Ocean observation buoys are currently powered-constrained by battery storage capacity or available solar power. Power constraints limit the number of measurements that can be made and the lifetime of the buoys. Ocean surface wave energy could be used for power production, but wave energy converters are not yet commercially available for ocean observation buoys. Here we present the design and testing of a drifting wave energy converter buoy using a pendulum transmission system (PTS). The wave energy converter buoy was designed to operate in Arctic temperatures and wave conditions, but it could be used in areas with warmer temperatures and larger waves. Field tests measured a maximum power production of 5 watts in waves with a significant wave height of 0.42 meters and a ten minute average power production of 37 milliwatts. Power production increased with the energy period and significant wave height. The energy harvesting capabilities of the PTS showed the utility of adding a wave energy conversion device to a drifting ocean observation buoy.

An approach to scalable surface-drifting buoys is needed to enable the high spatial and temporal resolution of oceanographic data that the science and meteorological communities are asking for. With the number of active buoys predicted to increase by a factor of 100 or more, the impact on the environment becomes even more important. Here, we present a pathway to a scalable and sustainable generation of buoys. We identify the main criteria to be used when developing such buoys to be low cost, with reliable data and neutral or even positive environmental impact. For each buoy subsystem — hull, electronics, energy generation and storage, sensors, and communication system — cutting-edge technological solutions are presented, many of them from emerging research in marine or other disciplines. We then assess the potential solutions against the design criteria and plot a path toward small, environmentally friendly, low-cost, and low-power buoys.

Weather and climate extremes are increasingly occurring in the Arctic. In this Review, we evaluate historical and projected changes in rare Arctic extremes across the atmosphere, cryosphere and ocean and elucidate their driving mechanisms. Clear shifts occur in mean and extreme distributions after ~2000. For instance, pre-2000 to post-2000 observational probabilities of 1.5 standard deviation events increase by 20% for atmospheric heat waves, 76.7% for Atlantic layer warm events, 83.5% for Arctic sea ice loss and 62.9% for Greenland Ice Sheet melt extent — in many cases, low probability, rare extreme events in the early period become the norm in the latter period. These observed changes can be explained using a 'pushing and triggering' concept, representing interplay between external forcing and internal variability: long-term warming destabilizes the climate system and 'pushes' it to a new state, allowing subsequent variability associated with large-scale atmosphere–ocean–ice interactions and synoptic systems to 'trigger' extreme events over different timescales. Ongoing anthropogenic warming is expected to further increase the frequency and magnitude of extremes, such that simulated probabilities of 1.5 standard deviation events increase by 72.6% for atmospheric heat waves, 68.7% for Atlantic layer warm events and 93.3% for Greenland Ice Sheet melt rate between historic (1984–2014) and future (2069–2099) periods under a very high emission scenario. Future research should prioritize the development of physically based metrics, enhance high-resolution observation and modelling capabilities and improve understanding of multiscale Arctic climate drivers.

The Arctic Ocean has seen a profound sea ice loss during the summer, with changes most pronounced in the Western Arctic. This has resulted in the Chukchi Sea, located just north of Bering Strait, being ice-free by the end of summer, i.e. September, since 2000, except during 2024. Here using the ice thickness budget, we investigate the processes responsible for the return of summer sea ice to the region during 2024. We show that an exceptional ice convergence event in February 2024, along with additional events in the winter and spring, resulted in ice thicknesses along the Siberian coast of the Chukchi Sea through the summer months that exceeded values last seen in the region during the late 20th century. The reduced penetration of shortwave radiation through the anomalously thick ice contributed to a delay in melt, contributing to the presence of sea ice in the region during the summer of 2024. We also argue that a thinner and more mobile ice pack contributed to this remarkable return of summer sea ice after a 25-year hiatus, opening the possibility of similar events in the future.

Sea Surface Salinity (SSS) anomalies and near-surface thermohaline stratification are key parameters to improve our understanding of sea-ice retreat and formation in polar regions. Since 2010, the remote sensing salinity missions ESA SMOS (Soil Moisture and Ocean Salinity) and NASA SMAP (Soil Moisture Active Passive) offer unprecedented SSS observations globally (SSS_SMOS and SSS_SMAP respectively). In this study, we compare these observations with in-situ salinity observations (SSS_in-situ) made during the NASA Salinity Field Campaign SASSIE (Salinity and Stratification at Sea-Ice Edge) during the fall of 2022. The SASSIE SSS_in-situ were collected by 9 different platforms: CastAway and Underway CTD, Wave Gliders, Thermosalinograph, Snake-salinity, SWIFT drifters, UpTempO buoys, Jet-SSP and ALTO and ALAMO profilers. Because satellite SSS retrievals are impacted by land and sea-ice contaminations, cold temperatures, and surface roughness, mean differences, RMSD and STD between satellite SSS and SSS_in-situ are examined as a function of distance from the coast and sea-ice edge, sea surface temperature (SST) and wind speed. We find that SSS_SMOS and SSS_SMAP are well correlated (0.66 and 0.78 respectively) with similar RMSD when compared with SSSin-situ. Close to the coast (0–150 km), SSS_SMAP compare better with SSSin-situ with RMSD (<2 g/kg) lower than that from SSS_SMOS. Near the sea-ice edge (0–150 km), SSS_SMOS compare better with SSS_in-situ with RMSD (<2.5 g/kg) lower than that from SSS_SMAP. In cold water (SST<1.5°C) and low wind speed conditions (< 7 m/s), both SSS_SMOS and SSS_SMAP are consistent with each other. The RMSD between SSS_SMAP and SSS_in-situ decreases considerably (<1 g/kg) when SST >1.5°C, while the RMSD between SSS_SMOS and SSS_in-situ shows less dependence on SST.

The stability of the upper ocean is crucial for the exchange of momentum, heat, and salt between sea ice and subsurface warm water in the Arctic Ocean’s Beaufort Gyre (BG) region. Here, based on multiple in-situ observations, the shifting phases of the BG during 2003–2023 are objectively defined. We find that the potential energy anomaly (PEA) in the upper 55 m decreased from 130.9 ± 2.3 J/m³ during 2006–2012 with BG intensification to 90.3 ± 2.0 J/m³ during 2013–2019 with BG relaxation. Further, the mixed layer became saltier and deeper across all seasons. Decreasing PEA indicates an overall weaker stratification in the upper water column which promotes stronger vertical entrainment. We also find that the mixed layer heat content increased across nearly all seasons, except during July to September (summer). Our analysis using a Price–Weller–Pinkel model suggests that the cause of this warming was not atmospheric heat fluxes from above, but rather subsurface heat entrainment upward. The key mechanism is the seasonal amplitude of PEA is smaller during 2013–2019 when the BG relaxes, thereby allowing mixing to greater depths under the same surface salt flux as in 2006–2012. This is important for the future evolution of the sea ice melting and oceanic vertical mixing if the BG relaxes further.

There are many challenges associated with obtaining high-fidelity sea ice concentration (SIC) information, and products that rely solely on passive microwave measurements often struggle to represent conditions at low concentration, especially within the marginal ice zone and during periods of active melt. Here, we present a newly gridded SIC product for the Alaskan Arctic, generated with data from the National Weather Service Alaska Sea Ice Program (hereafter referred to as ASIP), that synthesizes a variety of satellite SIC and in situ observations from 2007–present. These SIC fields have been primarily used for operational purposes and have not yet been gridded or independently validated. In this study, we first grid the ASIP product into 0.05° resolution in both latitude and longitude (hereafter referred to as gridded ASIP, or grASIP). We then perform extensive intercomparison with an international database of ship-based in situ SIC observations, supplemented with observations from saildrones. Additionally, an intercomparison between three ice products is performed: (i) grASIP, (ii) a high-resolution passive microwave product (AMSR2), and (iii) a product available from the National Snow and Ice Data Center (MASIE) that originates from the US National Ice Center (USNIC) operational IMS product. This intercomparison demonstrates that all products perform similarly when compared to in situ observations generally, but grASIP outperforms the other products during periods of active melt and in low-SIC regions. Furthermore, we show that the similarity in performance among products is partly due to the deficiencies in the in situ observations' geographical distribution, as most in situ observations are far from the ice edge in locations where all products agree. We find that the grASIP ice edge is generally farther south than both the AMSR2 and MASIE ice edges by an average of approximately 50 km in winter and 175 km in summer for grASIP vs. AMSR2 and 10 km in winter and 40 km in summer for grASIP vs. MASIE.

As our planet warms, Arctic sea ice coverage continues to decline, resulting in complex feedbacks with the climate system. The core objective of NASA's Salinity and Stratification at the Sea Ice Edge (SASSIE) mission is to understand how ocean salinity and near-surface stratification affect upper-ocean heat content and thus sea ice freeze and melt. SASSIE specifically focuses on the formation of Arctic Sea ice in autumn. The SASSIE field campaign in 2022 collected detailed observations of upper-ocean properties and meteorology near the sea ice edge in the Beaufort Sea using ship-based and piloted and drifting assets. The observations collected during SASSIE include vertical profiles of stratification up to the sea surface, air–sea fluxes, and ancillary measurements that are being used to better understand the role of salinity in coupled Arctic air–sea–ice processes. This publication provides a detailed overview of the activities during the 2022 SASSIE campaign and presents the publicly available datasets generated by this mission (available at https://podaac.jpl.nasa.gov/SASSIE, last access: 29 May 2024; DOIs for individual datasets in the "Data availability" section), introducing an accompanying repository that highlights the numerical routines used to generate the figures shown in this work.

The Arctic is one of the most important regions in the world;s oceans for understanding the impacts of a changing climate. Yet, it is also difficult to measure because of extreme weather and ice conditions. In this work, we directly compare four datasets from the Group for High-Resolution Sea Surface Temperature (GHRSST) with a NASA Saildrone deployment along the Alaskan Coast and the Bering Sea and Bering Strait. The four datasets used are the Remote Sensing Systems Microwave Infrared Optimally Interpolated (MWIR) product, the Canadian Meteorological Center (CMC) product, the Daily Optimally Interpolated Product (DOISST), and the Operational Sea Surface Temperature and Ice Analysis (OSTIA) product. Spatial sea surface temperature (SST) gradients were derived for both the Saildrone deployment and GHRSST products, with the GHRSST products collocated with the Saildrone deployment. Overall, statistics indicate that the OSTIA product had a correlation of 0.79 and a root mean square difference of 0.11°C/km when compared with Saildrone. CMC had the highest correlation of 0.81. Scatter plots indicate that OSTIA had the slope closest to one, thus best reproducing the magnitudes of the Saildrone gradients. Differences increased at latitudes >65°N where sea ice would have a greater impact. A trend analysis was then performed on the gradient fields. Overall, positive trends in gradients occurred in areas along the coastal regions. A negative trend occurred at approximately 60&$176;N. A major finding of this study is that future work needs to revolve around the impact of changing ice conditions on SST gradients. Another major finding is that a northward shift in the southern ice edge occurred after 2010 with a maxima at approximately 2019. This indicates that the shift of the southern ice edge is not gradual but has dramatically increased over the last decade. Future work needs to revolve around examining the possible causes for this northward shift.

This study quantifies the state-of-the-art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multi-model dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 17 dynamical models. Prediction skill is compared over the period 2001–2020 for predictions of Pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on June 1, July 1, August 1, and September 1. This diverse set of statistical and dynamical models can individually predict linearly detrended Pan-Arctic SIE anomalies with skill, and a multi-model median prediction has correlation coefficients of 0.79, 0.86, 0.92, and 0.99 at these respective initialization times. Regional SIE predictions have similar skill to Pan-Arctic predictions in the Alaskan and Siberian regions, whereas regional skill is lower in the Canadian, Atlantic, and Central Arctic sectors. The skill of dynamical and statistical models is generally comparable for Pan-Arctic SIE, whereas dynamical models outperform their statistical counterparts for regional and local predictions. The prediction systems are found to provide the most value added relative to basic reference forecasts in the extreme SIE years of 1996, 2007, and 2012. SIE prediction errors do not show clear trends over time, suggesting that there has been minimal change in inherent sea ice predictability over the satellite era. Overall, this study demonstrates that there are bright prospects for skillful operational predictions of September sea ice at least three months in advance.

The Arctic sea ice cover has decreased rapidly over the last few decades both in extent and thickness. Here we present multi-year (2013–2022) observations of sea ice thickness in the northwestern Barents Sea based on Upward Looking Sonar measurements and show that the winter sea ice has become thicker over the last decade. Sea ice thickness from the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) reproduces both the observed variability and recent 10-year trend and shows that this thickening (0.24 m decade^-1) has not been seen since the 1990s. Using PIOMAS we find that the recent increase in sea ice thickness can be explained by increased sea ice freezing as a result of lower temperatures in the ocean and in the atmosphere. The recent thickening is set in the context of a long-term thinning trend, with PIOMAS showing much thinner ice now than in the 1980s.

The Arctic region has warmed nearly four times faster than the global average since 1979, with far-reaching global implications. However, model projections of Arctic warming rates are uncertain and one key component is the ocean heat transport (OHT) into the Arctic Ocean. Here we use high-resolution historical and future climate simulations to show that the OHT through the Bering Strait exerts a more substantial influence on Arctic warming than previously recognized. The high-resolution ensemble exhibits a 20% larger warming rate for 2006–2100 compared with standard low-resolution model simulations. The enhanced Arctic warming in the high-resolution simulations is primarily attributable to an increased OHT through the narrow and shallow Bering Strait that is nearly four times larger than in the low-resolution simulations. Consequently, the projected rate of Arctic warming by low-resolution climate simulations is likely to be underestimated due to the model resolution being insufficient to capture future changes in Bering Strait OHT.

Available observations and a theoretical simulation are used to explore the consistency and relationship between sea surface temperature (SST) and sea ice concentration (SIC) within open-ocean-sea ice mixed satellite pixels as a function of grid resolution. The maximum limiting SST value for a specified SIC and spatial resolution is first examined within collocated satellite-derived products contained within existing Level 4 SST analyses distributed using the data specification from the Group for High Resolution Sea Surface Temperature. The shape of the interdependence is further validated with manually quality-controlled buoy SST and SIC collocations. A parametric equation for the limiting SST value is derived from simulations of a mixed ocean/ice pixel with specified ice fraction and a linear SST gradient extending away from the ice edge. The exponential curve matching the observed interdependence suggests a maximum 5 km pixel-averaged SST at SIC values approaching zero between 6 and 8°C. This maximum value is significantly greater than the previously assumed limiting values of ~3°C and the corresponding SST gradient is larger than those typically observed with satellite SST products, but agrees well with recent Saildrone SST observations near ice. The curve provides a conservative limit with which inconsistent SST/SIC pairings can be identified, not only near the ice edge but at intermediate ice concentrations. Application of the filter improves the agreement between the SST/SIC relationship in satellite products and available Saildrone observations as well as the internal consistency of the different satellite products.

As Arctic sea ice retreats during the melt season, the upper ocean warms in response to atmospheric heat fluxes. Overall, clouds reduce these fluxes in summer, but how the radiative impacts of clouds on ocean warming could change as sea ice declines has not been documented. In global climate model simulations with variable CO₂, the timing of sea ice retreat strongly influences the amplitude of cloud-induced summer cooling at the ocean surface. Under pre-industrial CO₂ concentrations, summer clouds have little direct effect on maximum annual sea surface temperatures (SST). When CO₂ concentrations increase, sea ice retreats earlier, allowing more solar radiation to warm the ocean. Clouds can counteract this summer warming by reflecting solar radiation back to space. Consequently, clouds explain up to 13% more variability in maximum annual SST under modern-day CO₂ concentrations. Maximum annual SST are three times more sensitive to summer clouds when CO₂ concentrations are four times pre-industrial levels.

Recent progress in understanding Beaufort Gyre (BG) dynamics reveals an important role of ice-ocean stress in stabilizing BG freshwater content (FWC) over seasonal to interannual timescales. But how the BG's stratification and FWC respond to surface forcing over decadal timescales has not been fully explored. Using a global ocean-sea ice model, we partition the BG into upper, middle (halocline), and lower (thermocline) layers and perform a volume budget analysis over 1948–2017. We find that the BG's asymmetric geometry (with steep and tight isohalines over continental slopes relative to the deep basin) is key in determining the mean volume transport balance. We further find that a net Ekman suction during 1983–1995 causes the upper and middle layers to deflate isopycnally, while an enhanced Ekman pumping during 1996–2017 causes these layers to inflate both isopycnally and diapycnally, the latter via anomalous flux from the upper to the middle layer.

Fresh water plays a pivotal role in the Arctic Ocean's climate, as salinity governs upper ocean stratification, convection, and the promotion of seasonal sea ice growth or melt. The Beaufort Gyre contains a significant amount of fresh water; however, there is limited understanding of the role that the Russian Arctic Shelf plays in the Arctic Ocean's freshwater content (FWC). Here, we use salinity from the European Centre for Medium-Range Weather Forecasts' (ECMWF) Ocean Reanalysis System 5 (ORAS5) product to first compare with in situ and satellite observations. We then conduct analyses over the years 1979–2018 to examine FWC and salinity on the Russian Shelf (30°E–180°E; shallower than 200 m depth), in the Beaufort Gyre (130°W–170°W, 70.5°N–80.5°N), and over the Arctic Ocean as a whole (northward of 66°N). Our results indicate that the Russian Shelf consists of ~16% of the total freshwater volume (FWV) in the Arctic Ocean (80,7623 km³) and has a negative trend (–15.63 km³/year), primarily influenced by negative trends in the Kara and Laptev Seas. We also find a notable regime shift during the summer of 2007 for both the Beaufort Gyre (increased FWV) and Russian Shelf (decreased FWV). When computing Arctic FWV changes before and after this 2007 regime shift, there is up to a 25% error if the Russian Shelf's FWV is omitted.

The Arctic Ocean has seen a remarkable reduction in sea ice coverage, thickness and age since the 1980s. These changes are most pronounced in the Beaufort Sea, with a transition around 2007 from a regime dominated by multi-year sea ice to one with large expanses of open water during the summer. Using satellite-based observations of sea ice, an atmospheric reanalysis and a coupled ice-ocean model, we show that during the summers of 2020 and 2021, the Beaufort Sea hosted anomalously large concentrations of thick and old ice. We show that ice advection contributed to these anomalies, with 2020 dominated by eastward transport from the Chukchi Sea, and 2021 dominated by transport from the Last Ice Area to the north of Canada and Greenland. Since 2007, cool season (fall, winter, and spring) ice volume transport into the Beaufort Sea accounts for ~45% of the variability in early summer ice volume — a threefold increase from that associated with conditions prior to 2007. This variability is likely to impact marine infrastructure and ecosystems.

Novel observations of the seasonal evolution of an ice algal bloom on the Chukchi shelf were collected by two autonomous buoys deployed 180 km apart in first-year drifting sea ice. High attenuation of blue light in the bottom of the ice indicated considerable accumulation of ice algae biomass with derived Chlorophyll-a concentrations (Chl a) up to 184 mg m^-2. Differences in the magnitude and persistence of ice algae biomass under each buoy appear to have been driven by differences in snow thickness, as ice thickness was similar between the sites. Minimal snow cover (0.02 m) around one buoy was associated with algae growth beginning in mid-May and lasting 70 days. The second buoy had notably more snow (0.4 m), causing ice algae production to lag behind the first site by approximately 4 weeks. The delay in growth diminished the peak of ice algae Chl a and duration compared to the first site. Light attenuation through the ice was intense enough at both buoys to have a potentially inhibiting impact on water column phytoplankton Chl a. Modeling ice algae growth with observed light intensities determined that nutrients were the limiting resource at the low snow site. In contrast, the algae at the high snow site were light-limited and never nutrient-limited. These data point toward changes in ice algae phenology with an earlier and longer window for growth; and nutrients rather than light determining the longevity and magnitude of production.

Observations from uncrewed surface vehicles (saildrones) in the Bering, Chukchi, and Beaufort Seas during June–September 2019 were used to evaluate initial conditions and forecasts with lead times up to 10 days produced by eight operational numerical weather prediction centers. Prediction error behaviors in pressure and wind are found to be different from those in temperature and humidity. For example, errors in surface pressure were small in short-range (<6 days) forecasts, but they grew rapidly with increasing lead time beyond 6 days. Non-weighted multimodel means outperformed all individual models approaching a 10-day forecast lead time. In contrast, errors in surface air temperature and relative humidity could be large in initial conditions and remained large through 10-day forecasts without much growth, and non-weighted multimodel means did not outperform all individual models. These results following the tracks of the mobile platforms are consistent with those at a fixed location. Large errors in initial condition of sea surface temperature (SST) resulted in part from the unusual Arctic surface warming in 2019 not captured by data assimilation systems used for model initialization. These errors in SST led to large initial and prediction errors in surface air temperature. Our results suggest that improving predictions of surface conditions over the Arctic Ocean requires enhanced in situ observations and better data assimilation capability for more accurate initial conditions as well as better model physics. Numerical predictions of Arctic atmospheric conditions may continue to suffer from large errors if they do not fully capture the large SST anomalies related to Arctic warming.

There is high demand for complete satellite SST maps (or L4 SST analyses) of the Arctic regions to monitor the rapid environmental changes occurring at high latitudes. Although there are a plethora of L4 SST products to choose from, satellite-based products evolve constantly with the advent of new satellites and frequent changes in SST algorithms, with the intent of improving absolute accuracies. The constant change of these products, as reflected by the version product, make it necessary to do periodic validations against in situ data. Eight of these L4 products are compared here against saildrone data from two 2019 campaigns in the western Arctic, as part of the MISST project. The accuracy of the different products is estimated using different statistical methods, from standard and robust statistics to Taylor diagrams. Results are also examined in terms of spatial scales of variability using auto- and cross-spectral analysis. The three products with the best performance, at this point and time, are used in a case study of the thermal features of the Yukon–Kuskokwim delta. The statistical analyses show that two L4 SST products had consistently better relative accuracy when compared to the saildrone subsurface temperatures. Those are the NOAA/NCEI DOISST and the RSS MWOI SSTs. In terms of the spectral variance and feature resolution, the UK Met Office OSTIA product appears to outperform all others at reproducing the fine scale features, especially in areas of high spatial variability, such as the Alaska coast. It is known that L4 analyses generate small-scale features that get smoothed out as the SSTs are interpolated onto spatially complete grids. However, when the high-resolution satellite coverage is sparse, which is the case in the Arctic regions, the analyses tend to produce more spurious small-scale features. The analyses here indicate that the high-resolution coverage, attainable with current satellite infrared technology, is too sparse, due to cloud cover to support very high resolution L4 SST products in high latitudinal regions. Only for grid resolutions of ~9–10 km or greater does the smoothing of the gridding process balance out the small-scale noise resulting from the lack of high-resolution infrared data. This scale, incidentally, agrees with the Rossby deformation radius in the Arctic Ocean (~10 km).

Ocean-to-ice heat flux (OHF) is important in regulating the variability of sea ice mass balance. Using surface drifting buoy observations, we show that during winter in the Arctic Ocean's Beaufort Gyre region, OHF increased from 0.76 ± 0.05 W/m² over 2006–2012 to 1.63 ± 0.08 W/m² over 2013–2018. We find that this is a result of thinner and less-compact sea ice that promotes enhanced winter ice growth, stronger ocean vertical convection, and subsurface heat entrainment. In contrast, Ekman upwelling declined over the study period, suggesting it had a secondary contribution to OHF changes. The enhanced ice growth creates a cooler, saltier, and deeper ocean surface mixed layer. In addition, the enhanced vertical temperature gradient near the mixed layer base in later years favors stronger entrainment of subsurface heat. OHF and its increase during 2006–2018 were not geographically uniform, with hot spots found in an upwelling region where ice was most seasonally variable.

Low-frequency internal atmospheric variability accounts for about one quarter of observed Arctic Ocean warming over the past four decades and 60% of the accelerated warming from 2000 to 2018.

The observed upper (0–-50 m) Arctic Ocean warming since 1979 has been primarily attributed to anthropogenically driven changes in the high latitudes. Here, using both observational and modeling analyses, we demonstrate that a multiyear trend in the summertime large-scale atmospheric circulation, which we ascribe to internal variability, has played an important role in upper ocean warming in summer and fall over the past four decades due to sea ice-albedo effect induced by atmospheric dynamics. Nudging experiments in which the wind fields are constrained toward the observed state support this mechanism and suggest that the internal variability contribution to recent upper Arctic Ocean warming accounts for up to one quarter of warming over the past four decades and up to 60% of warming from 2000 to 2018. This suggests that climate models need to replicate this important internal process in order to realistically simulate Arctic Ocean temperature variability and trends.

The Sea Ice Prediction Network—Phase 2 (SIPN2) is a multi-agency international effort to compare seasonal sea ice prediction methods and results at pan-Arctic, pan-Antarctic, and regional spatial scales using a multi-disciplinary approach that includes modeling, data analysis, and scientific networks. SIPN2 builds on lessons learned during the first phase of the Sea Ice Prediction Network (2014–2017), and since then has expanded in scope with activities that have included community seminars, workshops, and extensive research on the topic of seasonal sea ice prediction.

The L-band radiometer onboard the soil moisture active passive (SMAP) mission is used to retrieve sea surface salinity (SSS) over global ocean. In the Arctic seas, one of the major challenges of SSS remote sensing is the presence of sea ice. This paper proposes a data-driven ice correction (IC) algorithm which extracts emission from the water portion of measured brightness temperature (TB) in scenes mixed with water and ice. Emission of the ice portion was removed based on estimation according to the ice fraction ( f_ice ) in the satellite footprint and ice signature derived from surrounding pixels. The IC algorithm is applied to SMAP TB data to obtain TB with IC (TB_IC ), which are used for SSS retrieval using the standard JPL SMAP CAP processing system. We show that the algorithm is most effective near the ice edge, thereby increasing the f_ice threshold for possible SSS retrieval to 15% from the current 3% without IC. SMAP SSS are validated using in situ salinity collected during NASA's Ocean Melting Greenland (OMG) mission from 2016 to 2020 along the Greenland coast. The number of collocations between OMG and SMAP daily gridded salinity increased by more than 30% with IC. The statistical analysis shows a similar retrieval accuracy with or without IC, with the standard deviation of the difference between OMG and SMAP of 1.41 psu (with IC) and 1.42 psu (without IC). The bias-adjusted SMAP SSS depicts salinity patterns and gradients around Greenland consistent with OMG measurements.

The Arctic Ocean's Wandel Sea is the easternmost sector of the Last Ice Area, where thick, old sea ice is expected to endure longer than elsewhere. Nevertheless, in August 2020 the area experienced record-low sea ice concentration. Here we use satellite data and sea ice model experiments to determine what caused this record sea ice minimum. In our simulations there was a multi-year sea-ice thinning trend due to climate change. Natural climate variability expressed as wind-forced ice advection and subsequent melt added to this trend. In spring 2020, the Wandel Sea had a mixture of both thin and — unusual for recent years — thick ice, but this thick ice was not sufficiently widespread to prevent the summer sea ice concentration minimum. With continued thinning, more frequent low summer sea ice events are expected. We suggest that the Last Ice Area, an important refuge for ice-dependent species, is less resilient to warming than previously thought.

More high-quality, in situ observations of essential marine variables are needed over the seasonal ice zone to better understand Arctic (or Antarctic) weather, climate, and ecosystems. To better assess the potential for arrays of uncrewed surface vehicles (USVs) to provide such observations, five wind-driven and solar-powered saildrones were sailed into the Chukchi and Beaufort Seas following the 2019 seasonal retreat of sea ice. They were equipped to observe the surface oceanic and atmospheric variables required to estimate air-sea fluxes of heat, momentum and carbon dioxide. Some of these variables were made available to weather forecast centers in real time. Our objective here is to analyze the effectiveness of existing remote ice navigation products and highlight the challenges and opportunities for improving remote ice navigation strategies with USVs. We examine the sources of navigational sea-ice distribution information based on post-mission tabulation of the sea-ice conditions encountered by the vehicles. The satellite-based ice-concentration analyses consulted during the mission exhibited large disagreements when the sea ice was retreating fastest (e.g., the 10% concentration contours differed between analyses by up to ~175 km). Attempts to use saildrone observations to detect the ice edge revealed that in situ temperature and salinity measurements varied sufficiently in ice bands and open water that it is difficult to use these variables alone as a reliable ice-edge indicator. Devising robust strategies for remote ice zone navigation may depend on developing the capability to recognize sea ice and initiate navigational maneuvers with cameras and processing capability onboard the vehicles.

The Arctic Ocean is one of the most important and challenging regions to observe — it experiences the largest changes from climate warming, and at the same time is one of the most difficult to sample because of sea ice and extreme cold temperatures. Two NASA-sponsored deployments of the Saildrone vehicle provided a unique opportunity for validating sea-surface salinity (SSS) derived from three separate products that use data from the Soil Moisture Active Passive (SMAP) satellite. To examine possible issues in resolving mesoscale-to-submesoscale variability, comparisons were also made with two versions of the Estimating the Circulation and Climate of the Ocean (ECCO) model (Carroll, D; Menmenlis, D; Zhang, H.). The results indicate that the three SMAP products resolve the runoff signal associated with the Yukon River, with high correlation between SMAP products and Saildrone SSS. Spectral slopes, overall, replicate the –2.0 slopes associated with mesoscale-submesoscale variability. Statistically significant spatial coherences exist for all products, with peaks close to 100 km. Based on these encouraging results, future research should focus on improving derivations of satellite-derived SSS in the Arctic Ocean and integrating model results to complement remote sensing observations.

The Beaufort Gyre (BG), the largest Arctic Ocean freshwater reservoir, has drastically increased its liquid freshwater content by 40% in the past two decades. If released within a short period, the excess freshwater could potentially impact the large-scale ocean circulation by freshening the upper subpolar North Atlantic. Here, we track BG-sourced freshwater using passive tracers in a global ocean sea-ice model and show that this freshwater exited the Arctic mostly through the Canadian Arctic Archipelago, rather than Fram Strait, during an historical release event in 1983–1995. The Labrador Sea is the most affected region in the subpolar North Atlantic, with a freshening of 0.2 psu on the western shelves and 0.4 psu in the Labrador Current. Given that the present BG freshwater content anomaly is twice the historical analog studied here, the impact of a future rapid release on Labrador Sea salinity could be significant, easily exceeding similar fluxes from Greenland meltwater.

Less than three decades ago only a small fraction of the Arctic Ocean (AO) was ice free and then only for short periods. The ice cover kept sea surface p CO₂ at levels lower relative to other ocean basins that have been exposed year round to ever increasing atmospheric levels. In this study, we evaluate sea surface p CO₂ measurements collected over a 6‐year period along a fixed cruise track in the Canada Basin. The measurements show that mean p CO₂ levels are significantly higher during low ice years. The p CO₂ increase is likely driven by ocean surface heating and uptake of atmospheric CO₂ with large interannual variability in the contributions of these processes. These findings suggest that increased ice‐free periods will further increase sea surface p CO₂, reducing the Canada Basin's current role as a net sink of atmospheric CO₂.

Climate model projections suggest a substantial decrease of sea ice export into the outflow areas of the Arctic Ocean over the 21st century. Fram Strait, located in the Greenland Sea sector, is the principal gateway for ice export from the Arctic Ocean. The consequences of lower sea ice flux through Fram Strait on ocean dynamics and primary production in the Greenland Sea remain unknown. By using the most recent 16 years (2003–2018) of satellite imagery available and hydrographic in situ observations, the role of exported Arctic sea ice on water column stratification and phytoplankton production in the Greenland Sea is evaluated. Years with high Arctic sea ice flux through Fram Strait resulted in high sea ice concentration in the Greenland Sea, stronger water column stratification, and an earlier spring phytoplankton bloom associated with high primary production levels. Similarly, years with low Fram Strait ice flux were associated with a weak water column stratification and a delayed phytoplankton spring bloom. This work emphasizes that sea ice and phytoplankton production in subarctic "outflow seas" can be strongly influenced by changes occurring in the Arctic Ocean.

Arctic sea surface temperatures (SSTs) are estimated mostly from satellite sea ice concentration (SIC) estimates. In regions with sea ice the SST is the temperature of open water or of the water under the ice. A number of different proxy SST estimates based on SIC have been developed. In recent years more Arctic quality-control buoy SSTs have become available, allowing better validation of different estimates and the development of improved proxy estimates. Here proxy SSTs from different approaches are evaluated and an improved proxy SST method is shown. The improved proxy SSTs were tested in an SST analysis, and showed reduced bias and random errors compared to the Arctic buoy SSTs. Almost all reduction in errors is in the warm melt season. In the cold season the SIC is typically high and all estimates tend to have low errors. The improved method will be incorporated into an operational SST analysis.

Salinity is a critical parameter in the Arctic Ocean, having potential implications for climate and weather. This study presents the first systematic analysis of 6 commonly used sea surface salinity (SSS) products from the National Aeronautics and Space Administration (NASA) Aquarius and Soil Moisture Active Passive (SMAP) satellites and the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission, in terms of their consistency among one another and with in-situ data. Overall, the satellite SSS products provide a similar characterization of the time mean SSS large-scale patterns and are relatively consistent in depicting the regions with strong SSS temporal variability. When averaged over the Arctic Ocean, the SSS show an excellent consistency in describing the seasonal and interannual variations. Comparison of satellite SSS with in-situ salinity measurements along ship transects suggest that satellite SSS captures salinity gradients away from regions with significant sea-ice concentration. The root-mean square differences (RMSD) of satellite SSS with respect to in-situ measurements improves with increasing temperature, reflecting the limitation of L-band radiometric sensitivity to SSS in cold water. However, the satellite SSS biases with respect to the in-situ measurements do not show a consistent dependence on temperature. The results have significant implications for the calibration and validation of satellite SSS as well as for the modeling community and the design of future satellite missions.

The recent dramatic decline of sea ice in the western Arctic Ocean changes the transfer of momentum across the ice‐ocean boundary layer. The surface stress energy input through the surface geostrophic current in the Beaufort Gyre (BG) based on a numerical model is 0.03 mW/m² in 1992––2004 versus 0.23 mW/m² in 2005–2017. This energy input is primarily concentrated over the southern Canada Basin and the Chukchi Sea. It is 1.38 x 10¹⁶ J in observations versus 4.90 × 10¹⁶ J in the model in the BG during 2003–2014. We find that some well‐known freshwater changes in the BG over 1992–2017 resulted from episodic extrema of energy input in 2007, 2012, and 2016. In particular, most of the energy input in 2007 was transformed into potential energy (57%) which resulted in a new state of freshwater budget. Our study suggests that as of 2016, the BG had not yet reached a saturated freshwater state. Our results provide a way to predict the future changes of BG freshwater content.

Sea-surface temperature (SST) was one of the first ocean variables to be studied from earth observation satellites. Pioneering images from infrared scanning radiometers revealed the complexity of the surface temperature fields, but these were derived from radiance measurements at orbital heights and included the effects of the intervening atmosphere. Corrections for the effects of the atmosphere to make quantitative estimates of the SST became possible when radiometers with multiple infrared channels were deployed in 1979. At the same time, imaging microwave radiometers with SST capabilities were also flown. Since then, SST has been derived from infrared and microwave radiometers on polar orbiting satellites and from infrared radiometers on geostationary spacecraft. As the performances of satellite radiometers and SST retrieval algorithms improved, accurate, global, high resolution, frequently sampled SST fields became fundamental to many research and operational activities. Here we provide an overview of the physics of the derivation of SST and the history of the development of satellite instruments over half a century. As demonstrated accuracies increased, they stimulated scientific research into the oceans, the coupled ocean-atmosphere system and the climate. We provide brief overviews of the development of some applications, including the feasibility of generating Climate Data Records. We summarize the important role of the Group for High Resolution SST (GHRSST) in providing a forum for scientists and operational practitioners to discuss problems and results, and to help coordinate activities world-wide, including alignment of data formatting and protocols and research. The challenges of burgeoning data volumes, data distribution and analysis have benefited from simultaneous progress in computing power, high capacity storage, and communications over the Internet, so we summarize the development and current capabilities of data archives. We conclude with an outlook of developments anticipated in the next decade or so.

The Arctic Ocean's oldest and thickest sea ice lies along the ~2,000 km arc from the western Canadian Arctic Archipelago to the northern coast of Greenland. Climate models suggest that this region will be the last to lose its perennial ice cover, thus providing an important refuge for ice‐dependent species. However, remarkably little is known about the climate or characteristics of the sea ice in this remote and inhospitable region. Here, we use the Pan‐Arctic Ice Ocean Modeling and Assimilation System model to show that the ice cover in the region is very dynamic, with changes occurring at a rate twice that of the Arctic Ocean as a whole. However, there are some differences in the changing nature of the ice cover between the eastern and western regions of the Last Ice Area, which include different timing of the annual minimum in ice thickness as well as distinct ice motion patterns associated with ice thickness extrema.

As sources of reactive halogens, snowpacks in sea ice regions control the oxidative capacity of the Arctic atmosphere. However, measurements of snowpack halide concentrations remain sparse, particularly in the high Arctic, limiting our understanding of and ability to parameterize snowpack participation in tropospheric halogen chemistry. To address this gap, we measured concentrations of chloride, bromide, and sodium in snow samples collected during polar spring above remote multi-year sea ice (MYI) and first-year­ sea ­ice ­(FYI) ­north ­of ­Greenland­ and ­Alaska, ­as­ well­ as ­in ­the ­central ­Arctic, ­and ­compared these measurements to a larger dataset collected in the Alaskan coastal Arctic by Krnavek et al. (2012). Regardless of sea ice region, these surface snow samples generally featured lower salinities, compared to­ coastal ­snow. ­­Surface­ snow­ in ­FYI­ regions ­was ­typically­ enriched ­in bromide ­and­ chloride ­compared ­to seawater, indicating snowpack deposition of bromine and chlorine-containing trace gases and an ability of the snowpack to participate further in bromine and chlorine activation processes. In contrast, surface snow in MYI regions was more often depleted in bromide, indicating it served as a source of bromine-containing trace gases to the atmosphere prior to sampling. Measurements at various snow depths indicate that the deposition of sea salt aerosols and halogen-containing trace gases to the snowpack surface played a larger role in determining surface snow halide concentrations compared to upward brine migration from sea ice. Calculated enrichment factors for bromide and chloride, relative to sodium, in the MYI snow­ samples ­suggests ­that ­MYI­ regions, ­in addition ­to ­FYI­ regions, ­have ­the ­potential ­to ­play ­an ­active role in Arctic boundary layer bromine and chlorine chemistry. The ability of MYI regions to participate in springtime atmospheric halogen chemistry should be considered in regional modeling of halogen activation and interpretation of satellite-based tropospheric bromine monoxide column measurements.

The seasonal evolution of Arctic sea ice can be described by the timing of key dates of sea ice concentration (SIC) change during its annual retreat and advance cycle. Here, we use SICs from a satellite passive microwave climate data record to identify the sea ice dates of opening (DOO), retreat (DOR), advance (DOA), and closing (DOC) and the periods of time between these events. Regional variability in these key dates, periods, and sea ice melt onset and freeze-up dates for 12 Arctic regions during the melt seasons of 1979–2016 is investigated. We find statistically significant positive trends in the length of the melt season (outer ice-free period) for most of the eastern Arctic, the Bering Sea, and Hudson and Baffin Bays with trends as large as 11.9 d decade^-1 observed in the Kara Sea. Trends in the DOR and DOA contribute to statistically significant increases in the length of the open water period for all regions within the Arctic Ocean ranging from 3.9 to 13.8 d decade^-1. The length of the ice retreat period (DOR−DOO) ranges from 17.1 d in the Sea of Okhotsk to 41 d in the Greenland Sea. The length of the ice advance period (DOC–DOA) is generally much shorter and ranges from 17.9 to 25.3 d in the Sea of Okhotsk and Greenland Sea, respectively. Additionally, we derive the extent of the seasonal ice zone (SIZ) and find statistically significant negative trends (SIZ is shrinking) in the Sea of Okhotsk, Baffin Bay, Greenland Sea, and Barents Sea regions, which are geographically open to the oceans and influenced by reduced winter sea ice extent. Within regions of the Arctic Ocean, statistically significant positive trends indicate that the extent of the SIZ is expanding as Arctic summer sea ice declines.

Pacific Winter Water (PWW) enters the western Arctic Ocean from the Chukchi Sea; however, the physical mechanisms that regulate its circulation within the deep basin are still not clear. Here, we investigate the interannual variability of PWW with a comprehensive data set over a decade. We quantify the thickening and expansion of the PWW layer during 2002–2016, as well as its changing pathway. The total volume of PWW in the Beaufort Gyre (BG) region is estimated to have increased from 3.48 ± 0.04 x 10¹⁴ m³ during 2002–2006 to 4.11 ± 0.02 x 10¹⁴ m³ during 2011–2016, an increase of 18%. We find that the deepening rate of the lower bound of PWW is almost double that of its upper bound in the northern Canada Basin, a result of lateral flux convergence of PWW (via lateral advection of PWW from the Chukchi Borderland) in addition to the Ekman pumping. In particular, of the 70‐m deepening of PWW at its lower bound observed over 2003–2011 in the northwestern basin, 43% resulted from lateral flux convergence. We also find a redistribution of PWW in recent years toward the Chukchi Borderland associated with the wind‐driven spin‐up and westward shift of the BG. Finally, we hypothesize that a recently observed increase of lower halocline eddies in the BG might be explained by this redistribution, through a compression mechanism over the Chukchi Borderland.

During late February and early March 2018, an unusual polynya was observed off the north coast of Greenland. This period was also notable for the occurrence of a sudden stratospheric warming. Here we use satellite and in situ data, a reanalysis and an ice‐ocean model to document the evolution of the polynya and its synoptic forcing. We show that its magnitude was unprecedented and that it was associated with the transient response to the sudden stratospheric warming leading to anomalous warm southerly flow in north Greenland. Indeed, regional wind speeds and temperatures were the highest during February going back to the 1960s. There is evidence that the thinning sea ice has increased its wind‐driven mobility. However, we show that the polynya would have developed under thicker ice conditions representative of the late 1970s and that even with the predicted trend toward thinner sea ice, it will only open during enhanced southerly flow.

In seasonal ice zones (SIZs), such as the one of the Greenland Sea, the sea ice growth in winter and subsequent melting in summer influence the phytoplankton activity. However, studies assessing phytoplankton activities over complete annual cycles and at a fine temporal resolution are lacking in this environment. Biogeochemical‐Argo floats, which are able to sample under the ice, were used to collect physical and biogeochemical data along vertical profiles and at 5‐day resolution during two complete annual cycles in the Greenland Sea SIZ. Three phytoplankton activity phases were distinct within an annual cycle: one under ice, a second at the ice edge, and a third one around an open‐water subsurface chlorophyll maximum. As expected, the light and nitrate availabilities controlled the phytoplankton activity and the establishment of these phases. On average, most of the annual net community production occurred equally under ice and at the ice edge. The open‐water subsurface chlorophyll maximum phase contribution, on the other hand, was much smaller. Phytoplankton biomass accumulation and production thus occur over a longer period than might be assumed if under ice blooms were neglected. This also means that satellite‐based estimates of phytoplankton biomass and production in this SIZ are likely underestimated. Simulations with the Arctic‐based physical‐biologically coupled SINMOD model suggest that most of the annual net community production in this SIZ results from local processes rather than due to advection of nitrate from the East Greenland and Jan Mayen Currents.

A melt pond (MP) distribution equation has been developed and incorporated into the Marginal Ice‐Zone Modeling and Assimilation System to simulate Arctic MPs and sea ice over 1979–2016. The equation differs from previous MP models and yet benefits from previous studies for MP parameterizations as well as a range of observations for model calibration. Model results show higher magnitude of MP volume per unit ice area and area fraction in most of the Canada Basin and the East Siberian Sea and lower magnitude in the central Arctic. This is consistent with Moderate Resolution Imaging Spectroradiometer observations, evaluated with Measurements of Earth Data for Environmental Analysis (MEDEA) data, and closely related to top ice melt per unit ice area. The model simulates a decrease in the total Arctic sea ice volume and area, owing to a strong increase in bottom and lateral ice melt. The sea ice decline leads to a strong decrease in the total MP volume and area. However, the Arctic‐averaged MP volume per unit ice area and area fraction show weak, statistically insignificant downward trends, which is linked to the fact that MP water drainage per unit ice area is increasing. It is also linked to the fact that MP volume and area decrease relatively faster than ice area. This suggests that overall the actual MP conditions on ice have changed little in the past decades as the ice cover is retreating in response to Arctic warming, thus consistent with the Moderate Resolution Imaging Spectroradiometer observations that show no clear trend in MP area fraction over 2000–2011.

Information on the timing of Arctic snow and ice melt onset, sea ice opening, retreat, advance, and closing, can be beneficial to a variety of stakeholders. Sea ice modelers can use information on the evolution of the ice cover through the rest of the summer to improve their seasonal sea ice forecasts. The length of the open water season (as derived from retreat/advance dates) is important for human activities and for wildlife. Long-term averages and variability of these dates as climate indicators are beneficial to business strategic planning and climate monitoring. In this study, basic characteristics of temporal means and variability of Arctic sea ice climate indicators derived from a satellite-based climate data record from March 1979 to February 2017 melt and freeze seasons are described. Our results show that, over the Arctic region, anomalies of snow and ice melt onset, ice opening and retreat dates are getting earlier in the year at a rate of more than 5 days per decade, while that of ice advance and closing dates are getting later at a rate of more than 5 days per decade. These significant trends resulted in significant upward trends for anomalies of inner and outer ice-free periods at a rate of nearly 12 days per decade. Small but significant downward trends of seasonal ice loss and gain period anomalies were also observed at a rate of –1.48 and –0.53 days per decade, respectively. Our analyses also demonstrated that the means of these indicators and their trends are sensitive to valid data masks and regional averaging methods.

Observations of the seasonal light field in the upper Arctic Ocean are critical to understanding the impacts of changing Arctic ice conditions on phytoplankton growth in the water column. Here we discuss data from a new sensor system, deployed in seasonal ice cover north‐east of Utqiagvik, Alaska in March 2014. The system was designed to provide observations of light and phytoplankton biomass in the water column during the formation of surface melt ponds and the transition from ice to open water. Hourly observations of downwelling irradiance beneath the ice (at 2.9, 6.9, and 17.9 m depths) and phytoplankton biomass (at 2.9 m depth) were transmitted via Iridium satellite from 9 March to 10 November 2014. Evidence of an under‐ice phytoplankton bloom (Chl a ∼8 mg m^-3) was seen in June and July. Increases in light intensity observed by the buoy likely resulted from the loss of snow cover and development of surface melt ponds. A bio‐optical model of phytoplankton production supported this probable trigger for the rapid onset of under‐ice phytoplankton growth. Once under‐ice light was no longer a limiting factor for photosynthesis, open water exposure almost marginally increased daily phytoplankton production compared to populations that remained under the adjacent ice. As strong effects of climate change continue to be documented in the Arctic, the insight derived from autonomous buoys will play an increasing role in understanding the dynamics of primary productivity where ice and cloud cover limit the utility of ocean color satellite observations.

The winter Arctic atmosphere is under the influence of two very different circulation systems: extratropical cyclones travel along the primary North Atlantic storm track from Iceland toward the eastern Arctic, while the western Arctic is characterized by a quasi‐stationary region of high pressure known as the Beaufort High. The winter (January through March) of 2017 featured an anomalous reversal of the normally anticyclonic surface winds and sea ice motion in the western Arctic. This reversal can be traced to a collapse of the Beaufort High as the result of the intrusion of low‐pressure systems from the North Atlantic, along the East Siberian Coast, into the Arctic Basin. Thin sea ice as the result of an extremely warm autumn (October through December) of 2016 contributed to the formation of an anomalous thermal low over the Barents Sea that, along with a northward shift of the tropospheric polar vortex, permitted this intrusion. The collapse of the Beaufort High during the winter of 2017 was associated with simultaneous 2‐sigma sea level pressure, surface wind, and sea ice circulation anomalies in the western Arctic. As the Arctic sea ice continues to thin, such reversals may become more common and impact ocean circulation, sea ice, and biology.

Seven different methods, with and without including geostrophic currents, were used to explore Ekman dynamics in the western Arctic Ocean for the period 1992–2014. Results show that surface geostrophic currents have been increasing and are much stronger than Ekman layer velocities in recent years (2003–2014) when the oceanic Beaufort Gyre (BG) is spinning up in the region. The new methods that include geostrophic currents result in more realistic Ekman pumping velocities than a previous iterative method that does not consider geostrophic currents and therefore overestimates Ekman pumping velocities by up to 52% in the central area of the BG over the period 2003–2014. When the BG is spinning up as seen in recent years, geostrophic currents become stronger, which tend to modify the ice‐ocean stress and moderate the wind‐driven Ekman convergence in the Canada Basin. This is a mechanism we have identified to play an important and growing role in stabilizing the Ekman convergence and therefore the BG in recent years. This mechanism may be used to explain three scenarios that describe the interplay of changes in wind forcing, sea ice motion, and geostrophic currents that control the variability of the Ekman dynamics in the central BG during 1992–2014. Results also reveal several upwelling regions in the southern and northern Canada Basin and the Chukchi Abyssal Plain which may play a significant role in physical and biological processes in these regions.

A budget of meteoric water (MW = river runoff, net precipitation minus evaporation, and glacial meltwater) over four regions of the Arctic Ocean is constructed using a simple box model, regional precipitation-evaporation estimates from reanalysis data sets, and estimates of import and export fluxes derived from the literature with a focus on the 2003–2008 period. The budget indicates an approximate/slightly positive balance between MW imports and exports (i.e., no change in storage); thus, the observed total freshwater increase observed during this time period likely resulted primarily from changes in non-MW freshwater components (i.e., increases in sea ice melt or Pacific water and/or a decrease in ice export). Further, our analysis indicates that the MW increase observed in the Canada Basin resulted from a spatial redistribution of MW over the Arctic Ocean. Mean residence times for MW were estimated for the Western Arctic (5–7 years), Eastern Arctic (3–4 years), and Lincoln Sea (1–2 years). The MW content over the Siberian shelves was estimated (~14,000 km³) based on a residence time of 3.5 years. The MW content over the entire Arctic Ocean was estimated to be ≥ 44,000 km³. The MW export through Fram Strait consisted mostly of water from the Eastern Arctic (3237 ±â€‰1370 km³ yr^-1) whereas the export through the Canadian Archipelago was nearly equally derived from both the Western Arctic (1182 ±â€‰534 km³ yr^-1) and Lincoln Sea (972 ±â€‰391 km³ yr^-1).

Potential climate drivers of Arctic tundra vegetation productivity are investigated to understand recent greening and browning trends documented by maximum normalized difference vegetation index (NDVI) (MaxNDVI) and time-integrated NDVI (TI-NDVI) for 1982–2015. Over this period, summer sea ice has continued to decline while oceanic heat content has increased. The increases in summer warmth index (SWI) and NDVI have not been uniform over the satellite record. SWI increased from 1982 to the mid-1990s and remained relatively flat from 1998 onwards until a recent upturn. While MaxNDVI displays positive trends from 1982–2015, TI-NDVI increased from 1982 until 2001 and has declined since. The data for the first and second halves of the record were analyzed and compared spatially for changing trends with a focus on the growing season. Negative trends for MaxNDVI and TI-NDVI were more common during 1999–2015 compared to 1982–1998.

Trend analysis within the growing season reveals that sea ice decline was larger in spring for the 1982–1998 period compared to 1999–2015, while fall sea ice decline was larger in the later period. Land surface temperature trends for the 1982–1998 growing season are positive and for 1999–2015 are positive in May–June but weakly negative in July–August. Spring biweekly NDVI trends are positive and significant for 1982–1998, consistent with increasing open water and increased available warmth in spring. MaxNDVI trends for 1999–2015 display significant negative trends in May and the first half of June.

Numerous possible drivers of early growing season NDVI decline coincident with warming temperatures are discussed, including increased standing water, delayed spring snow-melt, winter thaw events, and early snow melt followed by freezing temperatures. Further research is needed to robustly identify drivers of the spring NDVI decline.

Data derived from satellite-based observations, with buoy-based observations and assimilations, are used to calculate ocean Ekman layer transport and evaluate long-term trends in the Arctic Ocean over the period 1979–2014. The 36 year mean of upwelling (downwelling) is 3.7 ±â€‰2.0 (–4.0 ±â€‰2.2) Sv for the entire Arctic Basin, with ~0.3 Sv net downwelling contributed mostly by the Canadian region. With regard to long-term trends, the annual mean upwelling (downwelling) over the entire Arctic Basin is increasing at a linear rate of 0.92 (–0.98) Sv/decade. The Canada/Alaska coasts and Beaufort and Laptev Seas are regions of greatest Ekman transport intensification. The central Arctic Ocean and Lincoln Sea also have an increasing trend in transport. The Canadian and Eurasian regions each account for about half the total vertical Ekman variations in the Arctic Basin.

Highlights

• Blended SST (L4) analyses exhibit very large differences in the Beaufort Sea.
• L4 analyses are evaluated using independent UpTempO buoy observations in 3 regimes.
• High-latitude performance is tested using Taylor diagrams and skill scores.
• Ice masking is assessed and has minimal impact.
• Analysis performance varies with region, but 3 products provide best results.

In this work, we explore the seasonal relationships (i.e., the phenology) between sea ice retreat, sea surface temperature (SST), and atmospheric heat fluxes in the Pacific Sector of the Arctic Ocean, using satellite and reanalysis data. We find that where ice retreats early in most years, maximum summertime SSTs are usually warmer, relative to areas with later retreat. For any particular year, we find that anomalously early ice retreat generally leads to anomalously warm SSTs. However, this relationship is weak in the Chukchi Sea, where ocean advection plays a large role. It is also weak where retreat in a particular year happens earlier than usual, but still relatively late in the season, primarily because atmospheric heat fluxes are weak at that time. This result helps to explain the very different ocean warming responses found in two recent years with extreme ice retreat, 2007 and 2012. We also find that the timing of ice retreat impacts the date of maximum SST, owing to a change in the ocean surface buoyancy and momentum forcing that occurs in early August that we term the Late Summer Transition (LST). After the LST, enhanced mixing of the upper ocean leads to cooling of the ocean surface even while atmospheric heat fluxes are still weakly downward. Our results indicate that in the near-term, earlier ice retreat is likely to cause enhanced ocean surface warming in much of the Arctic Ocean, although not where ice retreat still occurs late in the season.

To better simulate the seasonal evolution of sea ice in the Arctic, with particular attention to the marginal ice zone, a sea ice model of the distribution of ice thickness, floe size, and enthalpy was implemented into the Pan-arctic IceOcean Modeling and Assimilation System (PIOMAS). Theories on floe size distribution (FSD) and ice thickness distribution (ITD) were coupled in order to explicitly simulate multicategory FSD and ITD distributions simultaneously. The expanded PIOMAS was then used to estimate the seasonal evolution of the Arctic FSD in 2014 when FSD observations are available for model calibration and validation.

Results indicate that the simulated FSD, commonly described equivalently as cumulative floe number distribution (CFND), generally follows a power law across space and time and agrees with the CFND observations derived from TerraSAR-X satellite images. The simulated power-law exponents also correlate with those derived using MODIS images, with a low mean bias of 2%. In the marginal ice zone, the modeled CFND shows a large number of small floes in winter because of stronger winds acting on thin, weak first-year ice in the ice edge region. In mid-spring and summer, the CFND resembles an upper truncated power law, with the largest floes mostly broken into smaller ones; however, the number of small floes is lower than in winter because floes of small sizes or first-year ice are easily melted away. In the ice pack interior there are fewer floes in late fall and winter than in summer because many of the floes are welded together into larger floes in freezing conditions, leading to a relatively flat CFND with low power-law exponents.

The simulated mean floe size averaged over all ice-covered areas shows a clear annual cycle, large in winter and smaller in summer. However, there is no obvious annual cycle of mean floe size averaged over the marginal ice zone. The incorporation of FSD into PIOMAS results in reduced ice thickness, mainly in the marginal ice zone, which improves the simulation of ice extent and yields an earlier ice retreat.

This study examines the processes governing the seasonal response of the Arctic Ocean and sea ice to surface forcings as they appear in historical simulations of 14 Coupled Model Intercomparison Project Phase 5 coupled climate models. In both models and observations, the seasonal heat budget is dominated by a local balance between net surface heating and storage in the heat content of the ocean and in melting/freezing of sea ice. Observations suggest ocean heat storage is more important than sea ice melt, while in most of these models, sea ice melt dominates. Seasonal horizontal heat flux divergence driven by the seasonal cycle of volume transport is only important locally. In models and observations, the dominant terms in the basin-average seasonal freshwater budget are the storages of freshwater between the ocean and sea ice, and the exchange between the two. The largest external source term is continental discharge in early summer, which is an order of magnitude smaller. The appearance of sea ice (extent and volume) and also ocean stratification in both the heat and freshwater budgets provides two links between the budgets and provides two mechanisms for feedback. One consequence of such an interaction is the fact that models with strong/weak seasonal surface heating also have strong/weak seasonal haline and temperature stratification.

Each year, the arctic sea ice edge retreats from its winter maximum extent through the Seasonal Ice Zone (SIZ) to its summer minimum extent. On some days, this retreat happens at a rapid pace, while on other days, parts of the pan-arctic ice edge hardly move for periods of days up to 1.5 weeks. We term this stationary behavior "ice edge loitering," and identify areas that are more prone to loitering than others. Generally, about 20–25% of the SIZ area experiences loitering, most often only one time at any one location during the retreat season, but sometimes two or more times. The main mechanism controlling loitering is an interaction between surface winds and warm sea surface temperatures in areas from which the ice has already retreated. When retreat happens early enough to allow atmospheric warming of this open water, winds that force ice floes into this water cause melting. Thus, while individual ice floes are moving, the ice edge as a whole appears to loiter. The time scale of loitering is then naturally tied to the synoptic time scale of wind forcing. Perhaps surprisingly, the area of loitering in the arctic seas has not changed over the past 25 years, even as the SIZ area has grown. This is because rapid ice retreat happens most commonly late in the summer, when atmospheric warming of open water is weak. We speculate that loitering may have profound effects on both physical and biological conditions at the ice edge during the retreat season.

Samples of snow on sea ice were collected in springtime of the 6 years 2008–2013 in the region between Greenland, Ellesmere Island, and the North Pole (82°N – 89°N, 0°W – 100°W). The meltwater was passed through filters, whose spectral absorption was then measured to determine the separate contributions by black carbon (BC) and other light-absorbing impurities. The median mixing ratio of BC across all years' samples was 4 ± 3 ng g^-1, and the median fraction of absorption due to non-BC absorbers was 36 ± 11%. Variances represent both spatial and interannual variability; there was no interannual trend in either variable. The absorption Angstrom exponent, however, decreased with latitude, suggesting a transition from dominance by biomass-burning sources in the south to an increased influence by fossil-fuel-burning sources in the north, consistent with earlier measurements of snow in Svalbard and at the North Pole.

To better describe the state of sea ice in the marginal ice zone (MIZ) with floes of varying thicknesses and sizes, both an ice thickness distribution (ITD) and a floe size distribution (FSD) are needed. In this work, we have developed a FSD theory that is coupled to the ITD theory of Thorndike et al. (1975) in order to explicitly simulate the evolution of FSD and ITD jointly. The FSD theory includes a FSD function and a FSD conservation equation in parallel with the ITD equation. The FSD equation takes into account changes in FSD due to ice advection, thermodynamic growth, and lateral melting. It also includes changes in FSD because of mechanical redistribution of floe size due to ice ridging and, particularly, ice fragmentation induced by stochastic ocean surface waves. The floe size redistribution due to ice fragmentation is based on the assumption that wave-induced breakup is a random process such that when an ice floe is broken, floes of any smaller sizes have an equal opportunity to form, without being either favored or excluded. To focus only on the properties of mechanical floe size redistribution, the FSD theory is implemented in a simplified ITD and FSD sea ice model for idealized numerical experiments. Model results show that the simulated cumulative floe number distribution (CFND) follows a power law as observed by satellites and airborne surveys. The simulated values of the exponent of the power law, with varying levels of ice breakups, are also in the range of the observations. It is found that floe size redistribution and the resulting FSD and mean floe size do not depend on how floe size categories are partitioned over a given floe size range. The ability to explicitly simulate multicategory FSD and ITD together may help to incorporate additional model physics, such as FSD-dependent ice mechanics, surface exchange of heat, mass, and momentum, and wave-ice interactions.

The seasonal evolution of sea ice loss in the Beaufort Sea during 1979–2012 is examined, focusing on differences between eastern and western sectors. Two stages in ice loss are identified: the Day of Opening (DOO) is defined as the spring decrease in ice concentration from its winter maximum below a value of 0.8 areal concentration; the Day of Retreat (DOR) is the summer decrease below 0.15 concentration. We consider three aspects of the subject, i.e., (i) the long-term mean, (ii) long-term linear trends, and (iii) interannual variability. We find that in the mean, DOO occurs earliest in the eastern Beaufort Sea (EBS) owing to easterly winds which act to thin the ice there, relative to the western Beaufort Sea (WBS) where ice has been generally thicker. There is no significant long-term trend in EBS DOO, although WBS DOO is in fact trending toward earlier dates. This means that spatial differences in DOO across the Beaufort Sea have been shrinking over the past 33 years, i.e., these dates are becoming more synchronous, a situation which may impact human and marine mammal activity in the area. Retreat dates are also becoming more synchronous, although with no statistical significance over the studied time period. Finally, we find that in any given year, an increase in monthly mean easterly winds of ~1 m/s during spring is associated with earlier summer DOR of 6–15 days, offering predictive capability with 2–4 months lead time.

A numerical ocean sea-ice model is used to demonstrate that Arctic sea ice retreat affects momentum transfer into the ocean. A thinner and thus weaker ice cover is more easily forced by the wind, which increases the momentum flux. In contrast, increasing open water reduces momentum transfer because the ice surface provides greater drag than the open water surface. We introduce the concept of optimal ice concentration: momentum transfer increases with increasing ice concentration up to a point, beyond which frictional losses by floe interaction damp the transfer. For a common ice internal stress formulation, a concentration of 80–90% yields optimal amplification of momentum flux into the ocean. We study the seasonality and long-term evolution of Arctic Ocean surface stress over the years 1979–2012. Spring and fall feature optimal ice conditions for momentum transfer, but only in fall is the wind forcing at its maximum, yielding a peak basin-mean ocean surface stress of ~0.08 N/m². Since 1979, the basin-wide annual mean ocean surface stress has been increasing by 0.004 N/m²/decade, and since 2000 by 0.006 N/m²/decade. In contrast, summertime ocean surface stress has been decreasing at –0.002 N/m²/decade. These trends are linked to the weakening of the ice cover in fall, winter and spring, and to an increase in open water fraction in summer, i.e., changes in momentum transfer rather than changes in wind forcing. In most areas, the number of days per year with optimal ice concentration is decreasing.

The Lincoln Sea is a bifurcation point, where waters from the Canadian and Eurasian Basins flow to Nares or Fram Strait. Mechanisms that control which waters are found in the Lincoln Sea, and on its continental shelves, are unknown. Using conductivity-temperature-depth (CTD; from hydrographic and ice-tethered profiler surveys), nutrient, and mooring data with the DRAKKAR global 3-D coupled ocean/sea-ice model, the Lincoln Sea was examined from 1991 to 2012. Although both Pacific and Atlantic waters were observed on the North Ellesmere and North Greenland shelves, Atlantic water was shallower on the North Greenland shelf. Thus, deeper than 125 m, water was warmer and saltier on the North Greenland shelf than the North Ellesmere shelf. Three different water types were identified on the North Ellesmere shelf — waters from the Canadian Basin were observed 1992, 1993, 1996, 2005, and 2012, waters from both the Canadian and Eurasian Basins were observed in 2003, 2004, and 2008, and waters with no temperature minima or maxima below the surface mixed layer were observed in 1991, 2006, 2009, and 2010. Mixing with vertical advection speeds of 1x10^-4 m s^-1 were observed on the continental slope and this mixing could cause the disappearance of the temperature maxima. Model results suggest that currents on the North Ellesmere shelf were weak (less than 10 cm s^-1), baroclinic, and directed away from Nares Strait while currents on the North Greenland shelf were stronger (less than 15 cm s^-1), and primarily directed towards Nares Strait. CTD, mooring, and model results suggest that the water advected to Nares Strait is primarily from the North Greenland shelf while water on the North Ellesmere shelf is advected westward.

Observational studies have shown that an unprecedented warm anomaly has recently affected the temperature of the Atlantic Water (AW) layer lying at intermediate depth in the Arctic Ocean. Using observations from four profiling moorings, deployed in the interior of the Canada Basin between 2003 and 2011, the upward diffusive vertical heat flux from this layer is quantified. Vertical diffusivity is first estimated from a fine-scale parameterization method based on CTD and velocity profiles. Resulting diffusive vertical heat fluxes from the AW are in the range 0.1–0.2 W m^-2 on average. Although large over the period considered, the variations of the AW temperature maximum yields small variations for the temperature gradient and thus the vertical diffusive heat flux. In most areas, variations in upward diffusive vertical heat flux from the AW have only a limited effect on temperature variations of the overlying layer. However, the presence of eddies might be an effective mechanism to enhance vertical heat transfer, although the small number of eddies sampled by the moorings suggest that this mechanism remains limited and intermittent in space and time. Finally, our results suggest that computing diffusive vertical heat flux with a constant vertical diffusivity of ~2 x 10^-6 m² s^-1 provides a reasonable estimate of the upward diffusive heat transfer from the AW layer, although this approximation breaks down in the presence of eddies.

A coupled biophysical model is used to examine the impact of the great Arctic cyclone of early August 2012 on the marine planktonic ecosystem in the Pacific sector of the Arctic Ocean (PSA). Model results indicate that the cyclone influences the marine planktonic ecosystem by enhancing productivity on the shelves of the Chukchi, East Siberian, and Laptev seas during the storm. Although the cyclone's passage in the PSA lasted only a few days, the simulated biological effects on the shelves last 1 month or longer. At some locations on the shelves, primary productivity (PP) increases by up to 90% and phytoplankton biomass by up to 40% in the wake of the cyclone. The increase in zooplankton biomass is up to 18% on 31 August and remains 10% on 15 September, more than 1 month after the storm. In the central PSA, however, model simulations indicate a decrease in PP and plankton biomass. The biological gain on the shelves and loss in the central PSA are linked to two factors. (1) The cyclone enhances mixing in the upper ocean, which increases nutrient availability in the surface waters of the shelves; enhanced mixing in the central PSA does not increase productivity because nutrients there are mostly depleted through summer draw down by the time of the cyclone's passage. (2) The cyclone also induces divergence, resulting from the cyclone's low-pressure system that drives cyclonic sea ice and upper ocean circulation, which transports more plankton biomass onto the shelves from the central PSA. The simulated biological gain on the shelves is greater than the loss in the central PSA, and therefore, the production on average over the entire PSA is increased by the cyclone. Because the gain on the shelves is offset by the loss in the central PSA, the average increase over the entire PSA is moderate and lasts only about 10 days. The generally positive impact of cyclones on the marine ecosystem in the Arctic, particularly on the shelves, is likely to grow with increasing summer cyclone activity if the Arctic continues to warm and the ice cover continues to shrink.

Hydrographic data from the Arctic Ocean show that freshwater content in the Lincoln Sea, north of Greenland, increased significantly from 2007 to 2010, slightly lagging changes in the eastern and central Arctic. The anomaly was primarily caused by a decrease in the upper ocean salinity. In 2011 upper ocean salinities in the Lincoln Sea returned to values similar to those prior to 2007. Throughout 2008—2010, the freshest surface waters in the western Lincoln Sea show water mass properties similar to fresh Canada Basin waters north of the Canadian Arctic Archipelago. In the northeastern Lincoln Sea fresh surface waters showed a strong link with those observed in the Makarov Basin near the North Pole. The freshening in the Lincoln Sea was associated with a return of a subsurface Pacific Water temperature signal although this was not as strong as observed in the early 1990s. Comparison of repeat stations from the 2000s with the data from the 1990s at 65°W showed an increase of the Atlantic temperature maximum which was associated with the arrival of warmer Atlantic water from the Eurasian Basin. Satellite-derived dynamic ocean topography of winter 2009 showed a ridge extending parallel to the Canadian Archipelago shelf as far as the Lincoln Sea, causing a strong flow toward Nares Strait and likely Fram Strait. The total volume of anomalous freshwater observed in the Lincoln Sea and exported by 2011 was close to 110 ± 250 km, approximately 13% of the total estimated FW increase in the Arctic in 2008.

A high-resolution global ocean/sea ice model is used to investigate the modes of Arctic Ocean heat content variability for the period 1968–2007. A rotated empirical orthogonal function analysis is performed on the monthly mean vertically integrated heat content to investigate the mechanisms governing its spatiotemporal variations. In the model, 28% of the heat content variability is driven by the seasonal and interannual fluctuations of the atmospheric heat flux in the seasonally ice free regions. The heat flux variability associated with Atlantic Water advected through Fram Strait drives 31% of the heat content variability. Changes of temperature and circulation drive Fram Strait heat transport variability, and these two effects project on different modes and thus drive heat content variations in different parts of the Eurasian Basin. A second branch of Atlantic Water is modified in the Barents Sea and the variations of the heat flux associated with the Barents Sea water branch penetrating the deep Arctic yield heat content variations in the Eurasian Basin. The effect of the Bering Strait heat flux variations remains limited to the Chukchi Sea. Autonomous observing system may be able to capture the Arctic heat content variability. Sea surface temperature satellite observations combined with temperature profiles of the top 800 m in the deep Arctic covered by sea ice are sufficient to capture most of the variability signal. The results emphasize the crucial need for measurements in the Eurasian Basin.

Recent warming of surface waters, accompanied by reduced ice thickness and extent may have significant consequences for climate-driven changes of primary production (PP) in the Arctic Ocean (AO). However, it has been difficult to obtain a robust benchmark estimate of pan-Arctic PP necessary for evaluating change. This paper provides an estimate of pan-Arctic PP prior to significant warming from a synthetic analysis of the ARCSS-PP database of in situ measurements collected from 1954 to 2007 and estimates derived from satellite-based observations from 1998 to 2007.

The spatial and seasonal magnitude and variability of primary production in the Arctic Ocean (AO) is quantified with a pan-arctic approach. We synthesize estimates of primary production (PP), focusing on surface waters (0–5 m), using complementary methods that emphasize different spatial and temporal scales. These methods include (1) in situ observations of ¹⁴C uptake mostly and possibly some O₂ production reported in units of carbon (in situ PP), (2) remotely sensed primary production (sat-PP), and (3) an empirical algorithm giving net PP as a function of in situ chlorophyll a (in situ Chl-PP). The work presented herein examines historical data for PP collected in surface waters only, as they form the majority of the values of a larger ensemble of PP data collected over >50 years (ARCSS-PP) by many national and international efforts. This extended set of surface and vertically-resolved data will provide pan-Arctic validation of remotely sensed chlorophyll a and PP, an extremely valuable tool in this environment which is so difficult to sample. To this day, PP data in the AO are scarce and have uneven temporal and spatial coverage which, when added to the AO's regional heterogeneity, its strong seasonal changes, and limited access, have made and continue to make obtaining a comprehensive picture of PP in the AO difficult.

Combining nitrate, nitrite and phosphate data from several sources with additional quality control produced a database that eliminates many questionable values. This database, in turn, facilitated estimation of net community production (NCP) in the Arctic Marine System (AMS). In some regions, the new database enabled quantitative calculation of NCP over the vegetative season from changes in nutrient concentrations. In others, useful inferences were possible based on nutrient concentration patterns. This analysis demonstrates that it is possible to estimate NCP from seasonal changes in nutrients in many parts of the Arctic, however, the data were so sparse that most of our estimates for 14 sub-regions of the AMS are attended by uncertainties >50%. Nevertheless, the wide regional variation of NCP within the AMS (~two orders of magnitude) may make the results useful.

This model study examines the impact of an intense early August cyclone on the 2012 record low Arctic sea ice extent. The cyclone passed when Arctic sea ice was thin and the simulated Arctic ice volume had already declined ~40% from the 2007–2011 mean. The thin sea ice pack and the presence of ocean heat in the near surface temperature maximum layer created conditions that made the ice particularly vulnerable to storms. During the storm, ice volume decreased about twice as fast as usual, owing largely to a quadrupling in bottom melt caused by increased upward ocean heat transport. This increased ocean heat flux was due to enhanced mixing in the oceanic boundary layer, driven by strong winds and rapid ice movement. A comparison with a sensitivity simulation driven by reduced wind speeds during the cyclone indicates that cyclone-enhanced bottom melt strongly reduces ice extent for about two weeks, with a declining effect afterwards. The simulated Arctic sea ice extent minimum in 2012 is reduced by the cyclone, but only by 0.15 x 10⁶ km² (4.4%). Thus without the storm, 2012 would still have produced a record minimum.

Highlights

The 2011 annual wind-driven circulation regime was anticyclonic, supporting continued high volumes of freshwater in the Beaufort Gyre region and consistent with a 2012 shift of the Beaufort Gyre freshwater center to the west.

Sea surface temperatures in summer continue to be anomalously warm at the ice-free margins, while upper ocean temperature and salinity show significant interannual variability with no clear trends.

Oceanic fluxes of volume and heat through the Bering Strait increased by ~50% between 2001 and 2011.

Sea level exhibits decadal variability with a reduced correlation to sea level atmospheric pressure since the late 1990s.

Recent mooring observations in the Arctic Basin suggest the existence of a seasonality of Atlantic Water (AW) temperature. Here the DRAKKAR global ocean/sea-ice model is used to examine the seasonal cycle amplitude of AW temperature within the Arctic Ocean and to investigate the possible mechanisms governing this seasonality. The simulation as well as available mooring data reveals that the amplitude of the AW temperature seasonal cycle is significant only in the Nansen Basin along the continental slope, where AW is primarily advected. In the model, the seasonal cycle of the AW temperature is advected from Fram Strait up to St. Anna Trough and then re-energized by the Barents Sea Branch. This suggests that the seasonal AW temperature signal survives over a finite distance (~1000 km). Interannual changes in the seasonal cycle amplitude can be as large as the mean seasonal cycle amplitude; thus seasonality is difficult to characterize from observations spanning only a short period. The seasonal bias of in-situ observations taken during spring and summer does not induce a large error when considering the interannual-to-decadal variations of AW temperature, because the seasonal cycle accounts for a small or negligible part of AW temperature variability, even near the inflow region.

Freshening in the Canada basin of the Arctic Ocean began in the 1990s and continued to at least the end of 2008. By then, the Arctic Ocean might have gained four times as much fresh water as comprised the Great Salinity Anomaly of the 1970s, raising the spectre of slowing global ocean circulation. Freshening has been attributed to increased sea ice melting and contributions from runoff, but a leading explanation has been a strengthening of the Beaufort High — a characteristic peak in sea level atmospheric pressure — which tends to accelerate an anticyclonic (clockwise) wind pattern causing convergence of fresh surface water. Limited observations have made this explanation difficult to verify, and observations of increasing freshwater content under a weakened Beaufort High suggest that other factors must be affecting freshwater content.

Here we use observations to show that during a time of record reductions in ice extent from 2005 to 2008, the dominant freshwater content changes were an increase in the Canada basin balanced by a decrease in the Eurasian basin. Observations are drawn from satellite data (sea surface height and ocean-bottom pressure) and in situ data. The freshwater changes were due to a cyclonic (anticlockwise) shift in the ocean pathway of Eurasian runoff forced by strengthening of the west-to-east Northern Hemisphere atmospheric circulation characterized by an increased Arctic Oscillation index. Our results confirm that runoff is an important influence on the Arctic Ocean and establish that the spatial and temporal manifestations of the runoff pathways are modulated by the Arctic Oscillation, rather than the strength of the wind-driven Beaufort Gyre circulation.

A numerical model is used to investigate the time and space extent of the near-surface temperature maximum (NSTM) of the Canadian Basin of the Arctic Ocean over the years 2000%u20132009. The NSTM is formed from local summertime absorption of solar radiation which, in some circumstances, descends through the fall and early winter to form a warm subsurface layer just below the winter mixed layer. We find that winter survival of this layer is confined largely to the Beaufort Gyre of the Canadian Basin, where Ekman convergence and downwelling push the summer warm layer down below the winter mixing depth. In recent years, summer stratification has increased, downwelling has accelerated, and the NSTM has warmed as the sea ice cover in the Beaufort Gyre has thinned. The result is a strengthening NSTM which contained enough heat by the end of winter 2007/2008 to melt about 20 cm of sea ice. Northwest of Alaska the model also simulates a second, deeper temperature maximum layer that forms from advection of saltier summer Pacific water. However, this layer is difficult to adequately resolve and maintain given the model's resolution.

Analysis of modern and historical observations demonstrates that the temperature of the intermediate-depth (150–900 m) Atlantic water (AW) of the Arctic Ocean has increased in recent decades. The AW warming has been uneven in time; a local 1C maximum was observed in the mid-1990s, followed by an intervening minimum and an additional warming that culminated in 2007 with temperatures higher than in the 1990s by 0.24C. Relative to climatology from all data prior to 1999, the most extreme 2007 temperature anomalies of up to 1C and higher were observed in the Eurasian and Makarov Basins. The AW warming was associated with a substantial (up to 75–90 m) shoaling of the upper AW boundary in the central Arctic Ocean and weakening of the Eurasian Basin upper-ocean stratification.

Taken together, these observations suggest that the changes in the Eurasian Basin facilitated greater upward transfer of AW heat to the ocean surface layer. Available limited observations and results from a 1D ocean column model support this surmised upward spread of AW heat through the Eurasian Basin halocline. Experiments with a 3D coupled ice–ocean model in turn suggest a loss of 28–35 cm of ice thickness after 50 yr in response to the 0.5 W m^-2 increase in AW ocean heat flux suggested by the 1D model. This amount of thinning is comparable to the 29 cm of ice thickness loss due to local atmospheric thermodynamic forcing estimated from observations of fast-ice thickness decline. The implication is that AW warming helped precondition the polar ice cap for the extreme ice loss observed in recent years.

In this study, we use a numerical sea-ice-ocean model to examine what causes summertime upper ocean warming and sea ice melt during the 21st century in the Arctic Ocean. Our first question is, "What causes the ocean to warm in the Pacific Sector during the summer"? We find that about 80% of total heating over this region comes from ocean surface heat flux, with the remaining 20% originating in ocean lateral heat flux convergence. The latter occurs mostly within a few hundred kilometers of the northwest Alaskan coast. In the summer of 2007, the ocean gained just over twice the amount of heat it did over the average of the previous 7 years. Our second question is, "What causes sea ice to melt in the Pacific Sector during summer"? Our analysis shows that top melt dominates total melt early in the summer, while bottom melt (and in particular, bottom melt due to ocean heat transport) dominates later in the summer as atmospheric heating declines. Bottom melt rates in summer 2007 were 34% higher relative to the previous 7 year average. The modeled partition of top versus bottom melt closely matches observed melt rates obtained by a drifting buoy. Bottom melting contributes about 2/3 of total volume melt but is geographically confined to the Marginal Ice Zone, while top melting contributes a lesser 1/3 of volume melt but occurs over a much broader area of the ice pack.

Hydrologic cycle intensification is an expected manifestation of a warming climate. Although positive trends in several global average quantities have been reported, no previous studies have documented broad intensification across elements of the Arctic freshwater cycle (FWC). In this study, the authors examine the character and quantitative significance of changes in annual precipitation, evapotranspiration, and river discharge across the terrestrial pan-Arctic over the past several decades from observations and a suite of coupled general circulation models (GCMs). Trends in freshwater flux and storage derived from observations across the Arctic Ocean and surrounding seas are also described.

Numerical experiments are conducted to project arctic sea ice responses to varying levels of future anthropogenic warming and climate variability over 2010–2050. A summer ice-free Arctic Ocean is likely by the mid-2040s if arctic surface air temperature (SAT) increases 4 deg C by 2050 and climate variability is similar to the past relatively warm two decades. If such a SAT increase is reduced by one-half or if a future Arctic experiences a range of SAT fluctuation similar to the past five decades, a summer ice-free Arctic Ocean would be unlikely before 2050. If SAT increases 4 deg C by 2050, summer ice volume decreases to very low levels (10–37% of the 1978–2009 summer mean) as early as 2025 and remains low in the following years, while summer ice extent continues to fluctuate annually. Summer ice volume may be more sensitive to warming while summer ice extent more sensitive to climate variability. The rate of annual mean ice volume decrease relaxes approaching 2050. This is because, while increasing SAT increases summer ice melt, a thinner ice cover increases winter ice growth. A thinner ice cover also results in a reduced ice export, which helps to further slow ice volume loss. Because of enhanced winter ice growth, arctic winter ice extent remains nearly stable and therefore appears to be a less sensitive climate indicator.

We report on wintertime data collected from Baffin Bay and northern Davis Strait, a major gateway linking the Arctic with the subpolar North Atlantic, using narwhals (Monodon monoceros) as an oceanographic sampling platform. Fourteen narwhals were instrumented with satellite-linked time-depth-temperature recorders between 2005 and 2007. Transmitters collected and transmitted water column temperature profiles from each dive between December and April, where >90% of maximum daily dive depths reached the bottom. Temperature measurements were combined with 15 helicopter-based conductivity-temperature-depth (CTD) casts taken in April 2007 across central Baffin Bay and compared with hydrographic climatology values used for the region in Arctic climate models. Winter temperature maxima for whale and CTD data were in good agreement, ranging between 4.0 deg C and 4.6 deg C in inshore and offshore Baffin Bay and in Davis Strait. The warm Irminger Water was identified between 57 deg W and 59 deg W (at 68 deg N) between 200 and 400 m depths. Whale data correlated well with climatological temperature maxima; however, they were on average 0.9 deg C warmer plus/minus 0.6 deg C (P < 0.001). Furthermore, climatology data overestimated the winter surface isothermal layer thickness by 50–80 m.

Our results suggest the previously documented warming in Baffin Bay has continued through 2007 and is associated with a warmer West Greenland Current in both of its constituent water masses. This research demonstrates the feasibility of using narwhals as ocean observation platforms in inaccessible Arctic areas where dense sea ice prevents regular oceanographic measurements and where innate site fidelity, affinity for winter pack ice, and multiple daily dives to >1700 m offer a useful opportunity to sample the area.

We have developed a coupled 3-D pan-Arctic biology/sea ice/ocean model to investigate the impact of declining Arctic sea ice on the marine planktonic ecosystem over 1988–2007. The biophysical model results agree with satellite observations of a generally downward trend in summer sea ice extent during 1988–2007, resulting in an increase in the simulated photosynthetically active radiation (PAR) at the ocean surface and marine primary productivity (PP) in the upper 100 m over open water areas of the Arctic Ocean. The simulated Arctic sea ice thickness has decreased steadily during 1988–2007, leading to an increase in PAR and PP in sea ice-covered areas. The simulated total PAR in all areas of the Arctic Ocean has increased by 43%, from 146 TW in 1988 to 209 TW in 2007; the corresponding total PP has increased by 50%, from 456 Tg C yr^-1 in 1988 to 682 Tg C yr^-1 in 2007. The simulated PAR and PP increases mainly occur in the seasonally and permanently ice-covered Arctic Ocean. In addition to increasing PAR, the decline in sea ice tends to increase the nutrient availability in the euphotic zone by enhancing air-sea momentum transfer, leading to strengthened upwelling and mixing in the water column and therefore increased nutrient input into the upper ocean layers from below. The increasing nutrient availability also contributes to the increase in the simulated PP, even though significant surface nutrient drawdown in summer is simulated. In conjunction with increasing surface absorption of solar radiation and rising surface air temperature, the increasing surface water temperature in the Arctic Ocean peripheral seas further contributes to the increase in PP. As PP has increased, so has the simulated biomass of phytoplankton and zooplankton.

This 20th annual State of the Climate report highlights the climate conditions that characterized 2009, including notable extreme events. In total, 37 Essential Climate Variables are reported to more completely characterize the State of the Climate in 2009.

The pace of change in the arctic system during recent decades has captured the world's attention. Observations and model simulations both indicate that the arctic experiences an amplified response to climate forcing relative to that at lower latitudes. At the core of these changes is the arctic hydrologic system, which includes ice, gaseous vapor in the atmosphere, liquid water in soils and fluvial networks on land, and the freshwater content of the ocean. The changes in stores and fluxes of freshwater have a direct impact on biological systems, not only of the arctic region itself, but also well beyond its bounds. In this investigation, we used a heuristic, graphical approach to distill the system into its fundamental parts, documented the key relationships between those parts as best we know them, and identified the feedback loops within the system. The analysis illustrates relationships that are well understood, but also reveals others that are either unfamiliar, uncertain, or unexplored. The graphical approach was used to provide a visual assessment of the arctic hydrologic system in one possible future state in which the Arctic Ocean is seasonally ice free.

The dramatic reduction in minimum Arctic sea ice extent in recent years has been accompanied by surprising changes in the thermohaline structure of the Arctic Ocean, with potentially important impact on convection in the North Atlantic and the meridional overturning circulation of the world ocean. Extensive aerial hydrographic surveys carried out in March–April, 2008, indicate major shifts in the amount and distribution of fresh-water content (FWC) when compared with winter climatological values, including substantial freshening on the Pacific side of the Lomonosov Ridge. Measurements in the Canada and Makarov Basins suggest that total FWC there has increased by as much as 8,500 cubic kilometers in the area surveyed, effecting significant changes in the sea-surface dynamic topography, with an increase of about 75% in steric level difference from the Canada to Eurasian Basins, and a major shift in both surface geostrophic currents and freshwater transport in the Beaufort Gyre.

Mackenzie River discharge was at a record low in water year (WY) 1995 (October 1994 to September 1995), was near average in WY 1996, and was at a record high in WY 1997. The record high discharge in WY 1997, with above average flow each month, was followed by a record high flow in May 1998, then a sharp decline. Through diagnosing these changing flows and their expression in the Beaufort Sea via synthesis of observations and model output, this study provides insight into the nature of the Arctic's freshwater system.

The low discharge in WY 1995 manifests negative anomalies in P–E and precipitation, recycled summer precipitation, and dry surface conditions immediately prior to the water year. The complex hydrograph for WY 1996 reflects a combination of spring soil moisture recharge, buffering by rising lake levels, positive P–E anomalies in summer, and a massive release of water held in storage by Bennett Dam. The record high discharge in WY 1997 manifests the dual effects of reduced buffering by lakes and positive P–E anomalies for most of the year. With reduced buffering, only modest P–E the following spring led to a record discharge in May 1998. As simulated with a coupled ice–ocean model, the record low discharge in WY 1995 contributed to a negative freshwater anomaly on the Mackenzie shelf lasting throughout the winter of 1995/96. High discharge from July–October 1996 contributed approximately 20% to a positive freshwater anomaly forming in the Beaufort Sea in the autumn of that year. The remainder was associated with reduced autumn/winter ice growth, strong ice melt the previous summer, and positive P–E anomalies over the ocean itself. Starting in autumn 1997 and throughout 1998, the upper ocean became more saline owing to sea ice growth.

The minimum of Arctic sea ice extent in the summer of 2007 was unprecedented in the historical record. A coupled ice–ocean model is used to determine the state of the ice and ocean over the past 29 yr to investigate the causes of this ice extent minimum within a historical perspective. It is found that even though the 2007 ice extent was strongly anomalous, the loss in total ice mass was not. Rather, the 2007 ice mass loss is largely consistent with a steady decrease in ice thickness that began in 1987. Since then, the simulated mean September ice thickness within the Arctic Ocean has declined from 3.7 to 2.6 m at a rate of –0.57 m decade^-1. Both the area coverage of thin ice at the beginning of the melt season and the total volume of ice lost in the summer have been steadily increasing. The combined impact of these two trends caused a large reduction in the September mean ice concentration in the Arctic Ocean. This created conditions during the summer of 2007 that allowed persistent winds to push the remaining ice from the Pacific side to the Atlantic side of the basin and more than usual into the Greenland Sea. This exposed large areas of open water, resulting in the record ice extent anomaly.

A model study has been conducted of the unprecedented retreat of arctic sea ice in the summer of 2007. It is found that preconditioning, anomalous winds, and ice-albedo feedback are mainly responsible for the retreat. Arctic sea ice in 2007 was preconditioned to radical changes after years of shrinking and thinning in a warm climate. During summer 2007 atmospheric changes strengthened the transpolar drift of sea ice, causing more ice to move out of the Pacific sector and the central Arctic Ocean where the reduction in ice thickness due to ice advection is up to 1.5 m more than usual. Some of the ice exited Fram Strait and some piled up in part of the Canada Basin and along the coast of northern Greenland, leaving behind an unusually large area of thin ice and open water. Thin ice and open water allow more surface solar heating because of a much reduced surface albedo, leading to amplified ice melting. The Arctic Ocean lost additional 10% of its total ice mass in which 70% is due directly to the amplified melting and 30% to the unusual ice advection, causing the unprecedented ice retreat. Arctic sea ice has entered a state of being particularly vulnerable to anomalous atmospheric forcing.

We conduct experiments with an ice-ocean model to answer the question whether and to what degree unusually clear skies during the summer of 2007 contributed to the record sea ice extent minimum in the Arctic Ocean during September of 2007. Anomalously high pressure over the Beaufort Sea during summer 2007 appears associated with a strong negative cloud anomaly. This anomaly is two standard deviations below the 1980–2007 average established from a combination of two different satellite-based records. Cloud anomalies from the MODIS sensor are compared with anomalies from the NCEP/NCAR reanalysis and are found in good agreement in spatial patterns and magnitude. However, these experiments establish that the negative cloud anomaly and increased downwelling shortwave flux from June through August did not contribute substantially to the record sea ice extent minimum. This finding eliminates one aspect of the unusual weather that may have contributed to the record minimum.

Ensemble predictions of arctic sea ice in spring and summer 2008 have been carried out using an ice-ocean model. The ensemble is constructed by using atmospheric forcing from 2001 to 2007 and the September 2007 ice and ocean conditions estimated by the model. The prediction results show that the record low ice cover and the unusually warm ocean surface waters in summer 2007 lead to a substantial reduction in ice thickness in 2008. Up to 1.2 m ice thickness reduction is predicted in a large area of the Canada Basin in both spring and summer of 2008, leading to extraordinarily thin ice in summer 2008. There is a 50% chance that both the Northern Sea Route and the Northwest Passage will be nearly ice free in September 2008. It is not likely there will be another precipitous decline in arctic sea ice extent such as seen in 2007, unless a new atmospheric forcing regime, significantly different from the recent past, occurs.

How well can the extent of arctic sea ice be predicted for lead periods of up to one year? The forecast ability of a linear empirical model is explored. It uses as predictors historical information about the ocean and ice obtained from an ice–ocean model retrospective analysis. The monthly model fields are represented by a correlation-weighted average based on the predicted ice extent. The forecast skill of the procedure is found by fitting the model over subsets of the available data and then making subsequent projections using independent predictor data. The forecast skill, relative to climatology, for predictions of the observed September ice extent for the pan-arctic region is 0.77 for six months lead (from March) and 0.75 for 11 months lead (from October). The ice concentration is the most important variable for the first two months and the ocean temperature of the model layer with a depth of 200 to 270 m is most important for longer lead times. The trend accounts for 76% of the variance of the pan-arctic ice extent, so most of the forecast skill is realized by determining model variables that best represent this trend. For detrended data there is no skill for lead times of 3 months or more. The forecast skill relative to the estimate from the previous year is lower than the climate-relative skill but it is still greater than 0.45 for most lead times. Six-month predictions are also made for each month of the year and regional three-month predictions are made for 45-degree sectors. The ice-ocean model output significantly improves the predictive skill of the forecast model.

Ocean temperature profiles and satellite data have been analyzed for summertime sea surface temperature (SST) and upper ocean heat content variations over the past century, with a focus on the Arctic Ocean peripheral seas. We find that many areas cooled up to –0.5°C per decade during 1930–1965 as the Arctic Oscillation (AO) index generally fell, while these areas warmed during 1965–1995 as the AO index generally rose. Warming is particularly pronounced since 1995, and especially since 2000. Summer 2007 SST anomalies are up to 5°C. The increase in upper ocean summertime warming since 1965 is sufficient to reduce the following winter's ice growth by as much as 0.75 m. Alternatively, this heat may return to the atmosphere before any ice forms, representing a fall freeze-up delay of two weeks to two months. This returned heat might be carried by winds over terrestrial tundra ecosystems, contributing to the local heat budget.

Recent observations show dramatic changes of the Arctic atmosphere–ice–ocean system. Here the authors demonstrate, through the analysis of a vast collection of previously unsynthesized observational data, that over the twentieth century the central Arctic Ocean became increasingly saltier with a rate of freshwater loss of 239 ± 270 km³ decade^-1. In contrast, long-term (1920–2003) freshwater content (FWC) trends over the Siberian shelf show a general freshening tendency with a rate of 29 ± 50 km³ decade^-1. These FWC trends are modulated by strong multidecadal variability with sustained and widespread patterns. Associated with this variability, the FWC record shows two periods in the 1920s–30s and in recent decades when the central Arctic Ocean was saltier, and two periods in the earlier century and in the 1940s–70s when it was fresher. The current analysis of potential causes for the recent central Arctic Ocean salinification suggests that the FWC anomalies generated on Arctic shelves (including anomalies resulting from river discharge inputs) and those caused by net atmospheric precipitation were too small to trigger long-term FWC variations in the central Arctic Ocean; to the contrary, they tend to moderate the observed long-term central-basin FWC changes. Variability of the intermediate Atlantic Water did not have apparent impact on changes of the upper-Arctic Ocean water masses. The authors' estimates suggest that ice production and sustained draining of freshwater from the Arctic Ocean in response to winds are the key contributors to the salinification of the upper Arctic Ocean over recent decades. Strength of the export of Arctic ice and water controls the supply of Arctic freshwater to subpolar basins while the intensity of the Arctic Ocean FWC anomalies is of less importance. Observational data demonstrate striking coherent long-term variations of the key Arctic climate parameters and strong coupling of long-term changes in the Arctic/North Atlantic climate system. Finally, since the high-latitude freshwater plays a crucial role in establishing and regulating global thermohaline circulation, the long-term variations of the freshwater content discussed here should be considered when assessing climate change and variability.

Dramatic changes have been observed in the Arctic over the last century. Many of these involve the storage and cycling of fresh water. On land, precipitation and river discharge, lake abundance and size, glacier area and volume, soil moisture, and a variety of permafrost characteristics have changed. In the ocean, sea ice thickness and areal coverage have decreased and water mass circulation patterns have shifted, changing freshwater pathways and sea ice cover dynamics. Precipitation onto the ocean surface has also changed. Such changes are expected to continue, and perhaps accelerate, in the coming century, enhanced by complex feedbacks between the oceanic, atmospheric, and terrestrial freshwater systems. Change to the arctic freshwater system heralds changes for our global physical and ecological environment as well as human activities in the Arctic. In this paper we review observed changes in the arctic freshwater system over the last century in terrestrial, atmospheric, and oceanic systems.

Over the past several decades, the Arctic Ocean has undergone substantial change. Enhanced transport of warmer air from lower latitudes has led to increased Arctic surface air temperature. Concurrent reductions in Arctic ice extent and thickness have been documented. The first evidence of warming in the intermediate Atlantic Water (AW, water depth between 150 and 900 meters) of the Arctic Ocean was found in 1990. Another anomaly, found in 2004, suggests that the Arctic Ocean is in transition toward a new, warmer state [Polyakov et al., 2005, and references therein].

Temperature, salinity, and chemical measurements, including the nutrients silicic acid, nitrate, nitrite, ammonium, and phosphate, the oxygen isotopic composition of seawater, and barium concentrations were obtained from the central Arctic Ocean along transects radiating from the North Pole in early spring, 2000–2006. Stations that were reoccupied over this time period were grouped into five regions: from Ellesmere Island, (1) north along 70°W and (2) northwest along 90°W; near the North Pole, (3) on the Amundsen Basin flank and (4) directly over the Lomonosov Ridge; (5) through the Makarov Basin along 170–180°W. These regions had been shown by others to have undergone marked changes in water-mass assemblies in the early 1990s, but our time series tracer hydrographic data indicate a partial return of Pacific origin water within the mixed layer and the upper halocline layers beginning in 2003–2004. Back-trajectories derived from satellite-tracked ice buoys for these stations indicate that the upper levels of Pacific water in the central Arctic in 2004–2006 transited westward from the Bering Strait along the Siberian continental slope into the East Siberian Sea before entering the Transpolar Drift Stream (TPD). By 2004, the TPD shifted back from an alignment over the Alpha-Mendeleev Ridge toward the Lomonosov Ridge, as was characteristic prior to the early 1990s. At most stations occupied in 2006, a decrease in the Pacific influence was observed, both in the mixed layer and in the upper halocline, which suggests the Canadian branch of the TPD was shifting back toward North America. Clearly the system is more variable than has been previously appreciated.

This paper synthesizes a variety of atmospheric and oceanic data to examine the large-scale energy budget of the Arctic. Assessment of the atmospheric budget relies primarily on the ERA-40 reanalysis. The seasonal cycles of vertically integrated atmospheric energy storage and the convergence of energy transport from ERA-40, as evaluated for the polar cap (defined by the 70°N latitude circle), in general compare well with realizations from the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis over the period 1979–2001. However, shortcomings in top of atmosphere radiation, as compared to satellite data, and the net surface flux, contribute to large energy budget residuals in ERA-40. The seasonal cycle of atmospheric energy storage is strongly modulated by the net surface flux, which is also the primary driver of seasonal changes in heat storage within the Arctic Ocean. Averaged for an Arctic Ocean domain, the July net surface flux from ERA-40 of –100 W m^-2 (i.e., into the ocean), associated with sea ice melt and oceanic sensible heat gain, exceeds the atmospheric energy transport convergence of 91 W m^-2. During winter (for which budget residuals are large), oceanic sensible heat loss and sea ice growth yield an upward surface flux of 50–60 W m^-2, complemented with an atmospheric energy convergence of 80–90 W m^-2 to provide a net radiation loss to space of 175–180 W m^-2.

An ice-ocean model has been used to investigate the effect of vertical mixing on the circulation of the Atlantic Water layer (AL) in the Arctic Ocean. The motivation of this study comes from the disparate AL circulations in the various models that comprise the Arctic Ocean Model Intercomparison Project (AOMIP). It is found that varying vertical mixing significantly changes the ocean's stratification by altering the vertical distribution of salinity and hence the structure of the arctic halocline. In the Eurasian Basin, the changes in ocean stratification tend to change the strength and depth of the cyclonic AL circulation, but not the basic circulation pattern. In the Canada Basin, however, the changes in ocean stratification are sufficient to alter the direction of the AL circulation. Excessively strong vertical mixing drastically weakens the ocean stratification, leading to an anticyclonic circulation at all depths, including both the AL and the upper layer that consists of the surface mixed layer and the halocline. Overly weak vertical mixing makes the ocean unrealistically stratified, with a fresher and thinner upper layer than observations. This leads to an overly strong anticyclonic circulation in the upper layer and an overly shallow depth at which the underlying cyclonic circulation occurs. By allowing intermediate vertical mixing, the model does not significantly drift away from reality and is in a rather good agreement with observations of the vertical distribution of salinity throughout the Arctic Ocean. This realistic ocean stratification leads to a realistic cyclonic AL circulation in the Canada Basin. In order for arctic ice-ocean models to obtain realistic cyclonic AL circulation in the Canada Basin, it is essential to generate an upward concave-shaped halocline across the basin at certain depths, consistent with observations.

Ocean temperature and salinity data over the period 1950%u20132000 in the Northern Seas, defined here as the North Atlantic Ocean (north of 50°N), North Pacific Ocean (north of 40°N), and Arctic Oceans, are combined to diagnose the steric (i.e., density) contribution to sea level variation. The individual contributions to steric height from temperature (thermosteric height) and salinity (halosteric height) are also analyzed. It is found that during 1950–2000, steric height rose over the study's domain, mostly as a result of halosteric increases (i.e., freshening). Over a shorter time period (late 1960s to early 1990s) during which climate indices changed dramatically, steric height gradients near the Nordic Seas minimum were reduced by 18%–32%. It is speculated that this may be associated with a local slowing of both the Meridional Overturning Circulation and the southward flow through Fram Strait. However, steric height increases in the North Pacific Ocean during this time imply a possible acceleration of flow through the poorly measured Canadian Arctic. Evidence that the Great Salinity Anomaly of the late 1960s and 1970s had two distinct Arctic Ocean sources is also found: a late 1960s export of sea ice, and a delayed but more sustained 1970s export of liquid (ocean) freshwater. A simple calculation indicates that these Arctic Ocean freshwater sources were not sufficient to create the 1970s freshening observed in the North Atlantic Ocean.

Upper ocean hydrography in the central Arctic Ocean has relaxed since 2000 to near-climatological conditions that pertained before the dramatic changes of the 1990s. The behavior of the anomalies of temperature and salinity in the central Arctic Ocean follow a first-order linear response to the AO with time constant of 5 years and a delay of 3 years.

The formation of a low salinity anomaly observed in the southern Beaufort Gyre in fall 1997 is examined, using output from a numerical sea ice – ocean climate model. The anomaly forms from locally reduced fall ice growth and from advection of river water. With regard to the latter, we find anomalous northwestward advection of water from the Mackenzie River delta (MRD) during 1997–1999, which fed a low salinity anomaly that circulated and deepened in the Beaufort Gyre until summer 2002, when it dissipated. The MRD salinity anomaly was especially fresh in 1997 because unusually convergent sea ice the previous summer and fall 1996 suppressed fall ice growth. The model shows a high correlation between advection from the MRD and salinity anomalies in the southern Beaufort Gyre until about 2002, when the correlation weakens as local sea ice melt/growth becomes the dominant forcing.

This study was motivated by a strong warming signal seen in mooring-based and oceanographic survey data collected in 2004 in the Eurasian Basin of the Arctic Ocean. The source of this and earlier Arctic Ocean changes lies in interactions between polar and sub-polar basins. Evidence suggests such changes are abrupt, or pulse-like, taking the form of propagating anomalies that can be traced to higher-latitudes. For example, an anomaly found in 2004 in the eastern Eurasian Basin took ~1.5 years to propagate from the Norwegian Sea to the Fram Strait region, and additional ~4.5–5 years to reach the Laptev Sea slope. While the causes of the observed changes will require further investigation, our conclusions are consistent with prevailing ideas suggesting the Arctic Ocean is in transition towards a new, warmer state.

Dissolved oxygen (O₂) profiling by new generation sensors was conducted in the Arctic Ocean via aircraft during May 2003 as part of the North Pole Environmental Observatory (NPEO) and Freshwater Switchyard (SWYD) projects. At stations extending from the North Pole to the shelf off Ellesmere Island, such profiles display what appear to be various O₂ maxima (with concentrations 70% of saturation or less) over depths of 70–110 m in the halocline, corresponding to salinity and temperature ranges of 33.3–33.9 and ~1.7 to ~1.5°C. The features appear to be widely distributed: Similar features based on bottle data were recently reported for a subset of the 1997–1998 SHEBA stations in the southern Canada Basin and in recent Beaufort Sea sensor profiles. Oxygen sensor data from August 2002 Chukchi Borderlands (CBL) and 1994 Arctic Ocean Section (AOS) projects suggest that such features arise from interleaving of shelf-derived, O₂-depleted waters. This generates apparent oxygen maxima in Arctic Basin profiles that would otherwise trend more smoothly from near-saturation at the surface to lower concentrations at depth. For example, in the Eurasian Basin, relatively low O₂ concentrations are observed at salinities of about 34.2 and 34.7. The less saline variant is identified as part of the lower halocline, a layer originally identified by a Eurasian Basin minimum in "NO," which, in the Canadian Basin, is reinforced by additional inputs. The more saline and thus denser variant appears to arise from transformations of Atlantic source waters over the Barents and/or Kara shelves. Additional low-oxygen waters are generated in the vicinity of the Chukchi Borderlands, from Pacific shelf water outflows that interleave with Eurasian waters that flow over the Lomonosov Ridge into the Makarov Basin and then into the Canada Basin. One such input is associated with the well-known silicate maximum that historically has been associated with a salinity of %u224833.1. Above that (322-depleted.

We propose that these low O₂ waters influence the NPEO and SWYD profiles to varying extents in a manner reflective of the large-scale circulation. The patterns of halocline circulation we infer from the intrusive features defy a simple boundary-following cyclonic flow. These results demonstrate the value of the improved resolution made feasible with continuous O₂ profiling. In the drive to better understand variability and change in the Arctic Ocean, deployment of appropriately calibrated CTD-O₂ packages offers the promise of important new insights into circulation and ecosystem function.

We present an analysis of observed long-term (~100 year) salinity trends on the freshwater-dominated Siberian continental shelves. A multiple regression was performed in the White Sea (WS), the Kara Sea (KS), the Laptev Sea (LS), and the East Siberian Sea (ESS). Since 1930, the WS has gained freshwater while the ESS has lost it, consistent with river discharge trends over this period. Over the past 20 years, increases in both river discharge and direct precipitation can explain observed salinity decreases in the WS, but not in the KS. Salinity trends in the LS and ESS indicate that ocean circulation plays a dominate role in these areas, where in recent years freshwater has been diverted eastward along the coast, rather than northward toward the deep ocean.

A global ice-ocean model shows increasing Atlantic water (AW) inflow at the Iceland-Scotland Ridge (ISR) during 1953–2002. As a result, the Greenland-Iceland-Norwegian (GIN) Sea is gaining more heat and salt from the North Atlantic Ocean, while the latter is being freshened mainly by exporting more salt to the GIN Sea. The exchanges of volume, heat, and freshwater at the Greenland-Scotland Ridge (GSR) are strongly correlated with the North Atlantic Oscillation (NAO) and their positive trend is closely linked to the NAO elevation in recent decades. The model confirms observations of decreasing dense water outflow at the Faroe-Scotland Passage since the 1950s. However, the simulated dense water outflow shows an increase at Denmark Strait, at the Iceland-Faroe Ridge, and at the GSR as a whole, owing to an increase in AW inflow that may cause an increase in AW recirculation and deep water production in the GIN Sea. The increase of the ISR heat inflow since 1965 contributes to continued thinning of the arctic sea ice since 1966. The influence of the heat inflow on arctic sea ice lags 2–3 years, which suppresses ice production even when the NAO temporarily shifts to a negative mode. Because of this delay, the decline of arctic sea ice is likely to continue if the inflow continues to increase and if the NAO does not shift to a sustained negative mode.

Within the framework of the Arctic Ocean Model Intercomparison Project results from several coupled sea ice–ocean models are compared in order to investigate vertically integrated properties of the Arctic Ocean. Annual means and seasonal ranges of streamfunction, freshwater and heat content are shown. For streamfunction the entire water column is integrated. For heat and freshwater content integration is over the upper 1000 m. The study represents a step toward identifying differences among model approaches and will serve as a base for upcoming studies where all models will be executed with common forcing. In this first stage only readily available outputs are compared, while forcing as well as numerical parameterizations differ.

The intercomparison shows streamfunctions differing in pattern and by several Sverdrups in magnitude. Differences occur as well for the seasonal range, where streamfunction is subject to large variability.

Annual mean heat content, referenced to 0°C, in the Canada Basin varies from –3.5 to +1.8 GJ m^-2 among the models, representing both colder and warmer solutions compared to the climatology. Seasonal range is highest in regions with seasonal or no ice cover.

Corresponding freshwater content, referenced to 34.8 ppt, shows differences most obviously in the Beaufort Sea and Canada Basin where maximum values vary between 6 and 24 m for the individual models. Maxima in the seasonal range are related to river inflow.

In the current stage of the project, applied windstress contributes significantly to the differences. However differences due to model resolutions and model parameterizations can already be detected.

We present an analysis of Arctic Ocean hydrographic and sea ice observations from the 1990s, with a focus on the circulation of water that originates in the North Pacific Ocean. Previous studies have shown the presence of two varieties of relatively warm "summer halocline water" in the vicinity of the Chukchi Sea, i.e., the relatively fresh Alaskan Coastal Water (ACW) and the relatively saltier summer Bering Sea Water (sBSW). Here we extend these studies by tracing the circulation of these waters downstream into the Arctic Ocean. We find that ACW is generally most evident in the southern Beaufort Gyre, while sBSW is strongest in the northern portion of the Beaufort Gyre and along the Transpolar Drift Stream. We find that this separation is most extreme during the early mid-1990s, when the Arctic Oscillation was at historically high index values. This leads us to speculate that the outflow to the North Atlantic Ocean (through the Canadian Archipelago and Fram Strait) may be similarly separated. As Arctic Oscillation index values fell during the later 1990s, ACW and sBSW began to overlap in their regions of influence. These changes are evident in the area north of Ellesmere Island, where the influence of sBSW is highly correlated, with a 3-year lag, with the Arctic Oscillation index. We also note the presence of winter Bering Sea Water (wBSW), which underlies the summer varieties. All together, this brings the number of distinct Pacific water types in our Arctic Ocean inventory to three: ACW, sBSW, and wBSW.

Scientists have argued for a number of years that the Arctic may be a sensitive indicator of global change, but prior to the 1990s, conditions there were believed to be largely static. This has changed in the last 10 years. Decadal-scale changes have occurred in the atmosphere, in the ocean, and on land [Serreze et al., 2000]. Surface atmospheric pressure has shown a declining trend over the Arctic, resulting in a clockwise spin-up of the atmospheric polar vortex. In the 1990s, the Arctic Ocean circulation took on a more cyclonic character, and the temperature of Atlantic water in the Arctic Ocean was found to be the highest in 50 years of observation [Morison et al., 2000]. Sea-ice thickness over much of the Arctic decreased 43% in 1958–1976 and 1993–1997 [Rothrock et al., 1999].

The evolution during the 1990's of the cold halocline layer (CHL) of the Arctic Ocean is investigated using data from icebreaker and SCICEX submarine cruises. The CHL disappearance and subsequent partial recovery is described along repeated transects through the central Arctic Ocean from the Alpha Ridge to the Nansen Basin. Salinity at the top of the halocline is used as a measure of halocline development, with high salinity corresponding to a poorly developed halocline. In the Nansen, Amundsen, and Makarov basins, upper ocean salinity increased from 1991 to 1998 as the CHL disappeared, then decreased from 1998 to 2000 as it recovered. Salinity was higher over the study region through the 1990's than at any time during the prior 40 year period, hence the 1990's CHL recovery was only partial. Disappearance of the CHL from the Eurasian Basin in the early 1990's was due to a shift from the Laptev to East Siberian seas of the region for seaward flow of low salinity Siberian shelf waters. Ice velocities and sea level pressure fields suggest that the reappearance of the CHL in 1999 corresponded to a shift of this flow back to the Laptev Sea region.

CTD measurements from the Arctic Ocean 2001 expedition reveal that the cold halocline layer (CHL) has returned to the Amundsen Basin at a position close to that found during the Oden'91 expedition. River water from the Siberian shelves formed a strong freshwater front in the Amundsen Basin, extending from the Gakkel Ridge to the Lomonosov Ridge. Furthermore, we show from model computations that the presence of a CHL may increase winter sea ice growth by 0.25 m over one season compared to a case with a non-existing CHL due to increased vertical heat flux from the warm Atlantic water. The difference in sea ice growth is due to a much shallower winter convection with a CHL present, which is not able to reach into the warm Atlantic layer, resulting in a considerably smaller oceanic heat flux.

The Arctic Ocean is an important component of the global climate system. The processes occurring in the Arctic Ocean affect the rate of deep and bottom water formation in the convective regions of the high North Atlantic and influence ocean circulation across the globe. This fact is highlighted by global climate modeling studies that consistently show the Arctic to be one of the most sensitive regions to climate change. But an identification of the differences among models and model systematic errors in the Arctic Ocean remains unchecked, despite being essential to interpreting the simulation results and their implications for climate variability. For this reason, the Arctic Ocean Model Intercomparison Project (AOMIP), an international effort, was recently established to carry out a thorough analysis of model differences and errors. The geographical focus of this effort is shown in Figure 1.

Numerous recent observations indicate that the Arctic is undergoing a significant change. In the last decade, the hydrography of the Arctic Ocean has shifted, and the atmospheric circulation has undergone a change from the lower stratosphere to the surface. Typically the eastern Arctic Ocean, on the European side of the Lomonosov Ridge, is dominated by water of Atlantic origin. A cold halocline of varying thickness overlies the warmer Atlantic water and isolates it from the sea ice and surface mixed layer. The western Arctic Ocean, on the North American side of the Lomonosov Ridge, is characterized by an added layer of water from the Pacific immediately below the surface mixed layer. Data collected during several cruises from 1991 to 1995 indicate that in the 1990s the boundary between these eastern and western halocline types shifted from a position roughly parallel to the Lomonosov Ridge to near alignment with the Alpha and Mendeleyev Ridges. The Atlantic Water temperature has also increased, and the cold halocline has become thinner. The change has resulted in increased surface salinity in the Makarov Basin. Recent results suggest that the change also includes decreased surface salinity and greater summer ice melt in the Beaufort Sea. Atmospheric pressure fields and ice drift data show that the whole patterns of atmospheric pressure and ice drift for the early 1990s were shifted counterclockwise 40°-60° from earlier patterns. The shift in atmospheric circulation seems related to the Arctic Oscillation in the Northern Hemisphere atmospheric pressure pattern. The changes in the ocean circulation, ice drift, air temperatures, and permafrost can be explained as responses to the Arctic Oscillation, as can changes in air temperatures over the Russian Arctic.

It is well established that periods of high North Atlantic oscillation (NAO) index are characterized by a weakening of the surface high pressure and surface anticyclone in the Beaufort Sea and the intensification of the cyclonic circulation in the eastern Arctic Ocean. The response of Arctic sea ice to these atmospheric changes has been studied with a thickness distribution sea-ice model coupled to an ocean model. During a period of high NAO, 1989–96, the model shows a substantial reduction of ice advection into the eastern Arctic from the Canada Basin, and an increase of ice export through Fram Strait, both of which tend to deplete thick ice in the eastern Arctic Ocean and enhance it in the western Arctic, in an uneven dipolar pattern we call the East–West Arctic Anomaly Pattern (EWAAP). From the period 1979–88 with a lower-NAO index to the period 1988–96 with a high-NAO index, the simulated ice volume in the eastern Arctic drops by about a quarter, while that in the western Arctic increases by 16%. Overall, the Arctic Ocean loses 6%. The change from 1987 to 1996 is even larger — a loss of some 20% in ice volume for the whole Arctic. Both the model and satellite data show a significant reduction in ice extent in the eastern Arctic and in the Arctic Ocean as a whole.

There are corresponding changes in open water and therefore in ice growth, which tend to moderate the anomaly, and in lateral melting, which tends to enhance the anomaly. During the high NAO and strong EWAAP period, 1989%u201396, the eastern (western) Arctic has more (less) open water and enhanced (reduced) winter ice growth, so ice growth stabilizes the ice cover. On the other hand, the increased (decreased) open water enhances (reduces) summer melt by lowering (increasing) albedo in the eastern (western) Arctic. The nonlinearity of ice%u2013 albedo feedback causes the increased summer melt in the eastern Arctic to dominate the thermodynamic response and to collaborate with the ice advection pattern to enhance the EWAAP during high NAO.