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At least 343 records · Page 19

Tethered balloon-borne profile measurements of atmospheric properties in the cloudy atmospheric boundary layer over the Arctic sea ice during MOSAiC: Overview and first results

The tethered balloon-borne measurement system BELUGA (Balloon-bornE moduLar Utility for profilinG the lower Atmosphere) was deployed over the Arctic sea ice for 4 weeks in summer 2020 as part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition. Using BELUGA, vertical profiles of dynamic, thermodynamic, aerosol particle, cloud, radiation, and turbulence properties were measured from the ground up to a height of 1,500 m. BELUGA was operated during an anomalously warm period with frequent liquid water clouds and variable sea ice conditions. Three case studies of liquid water phase, single-layer clouds observed on 3 days (July 13, 23, and 24, 2020) are discussed to show the potential of the collected data set to comprehensively investigate cloud properties determining cloud evolution in the inner Arctic over sea ice. Simulated back-trajectories show that the observed clouds have evolved within 3 different air masses (“aged Arctic,” “advected over sea ice,” and “advected over open ocean”), which left distinct fingerprints in the cloud properties. Strong cloud top radiative cooling rates agree with simulated results of previous studies. The weak warming at cloud base is mostly driven by the vertical temperature profile between the surface and cloud base. In-cloud turbulence induced by the cloud top cooling was similar in strength compared to former studies. From the extent of the mixing layer, it is speculated that the overall cloud cooling is stronger and thus faster in the warm oceanic air mass. Larger aerosol particle number concentrations and larger sizes were observed in the air mass advected over the sea ice and in the air mass advected over the open ocean.

Arctic↗

Low ozone dry deposition rates to sea ice during the MOSAiC field campaign: Implications for the Arctic boundary layer ozone budget

Dry deposition to the surface is one of the main removal pathways of tropospheric ozone (O 3 ). We quantified for the first time the impact of O 3 deposition to the Arctic sea ice on the planetary boundary layer (PBL) O 3 concentration and budget using year-round flux and concentration observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign and simulations with a single-column atmospheric chemistry and meteorological model (SCM). Based on eddy-covariance O 3 surface flux observations, we find a median surface resistance on the order of 20,000 s m –1 , resulting in a dry deposition velocity of approximately 0.005 cm s –1 . This surface resistance is up to an order of magnitude larger than traditionally used values in many atmospheric chemistry and transport models. The SCM is able to accurately represent the yearly cycle, with maxima above 40 ppb in the winter and minima around 15 ppb at the end of summer. However, the observed springtime ozone depletion events are not captured by the SCM. In winter, the modelled PBL O 3 budget is governed by dry deposition at the surface mostly compensated by downward turbulent transport of O 3 towards the surface. Advection, which is accounted for implicitly by nudging to reanalysis data, poses a substantial, mostly negative, contribution to the simulated PBL O 3 budget in summer. During episodes with low wind speed (<5 m s –1 ) and shallow PBL (<50 m), the 7-day mean dry deposition removal rate can reach up to 1.0 ppb h –1 . Our study highlights the importance of an accurate description of dry deposition to Arctic sea ice in models to quantify the current and future O 3 sink in the Arctic, impacting the tropospheric O 3 budget, which has been modified in the last century largely due to anthropogenic activities.

54 ENVIRONMENTAL SCIENCES↗

The winter central Arctic surface energy budget: A model evaluation using observations from the MOSAiC campaign

This study evaluates the simulation of wintertime (15 October, 2019, to 15 March, 2020) statistics of the central Arctic near-surface atmosphere and surface energy budget observed during the MOSAiC campaign with short-term forecasts from 7 state-of-the-art operational and experimental forecast systems. Five of these systems are fully coupled ocean-sea ice-atmosphere models. Forecast systems need to simultaneously simulate the impact of radiative effects, turbulence, and precipitation processes on the surface energy budget and near-surface atmospheric conditions in order to produce useful forecasts of the Arctic system. This study focuses on processes unique to the Arctic, such as, the representation of liquid-bearing clouds at cold temperatures and the representation of a persistent stable boundary layer. It is found that contemporary models still struggle to maintain liquid water in clouds at cold temperatures. Given the simple balance between net longwave radiation, sensible heat flux, and conductive ground flux in the wintertime Arctic surface energy balance, a bias in one of these components manifests as a compensating bias in other terms. This study highlights the different manifestations of model bias and the potential implications on other terms. Three general types of challenges are found within the models evaluated: representing the radiative impact of clouds, representing the interaction of atmospheric heat fluxes with sub-surface fluxes (i.e., snow and ice properties), and representing the relationship between stability and turbulent heat fluxes.

54 ENVIRONMENTAL SCIENCES↗

Cloud-atmosphere impacts on the central Arctic surface energy budget (Final Report)

This project investigated how clouds and atmosphere-sea ice interactions shape the central Arctic surface energy budget using observations from the MOSAiC expedition and coordinated model experiments. Analyses focused on three themes. First, a new method applied to thermistor string data revealed that snow thermal conductivity is systematically higher than assumed in most models, strongly influencing conductive heat flux and sea ice growth, especially under clear skies. Second, a full annual cycle of surface energy budget observations, combined with detailed cloud microphysical retrievals, demonstrated how cloud regimes regulate radiative, turbulent, and conductive fluxes, driving seasonal contrasts in sea ice energy balance: in winter, radiative forcing elicits strong turbulent and conductive responses, while in summer excess energy is primarily partitioned into surface melt. Third, these observations were used to evaluate and improve regional and global forecast models. While some models captured key Arctic cloud-radiation states, most exhibited persistent deficiencies in representing liquid-containing clouds, snow-on-sea-ice processes, and flux responses to radiative forcing. Together, these results provide unprecedented benchmarks for understanding coupled Arctic processes, improve parameterizations of snow, sea ice, and cloud interactions, and highlight critical pathways by which atmospheric variability drives sea ice change in a rapidly evolving Arctic system. Lastly, the project was a resounding success, resulting in 38 peer-reviewed publications and dozens of presentations, while also supporting an early career scientist.

54 ENVIRONMENTAL SCIENCES↗

Linking climate change and human systems: a case study of Arctic pipelines

This case study estimates the potential economic risk from permafrost thaw on oil and gas pipelines in the Russian Arctic as part of a larger effort to better understand complex interactions between human and earth systems in the Arctic. Pan-Arctic simulations of permafrost thaw-depth from the Community Land Model version 4.5 and ground ice characteristics were used to generate ground subsidence projections over the period 2020 to 2040 with a quantification of uncertainty. Russian oil and gas transmission pipeline networks were then overlaid on the permafrost thaw projections in ArcGIS to identify pipelines vulnerable to damage from permafrost thaw. Recent pipeline construction costs were used to estimate the total replacement costs for at-risk pipelines under several thaw scenarios. The results indicate that permafrost thaw poses a major threat to pipeline infrastructure, especially gas pipelines, in the Russian Arctic. Over the twenty-year study period, total replacement costs for oil and gas pipelines were estimated at $\$$110 billion in 2020 USD. Reduced economic viability of pipelines under climate change will likely trigger major shifts in the Russian oil and gas industry, which would have impacts on markets, emissions, and geopolitics.

54 ENVIRONMENTAL SCIENCES↗

The correlation between Arctic sea ice, cloud phase and radiation using A-Train satellites

Abstract. Climate warming has a stronger impact on Arctic climate and sea ice cover (SIC) decline than previously thought. Better understanding and characterization of the relationship between sea ice and clouds and the implications for surface radiation is key to improving our confidence in Arctic climate projections. Here we analyze the relationship between sea ice, cloud phase and surface radiation over the Arctic, defined as north of 60° N, using active- and passive-sensor satellite observations from three different datasets. We find that all datasets agree on the climatology of and seasonal variability in total and liquid-bearing (liquid and mixed-phase) cloud covers. Similarly, our results show a robust relationship between decreased SIC and increased liquid-bearing clouds in the lowest levels (below 3 km) for all seasons (strongest in winter) but summer, while increased SIC and ice clouds are positively correlated in two of the three datasets. A refined map correlation analysis indicates that the relationship between SIC and liquid-bearing clouds can change sign over the Bering, Barents and Laptev seas, likely because of intrusions of warm air from low latitudes during winter and spring. Finally, the increase in liquid clouds resulting from decreasing SIC is associated with enhanced radiative cooling at the surface. Our findings indicate that the newly formed liquid clouds reflect more shortwave (SW) radiation back to space compared to the surface, generating a cooling effect of the surface, while their downward longwave (LW) radiation is similar to the upward LW surface emission, which has a negligible radiative impact on the surface. This overall cooling effect should contribute to dampening future Arctic surface warming as SIC continues to decline.

54 ENVIRONMENTAL SCIENCES↗

Quantifying the impacts of atmospheric rivers on the surface energy budget of the Arctic based on reanalysis

We present a comprehensive analysis of Arctic surface energy budget (SEB) components during atmospheric river (AR) events identified by integrated water vapor transport exceeding the monthly 85th-percentile climatological threshold in 3-hourly ERA5 reanalysis data from January 1980 to December 2019. Analysis of average anomalies in SEB components, net SEB, and the overall AR contribution to both the seasonal SEB components and net SEB climatology reveals clear seasonality and distinct land–sea–sea ice contrast patterns. Over the sea-ice-covered central Arctic Ocean, ARs significantly impact net SEB, inducing substantial surface warming in fall, winter, and spring. This warming is primarily driven by large anomalies in surface downward longwave radiation (LWD), which average 29–45 W m −2 during the cold seasons. In contrast, AR-related LWD anomalies are smaller in summer, averaging around 15 W m −2 , indicating a reduced impact during this season. Over sub-polar oceans, ARs have the most substantial positive impact on net SEB in cold seasons, mainly attributed to significant positive turbulent heat flux anomalies. AR-related turbulent heat anomalies reduce the upward turbulent flux, contributing up to −11 % relative to its seasonal climatology. In summer, ARs induce negative impacts on net SEB, primarily due to reduced shortwave radiation from increased cloud cover during AR events. Over continents, ARs generate smaller absolute impacts on net SEB because the large LWD anomalies are largely offset by corresponding increases in upward longwave radiation, particularly during cold seasons. Additionally, the seemingly large relative contributions of ARs to the net SEB over land primarily reflects the small magnitude of the climatological net SEB over continents. Greenland, especially western Greenland, exhibits significant downward longwave radiation anomalies associated with ARs, which drive large net SEB anomalies and contribute >54 % to mean SEB and induce amplified surface warming year-round. This holds significance for melt events, particularly during summer. Additionally, results of AR-related SEB impacts strongly depend on detection methods, as restrictive AR detection algorithms that emphasize extreme AR events, with large AR-related anomalies, do not necessarily indicate a large overall contribution to the SEB climatology due to the low occurrence frequency of these events. This study quantifies the role of ARs in the surface energy budget, contributing to our understanding of the Arctic warming and sea ice decline in ongoing Arctic amplification.

Arctic Sea ice change↗

Interactions between the Arctic Mediterranean and the Atlantic Meridional Overturning Circulation: A Review

The Atlantic Meridional Overturning Circulation (AMOC) plays a significant role in the global climate system, and its behavior in a warming climate is a matter of significant concern. The AMOC is thought to be driven largely by ocean heat loss in the subpolar North Atlantic Ocean, but recent research increasingly emphasizes the importance of the Arctic Mediterranean for the AMOC. In turn, the AMOC may influence the Arctic heat budget through its impact on poleward heat transport. Hence, understanding the processes that link the AMOC and the Arctic is critical for our ability to project how both may evolve in a warming climate. In this paper we review some of the recent research that is shaping our thinking about the AMOC and its two-way interactions with the Arctic.

54 ENVIRONMENTAL SCIENCES↗

Dynamics of Aboveground Phytomass of the Circumpolar Arctic Tundra During the Past Three Decades

Numerous studies have evaluated the dynamics of Arctic tundra vegetation throughout the past few decades, using remotely sensed proxies of vegetation, such as the normalized difference vegetation index (NDVI). While extremely useful, these coarse-scale satellite-derived measurements give us minimal information with regard to how these changes are being expressed on the ground, in terms of tundra structure and function. In this analysis, we used a strong regression model between NDVI and aboveground tundra phytomass, developed from extensive field-harvested measurements of vegetation biomass, to estimate the biomass dynamics of the circumpolar Arctic tundra over the period of continuous satellite records (1982-2010). We found that the southernmost tundra subzones (C-E) dominate the increases in biomass, ranging from 20 to 26%, although there was a high degree of heterogeneity across regions, floristic provinces, and vegetation types. The estimated increase in carbon of the aboveground live vegetation of 0.40 Pg C over the past three decades is substantial, although quite small relative to anthropogenic C emissions. However, a 19.8% average increase in aboveground biomass has major implications for nearly all aspects of tundra ecosystems including hydrology, active layer depths, permafrost regimes, wildlife and human use of Arctic landscapes. While spatially extensive on-the-ground measurements of tundra biomass were conducted in the development of this analysis, validation is still impossible without more repeated, long-term monitoring of Arctic tundra biomass in the field.

Arctic tundra↗

Arctic Sea Ice in Transformation: A Review of Recent Observed Changes and Impacts on Biology and Human Activity

Sea ice in the Arctic is one of the most rapidly changing components of the global climate system. Over the past few decades, summer areal extent has declined over 30, and all months show statistically significant declining trends. New satellite missions and techniques have greatly expanded information on sea ice thickness, but many uncertainties remain in the satellite data and long-term records are sparse. However, thickness observations and other satellite-derived data indicate a 40 decline in thickness, due in large part to the loss of thicker, older ice cover. The changes in sea ice are happening faster than models have projected. With continued increasing temperatures, summer ice-free conditions are likely sometime in the coming decades, though there are substantial uncertainties in the exact timing and high interannual variability will remain as sea ice decreases. The changes in Arctic sea ice are already having an impact on flora and fauna in the Arctic. Some species will face increasing challenges in the future, while new habitat will open up for other species. The changes are also affecting peoples living and working in the Arctic. Native communities are facing challenges to their traditional ways of life, while new opportunities open for shipping, fishing, and natural resource extraction.

Sea Ice↗

Aircraft-Measured Indirect Cloud Effects from Biomass Burning Smoke in the Arctic and Subarctic

The incidence of wildfires in the Arctic and subarctic is increasing; in boreal North America, for example, the burned area is expected to increase by 200-300 over the next 50-100 years, which previous studies suggest could have a large effect on cloud microphysics, lifetime, albedo, and precipitation. However, the interactions between smoke particles and clouds remain poorly quantified due to confounding meteorological influences and remote sensing limitations. Here, we use data from several aircraft campaigns in the Arctic and subarctic to explore cloud microphysics in liquid-phase clouds influenced by biomass burning. Median cloud droplet radii in smoky clouds were 50 smaller than in background clouds. Based on the relationship between cloud droplet number (N(liq))/ and various biomass burning tracers (BBt/ across the multi-campaign dataset, we calculated the magnitude of subarctic and Arctic smoke aerosol-cloud interactions (ACI, where ACI = (1/3) x dln(N(liq))/dln(BBt)) to be 0.12 out of a maximum possible value of 0.33 that would be obtained if all aerosols were to nucleate cloud droplets. Interestingly, in a separate subarctic case study with low liquid water content (0.02 gm/ cu m) and very high aerosol concentrations (2000-3000 cu m) in the most polluted clouds, the estimated ACI value was only 0.06. In this case, competition for water vapor by the high concentration of CCN strongly limited the formation of droplets and reduced the cloud albedo effect, which highlights the importance of cloud feedbacks across scales. Using our calculated ACI values, we estimate that the smoke-driven cloud albedo effect may decrease shortwave radiative flux by 2 and 4 W/sq or more under some low and homogeneous cloud cover conditions in the subarctic, although the changes should be smaller in high surface albedo regions of the Arctic. We lastly show evidence to suggest that numerous northern latitude background Aitken particles can interact with combustion particles, perhaps impacting their properties as cloud condensation and ice nuclei. However, the influence of background particles on smoke-driven indirect effects is currently unclear.

Arctic↗

Comparison of Passive Microwave-Derived Early Melt Onset Records on Arctic Sea Ice

Two long records of melt onset (MO) on Arctic sea ice from passive microwave brightness temperatures (Tbs) obtained by a series of satellite-borne instruments are compared. The Passive Microwave (PMW) method and Advanced Horizontal Range Algorithm (AHRA) detect the increase in emissivity that occurs when liquid water develops around snow grains at the onset of early melting on sea ice. The timing of MO on Arctic sea ice influences the amount of solar radiation absorbed by the ice-ocean system throughout the melt season by reducing surface albedos in the early spring. This work presents a thorough comparison of these two methods for the time series of MO dates from 1979through 2012. The methods are first compared using the published data as a baseline comparison of the publically available data products. A second comparison is performed on adjusted MO dates we produced to remove known differences in inter-sensor calibration of Tbs and masking techniques used to develop the original MO date products. These adjustments result in a more consistent set of input Tbs for the algorithms. Tests of significance indicate that the trends in the time series of annual mean MO dates for the PMW and AHRA are statistically different for the majority of the Arctic Ocean including the Laptev, E. Siberian, Chukchi, Beaufort, and central Arctic regions with mean differences as large as 38.3 days in the Barents Sea. Trend agreement improves for our more consistent MO dates for nearly all regions. Mean differences remain large, primarily due to differing sensitivity of in-algorithm thresholds and larger uncertainties in thin-ice regions.

sea ice↗

Variability and Trends in the Arctic Sea Ice Cover: Results from Different Techniques

Variability and trend studies of sea ice in the Arctic have been conducted using products derived from the same raw passive microwave data but by different groups using different algorithms. This study provides consistency assessment of four of the leading products, namely, Goddard Bootstrap (SB2), Goddard NASA Team (NT1), EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF 1.2), and Hadley HadISST 2.2 data in evaluating variability and trends in the Arctic sea ice cover. All four provide generally similar ice patterns but significant disagreements in ice concentration distributions especially in the marginal ice zone and adjacent regions in winter and meltponded areas in summer. The discrepancies are primarily due to different ways the four techniques account for occurrences of new ice and meltponding. However, results show that the different products generally provide consistent and similar representation of the state of the Arctic sea ice cover. Hadley and NT1 data usually provide the highest and lowest monthly ice extents, respectively. The Hadley data also show the lowest trends in ice extent and ice area at negative 3.88 percent decade and negative 4.37 percent decade, respectively, compared to an average of negative 4.36 percent decade and negative 4.57 percent decade for all four. Trend maps also show similar spatial distribution for all four with the largest negative trends occurring at the Kara/Barents Sea and Beaufort Sea regions, where sea ice has been retreating the fastest. The good agreement of the trends especially with updated data provides strong confidence in the quantification of the rate of decline in the Arctic sea ice cover.

Arctic↗

Understanding Arctic Surface Temperature Differences in Reanalyses

Reanalyses in the Arctic are widely used for model evaluation and for understanding contemporary climate change. Nevertheless, differences among reanalyses in fundamental meteorological variables including surface air temperature are large. A review of surface temperature differences is presented with a particular focus on differences in contemporary reanalyses. An important consideration is the significant differences in Arctic surfaces, including the central Arctic Ocean, the Greenland Ice Sheet, and non-glaciated land. While there is significant correlation among reanalyses in annual time series, there is substantial disagreement in mean values. For the period 1980-2013, the trend in annual temperature ranges from 0.3 to 0.7K per decade. Over the central Arctic Ocean, differences in mean values and trends are larger. Most of the uncertainty is associated with winter months. This is likely associated with the constraint imposed by melting processes (i.e. 0 deg. Celsius), rather than seasonal changes to the observing system.

Sea Ic↗

Sensitivity of Low Tropospheric Arctic Temperatures to Assimilation of AIRS Cloud-Cleared Radiances: Impact on Mid-Latitude Waves

In this work, it is shown that the prediction of individual mid-latitude waves in a global forecast framework is sensitive to the initialization over the Arctic and may benefit from the assimilation of cloud-cleared radiances (CCRs) from the Atmospheric Infrared Sounder (AIRS), particularly in partially cloudy regions with active dynamics. This study shows that the assimilation of AIRS CCRs over the Arctic Ocean, providing more information than clear-sky radiances from areas affected by broken low-level stratus clouds, produces slightly cooler low-level temperatures and lower mid-tropospheric height through hydrostatic adjustment. In areas that are data void, as observed by clear-sky radiances, and dynamically active, the assimilation of CCRs provides valuable information that can improve the representation of individual baroclinic waves and their subsequent forecasts. The modifications induced by the assimilation of AIRS CCRs over the Arctic Ocean slightly modifies the geopotential height gradients between the Arctic and the mid-latitudes, leading to potential improvements in the forecast of individual baroclinic waves as is shown through a case study. The observing system experiment (OSE) is performed with the NASA Goddard Earth Observing System (GEOS) data assimilation and forecast system during boreal autumn 2014. AIRS CCRs are thinned to approximately one quarter the density of operationally assimilated AIRS radiances, consistent with their higher information content. Global, 6-hourly analyses are produced from 1 September to 10 November 2014 and 7-day forecasts are initialized at 0000 UTC daily. Since the CCR methodology is widely applicable, these findings are also relevant to other infrared sensors.

Cloud-clearing↗

Overview of Large-Scale Transport into the Arctic in the Chemistry Climate Model Initiative (CCMI) Simulations

The transport of trace gases and aerosols is a major uncertainty in the modeling of Arctic tropospheric composition. Here we compare the large-scale midlatitude-to-Arctic transport properties among different models participating in the Chemistry Climate Modeling Initiative (CCMI). Among simulations of the recent past (1980-2010) we show that there are substantial (~30-45%) differences in transport to the Arctic free troposphere, as diagnosed through use of idealized tracers emitted over the Northern Hemisphere (NH) midlatitude surface and subject to prescribed uniform loss. In addition, we show that the spread among tracers with predominantly land-based sources is correlated with the spread in the location of the Hadley Cell edge, while the spread in tracers with zonally uniform sources is also related to differences in (parameterized) convection over oceans. Interestingly, comparisons with simulations constrained with analysis fields reveal similar, if not larger, transport differences, compared to the free-running simulations, indicating that caution should be taken when interpreting simulations constrained with analyzed winds. Finally, among simulations of the 21st century we show that models project a consistent, albeit small (~5-10%), increase in transport from the NH midlatitude surface to the Arctic upper troposphere.

Large-Scale Transpor↗

The Future of Arctic Fires: Leveraging Ongoing Activities, New Efforts, and International Cooperation

Fires in the Arctic region are gaining more attention and driving increased concern from the public, the scientific community, and policymakers. An increasing number of scientific projects, collaboration efforts, media coverage, and policy assessments have been and are being implemented and published regarding this emerging and important wildland fire phenomenon. In short, this increased activity comes from the recognition of increasing fire risk and activity close to, within, and impacting the Arctic. There is a need to integrate these numerous and expanding local, national, and international efforts to avoid redundant and overlapping efforts and to focus resources more efficiently. As a response, this report suggests short and long-term goals to respond to the growing fire risk and fire danger in the Arctic. All efforts call for more integrated international collaboration and greater recognition of the importance for Arctic communities to be collaborators and leaders.

Future↗

The Correlation Between Arctic Sea Ice, Cloud Phase and Radiation Using A-Train Satellites

Climate warming has a stronger impact on Arctic climate and sea ice cover (SIC) decline than previously thought. Better understanding and characterization of the relationship between sea ice and clouds and the implications for surface radiation is key to improving our confidence in Arctic climate projections. Here we analyze the relationship between sea ice, cloud phase and surface radiation over the Arctic, defined as north of 60° N, using active- and passive-sensor satellite observations from three different datasets. We find that all datasets agree on the climatology of and seasonal variability in total and liquid-bearing (liquid and mixed-phase) cloud covers. Similarly, our results show a robust relationship between decreased SIC and increased liquid-bearing clouds in the lowest levels (below 3 km) for all seasons (strongest in winter) but summer, while increased SIC and ice clouds are positively correlated in two of the three datasets. A refined map correlation analysis indicates that the relationship between SIC and liquid-bearing clouds can change sign over the Bering, Barents and Laptev seas, likely because of intrusions of warm air from low latitudes during winter and spring. Finally, the increase in liquid clouds resulting from decreasing SIC is associated with enhanced radiative cooling at the surface. Our findings indicate that the newly formed liquid clouds reflect more shortwave (SW) radiation back to space compared to the surface, generating a cooling effect of the surface, while their downward longwave (LW) radiation is similar to the upward LW surface emission, which has a negligible radiative impact on the surface. This overall cooling effect should contribute to dampening future Arctic surface warming as SIC continues to decline.

Arctic climate↗