Arctic Change Research Articles

The Relative Importance of Antarctic Sea Ice Loss within the Response to Greenhouse Warming

Abstract The response to Antarctic sea ice loss within a coupled modeling framework is examined in comparison to the response to Arctic sea ice loss and within the context of general greenhouse warming. Sea ice loss responses are found to be linear (particularly in response to Antarctic or global sea ice loss) with respect to the degree of imposed perturbation and additive when perturbations are applied in hemispheres separately and concurrently. Globally, and in the tropical Pacific in particular, Antarctic sea ice loss plays a relatively larger role than Arctic sea ice loss in both the atmosphere and the ocean, within the parameters of our experiments. The pattern of response to Antarctic sea ice loss is also found to more closely resemble that of greenhouse warming, again particularly in the tropics. An extension to multiparameter pattern scaling is developed to include a scaling factor for Antarctic change in addition to those for tropical warming and Arctic sea ice loss. The decomposition is applied to the modeled response to Antarctic sea ice loss to break it down into component partial responses that scale with Antarctic, tropical, and Arctic changes. This reveals the aspects of the response that are directly related to Antarctic change, such as an equatorward intensification of tropical precipitation in the Northern Hemisphere, and those that are modified via the induced changes in the tropics and Arctic, such as Northern Hemisphere temperature change. With this, we hope to gain a deeper understanding of the role of each of these changes for the development of physical mechanisms of the response.

Meteorological, snow and soil data, CO2, water and energy fluxes from a low-Arctic valley of Northern Quebec

Abstract. As the vegetation in the Arctic changes, tundra ecosystems along the southern border of the Arctic are becoming greener and gradually giving way to boreal ecosystems. This change is affecting local populations, wildlife, energy exchange processes between environmental compartments, and the carbon cycle. To understand the progression and the implications of this change in vegetation, satellite measurements and surface models can be employed. However, in situ observational data are required to validate these measurements and models. This paper presents observational data from two nearby sites in the forest–tundra ecotone in the Tasiapik Valley near Umiujaq in Northern Quebec, Canada. One site is on a mixture of lichen and shrub tundra. The associated data set comprises 9 years of meteorological, soil and snow data as well as 3 years of eddy covariance data. The other site, 850 m away, features vegetation consisting mostly of tall shrubs and black spruce. For that location, 6 years of meteorological, soil and snow data are available. In addition to the data from the automated stations, profiles of snow density and specific surface area were collected during field campaigns. The data are available at https://doi.org/10.1594/PANGAEA.964743 (Domine et al., 2024).

Towards an increasingly biased view on Arctic change

The Russian invasion of Ukraine hampers the ability to adequately describe conditions across the Arctic, thus biasing the view on Arctic change. Here we benchmark the pan-Arctic representativeness of the largest high-latitude research station network, INTERACT, with or without Russian stations. Excluding Russian stations lowers representativeness markedly, with some biases being of the same magnitude as the expected shifts caused by climate change by the end of the century.

ESD Ideas: Arctic amplification's contribution to breaches of the Paris Agreement

Abstract. The Arctic is warming at almost 4 times the global average rate. Here we reframe this amplified Arctic warming in terms of global climate ambition to show that without Arctic amplification, the world would breach the Paris Agreement's 1.5 and 2 ∘C limits 5 and 8 years later, respectively. We also find the Arctic to be a disproportionate contributor to uncertainty in the timing of breaches. The outsized influence of Arctic warming on global climate targets highlights the need for better modelling and monitoring of Arctic change.

Aerosol and dynamical contributions to cloud droplet formation in Arctic low-level clouds

Abstract. The Arctic is one of the most rapidly warming regions of the globe. Low-level clouds and fog modify the energy transfer from and to space and play a key role in the observed strong Arctic surface warming, a phenomenon commonly termed “Arctic amplification”. The response of low-level clouds to changing aerosol characteristics throughout the year is therefore an important driver of Arctic change that currently lacks sufficient constraints. As such, during the NASCENT campaign (Ny-Ålesund AeroSol Cloud ExperimeNT) extending over a full year from October 2019 to October 2020, microphysical properties of aerosols and clouds were studied at the Zeppelin station (475 m a.s.l.), Ny-Ålesund, Svalbard, Norway. Particle number size distributions obtained from differential mobility particle sizers as well as chemical composition derived from filter samples and an aerosol chemical speciation monitor were analyzed together with meteorological data, in particular vertical wind velocity. The results were used as input to a state-of-the-art cloud droplet formation parameterization to investigate the particle sizes that can activate to cloud droplets, the levels of supersaturation that can develop, the droplet susceptibility to aerosol and the role of vertical velocity. We evaluate the parameterization and the droplet numbers calculated through a droplet closure with in-cloud in situ measurements taken during nine flights over 4 d. A remarkable finding is that, for the clouds sampled in situ, closure is successful in mixed-phase cloud conditions regardless of the cloud glaciation fraction. This suggests that ice production through ice–ice collisions or droplet shattering may have explained the high ice fraction, as opposed to rime splintering that would have significantly reduced the cloud droplet number below levels predicted by warm-cloud activation theory. We also show that pristine-like conditions during fall led to clouds that formed over an aerosol-limited regime, with high levels of supersaturation (generally around 1 %, although highly variable) that activate particles smaller than 20 nm in diameter. Clouds formed in the same regime in late spring and summer, but aerosol activation diameters were much larger due to lower cloud supersaturations (ca. 0.5 %) that develop because of higher aerosol concentrations and lower vertical velocities. The contribution of new particle formation to cloud formation was therefore strongly limited, at least until these newly formed particles started growing. However, clouds forming during the Arctic haze period (winter and early spring) can be limited by updraft velocity, although rarely, with supersaturation levels dropping below 0.1 % and generally activating larger particles (20 to 200 nm), including pollution transported over a long range. The relationship between updraft velocity and the limiting cloud droplet number agrees with previous observations of various types of clouds worldwide, which supports the universality of this relationship.

Arctic weather variability and connectivity

The Arctic’s rapid sea ice decline may influence global weather patterns, making the understanding of Arctic weather variability (WV) vital for accurate weather forecasting and analyzing extreme weather events. Quantifying this WV and its impacts under human-induced climate change remains a challenge. Here we develop a complexity-based approach and discover a strong statistical correlation between intraseasonal WV in the Arctic and the Arctic Oscillation. Our findings highlight an increased variability in daily Arctic sea ice, attributed to its decline accelerated by global warming. This weather instability can influence broader regional patterns via atmospheric teleconnections, elevating risks to human activities and weather forecast predictability. Our analyses reveal these teleconnections and a positive feedback loop between Arctic and global weather instabilities, offering insights into how Arctic changes affect global weather. This framework bridges complexity science, Arctic WV, and its widespread implications.

Processes Controlling the Seasonally Varying Emergence of Forced Arctic Longwave Radiation Changes

Abstract Most observed patterns of recent Arctic surface warming and sea ice loss lie outside of unforced internal climate variability. In contrast, human influence on related changes in outgoing longwave radiation has not been assessed. Outgoing longwave radiation captures the flow of thermal energy from the surface through the atmosphere to space, making it an essential indicator of Arctic change. Furthermore, satellites have measured pan-Arctic radiation for two decades while surface temperature observations remain spatially and temporally sparse. Here, two climate model initial-condition large ensembles and satellite observations are used to investigate when and why twenty-first-century Arctic outgoing longwave radiation changes emerge from unforced internal climate variability. Observationally, outgoing longwave radiation changes from 2001 to 2021 are within the range of unforced internal variability for all months except October. The model-predicted timing of Arctic longwave radiation emergence varies throughout the year. Specifically, fall emergence occurs a decade earlier than spring emergence. These large emergence timing differences result from seasonally dependent sea ice loss and surface warming. The atmosphere and clouds then widen these seasonal differences by delaying emergence more in the spring and winter than in the fall. Finally, comparison of the two ensembles shows that more sea ice and a more transparent atmosphere during the melt season led to an earlier emergence of forced longwave radiation changes. Overall, these findings demonstrate that attributing changes in Arctic outgoing longwave radiation to human influence requires understanding the seasonality of both forced change and internal climate variability.

Impacts of Atlantic water intrusion on interannual variability of the phytoplankton community structure in the summer season of Kongsfjorden, Svalbard under rapid Arctic change

Atlantification, known as impacts of high-latitude Atlantic water inflows on the Arctic Ocean has strengthened owing to climate change, corresponding to the rapid ice retreat in the Arctic. The relationship between phytoplankton and environmental changes in the Arctic on the interannual scale is unclear because of the lack of long-time series data. In this study, we discuss the ecological response to Atlantic water intrusion in the Kongsfjorden,Svalbard. We measured chlorophyll a and photosynthesis pigments for the water column samples from a fixed section along the Kongsfjorden to study the response of phytoplankton biomass and communities to Atlantic water intrusion in the summer season from 2007 to 2018. The results showed that dinoflagellates, prasinophytes, cryptophytes, and chlorophytes consistently accounted for over 50% of the total biomass, with the distinct annual variation of chlorophyll a. Bioavailable nitrogen was the main limiting factor on phytoplankton growth in the study area, as inferred by its concentration and nutrients ratios. The relationship between phytoplankton and water mass analysis suggested that the intrusion of Atlantic water in Kongsfjorden may cause interannual variability of the phytoplankton biomass and community structure by influencing the nutrient supply and water stratification in the fjord region. Our study provides insights into the ongoing impact of Atlantification on the phytoplankton community in the Arctic fjord.

Recent trends in the chemistry of major northern rivers signal widespread Arctic change

Recent trends in the chemistry of major northern rivers signal widespread Arctic change

Reducing uncertainty of high-latitude ecosystem models through identification of key parameters

Climate change is having significant impacts on Earth’s ecosystems and carbon budgets, and in the Arctic may drive a shift from an historic carbon sink to a source. Large uncertainties in terrestrial biosphere models (TBMs) used to forecast Arctic changes demonstrate the challenges of determining the timing and extent of this possible switch. This spread in model predictions can limit the ability of TBMs to guide management and policy decisions. One of the most influential sources of model uncertainty is model parameterization. Parameter uncertainty results in part from a mismatch between available data in databases and model needs. We identify that mismatch for three TBMs, DVM-DOS-TEM, SIPNET and ED2, and four databases with information on Arctic and boreal above- and belowground traits that may be applied to model parametrization. However, focusing solely on such data gaps can introduce biases towards simple models and ignores structural model uncertainty, another main source for model uncertainty. Therefore, we develop a causal loop diagram (CLD) of the Arctic and boreal ecosystem that includes unquantified, and thus unmodeled, processes. We map model parameters to processes in the CLD and assess parameter vulnerability via the internal network structure. One important substructure, feed forward loops (FFLs), describe processes that are linked both directly and indirectly. When the model parameters are data-informed, these indirect processes might be implicitly included in the model, but if not, they have the potential to introduce significant model uncertainty. We find that the parameters describing the impact of local temperature on microbial activity are associated with a particularly high number of FFLs but are not constrained well by existing data. By employing ecological models of varying complexity, databases, and network methods, we identify the key parameters responsible for limited model accuracy. They should be prioritized for future data sampling to reduce model uncertainty.

Nunaaqqit Savaqatigivlugich—working with communities: evolving collaborations around an Alaska Arctic observatory and knowledge hub

Indigenous Peoples across the Arctic have adapted to environmental change since time immemorial, yet recent climate change has imposed unprecedented and abrupt changes that affect the land and sea upon which communities rely. Co-created community-based observing programs offer an opportunity to harness the holistic breadth of knowledge in communities with the goal of tracking Arctic change while simultaneously supporting community priorities and local-scale needs. The Alaska Arctic Observatory and Knowledge Hub (AAOKH) is a network of Iñupiaq observers from northern Alaska coastal communities working in partnership with academic researchers. Here, we describe five core functions that have emerged through AAOKH, which include tracking long-term environmental changes; communicating Indigenous-led observations of the environment and their meaning; place-based and culturally relevant education; enabling scientific and Indigenous Knowledge exchange; and supporting community-led responses to environmental change. We outline and discuss specific actions and opportunities that have been used to increase knowledge exchange of AAOKH observations, make space for the next generation of Indigenous scholars, and create locally relevant data products and syntheses that can inform resource management and community planning. We also discuss our ongoing efforts to increasingly shift toward a knowledge coproduction framework as we plan to sustain AAOKH into the future.

Bowhead whale year-round acoustic presence and habitat associations in the Amundsen Gulf, Western Canadian Arctic, 2018–2019

Understanding the temporal and spatial distribution of bowhead whales is ecologically and culturally important in the context of a rapidly changing climate. Long-term monitoring can reveal alterations in the bowhead whale distribution range, spatiotemporal patterns, and migration phenology that can be responses to global change. However, Arctic ecosystems are challenging to monitor. Here, we deployed passive acoustic recorders at three locations in the southern Amundsen Gulf (western Canadian Arctic) between September 2018 and September 2019 to detect bowhead whale presence, quantify their seasonal occurrence, and examine the oceanographic conditions that correlate with bowhead occurrence. Results show clear seasonal patterns in the occurrence of bowheads with increased acoustic presence in spring/summer at all sites. In contrast to their typical migratory behavior, bowhead sounds were detected throughout the year at all sites, providing evidence of a number of overwintering animals in what is normally their summer feeding ground. The continuous occupancy of bowheads from May to August at all sites emphasizes the importance of this area as a core foraging ground for this population. Our results indicate a clear selection for the shallowest habitat over an annual cycle. Statistical habitat modeling indicated associations between bowhead occurrence and decreasing sea-ice coverage, wind speed, temperature, and salinity. Positive relationships between bowhead detections and zooplankton density suggest a predator-prey dynamic. These results are the first that cover an entire annual cycle of bowhead presence in the southern Amundsen Gulf, providing new knowledge and current status of bowhead habitat use to support effective management under ongoing Arctic change.

The Alaska Blocking Index, version 2: Analysis and covariability with statewide and large‐scale climate from 1948 to 2020

AbstractMonitoring and quantifying high‐latitude atmospheric circulation variability and trends are important towards understanding the anatomy of extreme events and constraining their probabilities under continued Arctic change. The greater Alaska region stands out as one region of enhanced warming and environmental changes over the Arctic amplification era, which has shown proclivity to extreme events and speaks to the need to consistently monitor overlying atmospheric variability. In this paper, we describe the creation and analysis of an updated, daily mid‐tropospheric Alaska Blocking Index (ABI) time series from 1948 to 2020. Sensitivity testing and index modifications from the initial dataset are discussed, and the new ABI is evaluated over the full period and subperiods. Additionally, we assess the role of the ABI as a regional climate indicator by analysing its variability against surface air temperature and precipitation from 13 climate divisions across Alaska as well as broader‐scale hemispheric temperatures. Months of the highest ABI means mainly transpired in the most recent climatological period, 1991–2020, and most notably during the spring and autumn transition seasons, reflecting the nonstationary nature of the jet stream magnitude through time atop Alaska. ABI trends are positive across all months, seasons, and annually only in the 1991–2020 period. Contemporaneous ABI values are strongly and positively correlated with air temperature across all Alaskan climate divisions during the warm season, but negatively correlated with winter temperatures over southeastern Alaska. Meanwhile, the ABI is significantly anticorrelated with summer precipitation over Interior and southern Alaska, but only over southeastern Alaska in other seasons. The ABI is statistically differentiated from the primary modes of atmospheric variability as shown by its generally weak correlations with the Arctic Dipole and the Arctic Oscillation (r ≤ 0.40).

Circum-Arctic release of terrestrial carbon varies between regions and sources

Arctic change is expected to destabilize terrestrial carbon (terrOC) in soils and permafrost, leading to fluvial release, greenhouse gas emission and climate feedback. However, landscape heterogeneity and location-specific observations complicate large-scale assessments of terrOC mobilization. Here we reveal differences in terrOC release, deduced from the Circum-Arctic Sediment Carbon Database (CASCADE) using source-diagnostic (δ13C-Δ14C) and carbon accumulation data. The results show five-times larger terrOC release from the Eurasian than from the American Arctic. Most of the circum-Arctic terrOC originates from near-surface soils (61%); 30% stems from Pleistocene-age permafrost. TerrOC translocation, relative to land-based terrOC stocks, varies by a factor of five between circum-Arctic regions. Shelf seas with higher relative terrOC translocation follow the spatial pattern of recent Arctic warming, while such with lower translocation reflect long-distance lateral transport with efficient remineralization of terrOC. This study provides a receptor-based perspective for how terrOC release varies across the circum-Arctic.

Integrated airborne investigation of the air composition over the Russian sector of the Arctic

Abstract. The change of the global climate is most pronounced in the Arctic, where the air temperature increases 2 to 3 times faster than the global average. This process is associated with an increase in the concentration of greenhouse gases in the atmosphere. There are publications predicting the sharp increase in methane emissions into the atmosphere due to permafrost thawing. Therefore, it is important to study how the air composition in the Arctic changes in the changing climate. In the Russian sector of the Arctic, the air composition was measured only in the surface atmospheric layer at the coastal stations or earlier at the drifting stations. Vertical distributions of gas constituents of the atmosphere and aerosol were determined only in a few small regions. That is why the integrated experiment was carried out to measure the composition of the troposphere in the entire Russian sector of the Arctic from on board the Optik Tu-134 aircraft laboratory in the period of ​​​​​​​4 to 17 September of 2020. The aircraft laboratory was equipped with contact and remote measurement facilities. The contact facilities were capable of measuring the concentrations of CO2, CH4, O3, CO, NOx​​​​​​​, and SO2, as well as the disperse composition of particles in the size range from 3 nm to 32 µm, black carbon, and organic and inorganic components of atmospheric aerosol. The remote facilities were operated to measure the water transparency in the upper layer of the ocean, the chlorophyll content in water, and spectral characteristics of the underlying surface. The measured data have shown that the ocean continues absorbing CO2. This process is most intense over the Barents and Kara seas. The recorded methane concentration was increased over all the Arctic seas, reaching 2090 ppb in the near-water layer over the Kara Sea. The contents of other gas components and black carbon were close to the background level. In bioaerosol, bacteria predominated among the identified microorganisms. In most samples, they were represented by coccal forms, less often spore-forming and non-spore-bearing rod-shaped bacteria. No dependence of the representation of various bacterial genera on the height and the sampling site was revealed. The most turbid during the experiment was the upper layer of the Chukchi and Bering seas. The Barents Sea turned out to be the most transparent. The differences in extinction varied by more than a factor of 1.5. In all measurements, except for the Barents Sea, the tendency of an increase in chlorophyll fluorescence in more transparent waters was observed.

Comparison of Pond Depth and Ice Thickness Retrieval Algorithms for Summer Arctic Sea Ice

In order to satisfy the demand of key sea ice parameters, including melt pond depth Hp and underlying ice thickness Hi, in studies of Arctic sea ice change in summer, four algorithms of retrieving Hp and Hi were compared and validated by using optical data of melt ponds from field observations. The Malinka18 algorithm stood out as the most accurate algorithm for the retrieval of Hp. For the retrieval of Hi, Malinka18 and Zhang21 algorithms could also provide reasonable results and both can be applied under clear and overcast sky conditions, while retrievals under clear sky conditions are more accurate. The retrieval results of Hi for Lu18 agreed better with field measurements for thin ice (Hi < 1 m) than that for thick ice, but those results of Hp were not satisfactory. The König20 algorithm was only suitable for clear sky conditions, and underestimated Hp, while showing a good agreement with Hp < 0.15 m. For Arctic applications, Malinka18 and Zhang21 algorithms provided a basis and reference for the satellite optical data such as WoeldView2 to retrieve Hp and Hi. Malimka18 also showed the ability to retrieve Hi, except for the Lu18 algorithm if pond color captured by helicopters and unmanned aerial vehicles were available. This study identifies the optimal algorithm for retrieval of Hp and Hi under different conditions, which have the potential to provide necessary data for numerical simulations of Arctic sea ice changes in summer.

Change in Climate Sensitivity and Its Dependence on the Lapse-Rate Feedback in 4 × CO2 Climate Model Experiments

Abstract Robust estimates of climate sensitivity are important for decision-making on mitigation of climate change. However, climate sensitivity and its governing processes are still subject to large uncertainty. Recently it has been established that climate sensitivity changes over time in numerical climate model experiments with abrupt quadrupling of the CO2 concentration. Here we conduct an analysis of such experiments from a range of climate models from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP). Climate feedbacks associated with clouds, lapse rate, Planck radiation, surface albedo, and water vapor and their changes over time are diagnosed based on a radiative kernel method. We find two clearly distinct model groups, one with weak and one with strong lapse-rate feedback change. The Arctic is the region showing the largest differences between these two model groups, with respect to both warming change and individual feedback changes. We retrace this change to the development over time of the Arctic sea ice, which impacts both the surface-albedo and lapse-rate feedbacks. Generally, models that warm quickly, both globally and in the Arctic, also quickly lose their Arctic sea ice and change their total global-mean climate feedback only little, and vice versa. However, it remains unclear if the Arctic changes are a cause or rather a by-product of the total global-mean feedback change. Finally, we find support for the results of previous studies finding that the relative warming in the tropical Indo-Pacific region may control the change of total climate feedback over time.

Sources and Fate of Organic Carbon in West Spitsbergen Fjord Systems: A Review

Abstract Fjord margins in the high latitude regions are the hotspots for long term carbon burial. Studying the source and fate of organic carbon in high latitude fjords would help assess the sedimentary processes and burial. With the unprecedented warming, the marine productivity patterns are changing, leading to changes in the sources of organic carbon and its eventual burial in marine sediments. In the present study, high latitude fjords in the West Spitsbergen region has been reviewed, subjected to competing effects of large freshwater influx from the glacial melts, enhanced West Spitsbergen Current and its control on marine productivity. The West Spitsbergen Current advects warm North Atlantic waters enriched in nutrients to the fjords in the West Spitsbergen region. The increased freshwater from the glacial melts also dominates the fjords. Thus, the composition of organic matter in the fjord is mainly controlled by the inflow of freshwater from the glaciers and intrusion of oceanic waters to the fjords influencing the organic matter stability and carbon burial efficiency in the fjord sediments. The ongoing rapid warming in the Arctic changes the hydrographic settings, and changes in the strength of West Spitsbergen Current may also influence the long-term organic carbon burial in the West Spitsbergen fjords.

Regional sensitivity patterns of Arctic Ocean acidification revealed with machine learning

Ocean acidification is a consequence of the absorption of anthropogenic carbon emissions and it profoundly impacts marine life. Arctic regions are particularly vulnerable to rapid pH changes due to low ocean buffering capacities and high stratification. Here, an unsupervised machine learning methodology is applied to simulations of surface Arctic acidification from two state-of-the-art coupled climate models. We identify four sub-regions whose boundaries are influenced by present-day and projected sea ice patterns. The regional boundaries are consistent between the models and across lower (SSP2-4.5) and higher (SSP5-8.5) carbon emissions scenarios. Stronger trends toward corrosive surface waters in the central Arctic Ocean are driven by early summer warming in regions of annual ice cover and late summer freshening in regions of perennial ice cover. Sea surface salinity and total alkalinity reductions dominate the Arctic pH changes, highlighting the importance of objective sub-regional identification and subsequent analysis of surface water mass properties.

Coastal marine biodiversity in the western Canadian Arctic

Establishing a baseline of Arctic marine biodiversity is necessary for monitoring impacts of climate change in the vulnerable Canadian Arctic and protecting sensitive regions that are of significant importance to Inuit culture and socioeconomics. Under the goals of improving documentation of Arctic marine communities and creating a tool for assessing coastal Arctic biodiversity across different regions, relative abundance data of fishes, benthic invertebrates, and prey items found in fish stomach contents from coastal areas near Paulatuk and Sachs Harbour, Northwest Territories, and Kugluktuk, Nunavut were used to calculate Shannon–Wiener Biodiversity Indices. Biodiversity varied among and within regions and trophic groups; fish and stomach content biodiversity were highest in Kugluktuk, whereas benthic biodiversity was highest near Paulatuk. The methods presented here can be used as a tool for assessing low- to mid-trophic Canadian Arctic coastal biodiversity and would also facilitate spatial comparisons and long-term monitoring as climate warming impacts Arctic ecosystems.