The Arctic climate system is rapidly transitioning into a new regime with a reduction in the extent of sea ice, enhanced mixing in the ocean and atmosphere, and thus enhanced coupling within the ocean–ice–atmosphere system; these physical changes are leading to ecosystem changes in the Arctic Ocean. In this review paper, we assess one of the critically important aspects of this new regime, the variability of Arctic freshwater, which plays a fundamental role in the Arctic climate system by impacting ocean stratification and sea ice formation or melt. Liquid and solid freshwater exports also affect the global climate system, notably by impacting the global ocean overturning circulation. We assess how freshwater budgets have changed relative to the 2000–2010 period. We include discussions of processes such as poleward atmospheric moisture transport, runoff from the Greenland Ice Sheet and Arctic glaciers, the role of snow on sea ice, and vertical redistribution. Notably, sea ice cover has become more seasonal and more mobile; the mass loss of the Greenland Ice Sheet increased in the 2010s (particularly in the western, northern, and southern regions) and imported warm, salty Atlantic waters have shoaled. During 2000–2010, the Arctic Oscillation and moisture transport into the Arctic are in-phase and have a positive trend. This cyclonic atmospheric circulation pattern forces reduced freshwater content on the Atlantic–Eurasian side of the Arctic Ocean and freshwater gains in the Beaufort Gyre. We show that the trend in Arctic freshwater content in the 2010s has stabilized relative to the 2000s, potentially due to an increased compensation between a freshening of the Beaufort Gyre and a reduction in freshwater in the rest of the Arctic Ocean. However, large inter-model spread across the ocean reanalyses and uncertainty in the observations used in this study prevent a definitive conclusion about the degree of this compensation.

During ice-free periods, the Northern Sea Route (NSR) could be an attractive shipping route. The decline in Arctic sea-ice extent, however, could be associated with an increase in the frequency of the causes of severe weather phenomena and high wind-driven waves and the advection of sea ice could make ship navigation along the NSR difficult. Accurate forecasts of weather and sea ice are desirable for safe navigation, but large uncertainties exist in current forecasts, partly owing to the sparse observational network over the Arctic Ocean. Here, we show that the incorporation of additional Arctic observations improves the initial analysis and enhances the skill of weather and sea-ice forecasts, the application of which has socioeconomic benefits. Comparison of 63-member ensemble atmospheric forecasts, using different initial data sets, revealed that additional Arctic radiosonde observations were useful for predicting a persistent strong wind event. The sea-ice forecast, initialised by the wind fields that included the effects of the observations, skilfully predicted rapid wind-driven sea-ice advection along the NSR.

The relationship between cloud phase, ice‐nucleating particles (INPs), and ocean state is vital in climate system modeling. High wave conditions induced by the Arctic sea‐ice decline and intensified atmospheric forcing over the ice‐free ocean increase dynamical geochemical oceanic mixing and sea spray supply containing organic substances, which could act as INPs promoting formation of lower tropospheric ice‐containing clouds. Here, we show that the surface ocean state regulates INP concentration and ice cloud presence in the boundary layer. Arctic research cruise data from the marginal ice zone in the Chukchi Sea in November 2018 revealed high number concentrations of INPs active greater than °C and ice‐containing clouds under high wave conditions. Chemical analysis revealed high contents of organic carbon and sea salt that coincided with the increased oceanic turbidity. The findings suggest that elevated levels of marine organics will contribute to modification of cloud phase from liquid droplets to ice crystals.

The presence of clouds in the Arctic regulates the surface energy budget (SEB) over the sea‐ice surface and the ice‐free ocean. Following several previous field campaigns, the cloud‐radiation relationship, including cloud vertical structure and phase, has been elucidated; however, modeling of this relationship has matured slowly. In recognition of the recent decline in the Arctic sea‐ice extent, representation of the cloud system in numerical models should consider the effects of areas covered by sea ice and ice‐free areas. Using an in situ stationary meteorological observation data set obtained over the ice‐free Arctic Ocean by the Japanese Research Vessel Mirai (September 2014), coordinated evaluation of six regional climate models (RCMs) with nine model runs was performed by focusing on clouds and the SEB. The most remarkable findings were as follows: (1) reduced occurrence of unstable stratification with low‐level cloud water in all models in comparison to the observations, (2) significant differences in cloud water representations between single‐ and double‐moment cloud schemes, (3) extensive differences in partitioning of hydrometeors including solid/liquid precipitation, and (4) pronounced lower‐tropospheric air temperature biases. These issues are considered as the main sources of SEB uncertainty over ice‐free areas of the Arctic Ocean. The results from a coupled RCM imply that the SEB is constrained by both the atmosphere and the ocean (and sea ice) with considerable feedback. Coordinated improvement of both stand‐alone atmospheric and coupled RCMs would promote a more comprehensive and improved understanding of the Arctic air‐ice‐sea coupled system.

Constraints from ozone (O₃) observations over oceans are needed in addition to those from terrestrial regions to fully understand global tropospheric chemistry and its impact on the climate. Here, we provide a large data set of ozone and carbon monoxide (CO) levels observed (for 11 666 and 10 681 h, respectively) over oceans. The data set is derived from observations made during 24 research cruise legs of R/V Mirai during 2012 to 2017, in the Southern, Indian, Pacific, and Arctic oceans, covering the region from 67^∘ S to 75^∘ N. The data are suitable for critical evaluation of the over-ocean distribution of ozone derived from global atmospheric chemistry models. We first give an overview of the statistics in the data set and highlight key features in terms of geographical distribution and air mass type. We then use the data set to evaluate ozone mixing ratio fields from the tropospheric chemistry reanalysis version 2 (TCR-2), produced by assimilating a suite of satellite observations of multiple species into a global atmospheric chemistry model, namely CHASER. For long-range transport of polluted air masses from continents to the oceans, during which the effects of forest fires and fossil fuel combustion were recognized, TCR-2 gave an excellent performance in reproducing the observed temporal variations and photochemical buildup of O₃ when assessed from ΔO₃∕ΔCO ratios. For clean marine conditions with low and stable CO mixing ratios, two focused analyses were performed. The first was in the Arctic (> 70^∘ N) in September every year from 2013 to 2016; TCR-2 underpredicted O₃ levels by 6.7 ppbv (21 %) on average. The observed vertical profiles from O₃ soundings from R/V Mirai during September 2014 had less steep vertical gradients at low altitudes (> 850 hPa) than those obtained by TCR-2. This suggests the possibility of a more efficient descent of the O₃-rich air from above than assumed in the models. For TCR-2 (CHASER), dry deposition on the Arctic ocean surface might also have been overestimated. In the second analysis, over the western Pacific equatorial region (125–165^∘ E, 10^∘ S to 25^∘ N), the observed O₃ level more frequently decreased to less than 10 ppbv in comparison to that obtained with TCR-2 and also those obtained in most of the Atmospheric Chemistry Climate Model Intercomparison Project (ACCMIP) model runs for the decade from 2000. These results imply loss processes that are unaccounted for in the models. We found that the model's positive bias positively correlated with the daytime residence times of air masses over a particular grid, namely 165–180^∘ E and 15–30^∘ N; an additional loss rate of 0.25 ppbv h⁻¹ in the grid best explained the gap. Halogen chemistry, which is commonly omitted from currently used models, might be active in this region and could have contributed to additional losses. Our open data set covering wide ocean regions is complementary to the Tropospheric Ozone Assessment Report data set, which basically comprises ground-based observations and enables a fully global study of the behavior of O₃.

Recent cold winter extremes over Eurasia and North America have been considered to be a consequence of a warming Arctic. More accurate weather forecasts are required to reduce human and socioeconomic damages associated with severe winters. However, the sparse observing network over the Arctic brings errors in initializing a weather prediction model, which might impact accuracy of prediction results at midlatitudes. Here we show that additional Arctic radiosonde observations from the Norwegian young sea ICE expedition (N-ICE2015) drifting ice camps and existing land stations during winter improved forecast skill and reduced uncertainties of weather extremes at midlatitudes of the Northern Hemisphere. For two winter storms over East Asia and North America in February 2015, ensemble forecast experiments were performed with initial conditions taken from an ensemble atmospheric reanalysis in which the observation data were assimilated. The observations reduced errors in initial conditions in the upper troposphere over the Arctic region, yielding more precise prediction of the locations and strengths of upper troughs and surface synoptic disturbances. Errors and uncertainties of predicted upper troughs at midlatitudes would be brought with upper level high potential vorticity (PV) intruding southward from the observed Arctic region. This is because the PV contained a “signal” of the additional Arctic observations as it moved along an isentropic surface. This suggests that a coordinated sustainable Arctic observing network would be effective not only for regional weather services but also for reducing weather risks in locations distant from the Arctic.