convect the least form the most accurate AABW but the least accurate NADW. The four CESM2 models with their overflow parameterisation are among the most accurate models. In the Atlantic, the colder the AABW, the stronger the abyssal overturning at 30^∘ S, and the further north the AABW layer extends. The saltier the NADW, the stronger the Atlantic Meridional Overturning Circulation (AMOC), and the further south the NADW layer extends. In the Indian and Pacific oceans in contrast, the fresher models are the ones which extend the furthest regardless of the strength of their abyssal overturning, most likely because they are also the models with the weakest fronts in the Antarctic Circumpolar Current. There are clear improvements since CMIP5: several CMIP6 models correctly represent or parameterise Antarctic shelf processes, fewer models exhibit Southern Ocean deep convection, more models convect at the right location in the Labrador Sea, bottom density biases are reduced, and abyssal overturning is more realistic. However, more improvements are required, e.g. by generalising the use of overflow parameterisations or by coupling to interactive ice sheet models, before deep and bottom water formation, and hence heat and carbon storage, are represented accurately.

Southern Ocean deep water properties and formation processes in climate models are indicative of their capability to simulate future climate, heat and carbon uptake, and sea level rise. Southern Ocean temperature and density averaged over 1986–2005 from 15 CMIP5 (Coupled Model Intercomparison Project Phase 5) climate models are compared with an observed climatology, focusing on bottom water. Bottom properties are reasonably accurate for half the models. Ten models create dense water on the Antarctic shelf, but it mixes with lighter water and is not exported as bottom water as in reality. Instead, most models create deep water by open ocean deep convection, a process occurring rarely in reality. Models with extensive deep convection are those with strong seasonality in sea ice. Optimum bottom properties occur in models with deep convection in the Weddell and Ross Gyres. Bottom Water formation processes are poorly represented in ocean models and are a key challenge for improving climate predictions.

Arctic Ocean properties and processes are highly relevant to the regional and global coupled climate system, yet still scarcely observed, especially in winter. Team OCEAN conducted a full year of physical oceanography observations as part of the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC), a drift with the Arctic sea ice from October 2019 to September 2020. An international team designed and implemented the program to characterize the Arctic Ocean system in unprecedented detail, from the seafloor to the air-sea ice-ocean interface, from sub-mesoscales to pan-Arctic. The oceanographic measurements were coordinated with the other teams to explore the ocean physics and linkages to the climate and ecosystem. This paper introduces the major components of the physical oceanography program and complements the other team overviews of the MOSAiC observational program. Team OCEAN’s sampling strategy was designed around hydrographic ship-, ice- and autonomous platform-based measurements to improve the understanding of regional circulation and mixing processes. Measurements were carried out both routinely, with a regular schedule, and in response to storms or opening leads. Here we present along-drift time series of hydrographic properties, allowing insights into the seasonal and regional evolution of the water column from winter in the Laptev Sea to early summer in Fram Strait: freshening of the surface, deepening of the mixed layer, increase in temperature and salinity of the Atlantic Water. We also highlight the presence of Canada Basin deep water intrusions and a surface meltwater layer in leads. MOSAiC most likely was the most comprehensive program ever conducted over the ice-covered Arctic Ocean. While data analysis and interpretation are ongoing, the acquired datasets will support a wide range of physical oceanography and multi-disciplinary research. They will provide a significant foundation for assessing and advancing modeling capabilities in the Arctic Ocean.

Deep water formation in climate models is indicative of their ability to simulate future ocean circulation, carbon and heat uptake, and sea level rise. Present-day temperature, salinity, sea ice concentration and ocean transport in the North Atlantic subpolar gyre and Nordic Seas from 23 CMIP5 (Climate Model Intercomparison Project, phase 5) models are compared with observations to assess the biases, causes and consequences of North Atlantic deep convection in models. The majority of models convect too deep, over too large an area, too often and too far south. Deep convection occurs at the sea ice edge and is most realistic in models with accurate sea ice extent, mostly those using the CICE model. Half of the models convect in response to local cooling or salinification of the surface waters; only a third have a dynamic relationship between freshwater coming from the Arctic and deep convection. The models with the most intense deep convection have the warmest deep waters, due to a redistribution of heat through the water column. For the majority of models, the variability of the Atlantic Meridional Overturning Circulation (AMOC) is explained by the volumes of deep water produced in the subpolar gyre and Nordic Seas up to 2 years before. In turn, models with the strongest AMOC have the largest heat export to the Arctic. Understanding the dynamical drivers of deep convection and AMOC in models is hence key to realistically forecasting Arctic oceanic warming and its consequences for the global ocean circulation, cryosphere and marine life.