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The cloud feedback may result in amplification or damping of Arctic warming. Two common techniques used to diagnose the top‐of‐the‐atmosphere cloud feedback are the Adjusted Cloud Radiative Effect (AdjCRE) method and the Cloud Radiative Kernel (CRK) method. We apply both to CMIP5 and CMIP6 model data, finding that the AdjCRE calculated Arctic shortwave cloud feedback is twice as correlated with sea ice loss in CMIP5, and four times in CMIP6, as the CRK method. We find that the CRK method produces Arctic all‐sky residual percentages exceeding 20% in 15 of 18 models. We use the CRK method to decompose the feedback in CMIP5 and CMIP6 finding that its median value changed from negative to positive driven by a less‐negative cloud optical depth feedback. Despite its lack of closure, we conclude that the CRK method is better suited for Arctic SW feedbacks as it is less impacted by surface albedo changes. Plain Language Summary: The cloud feedback is the process by which cloud property changes in a warming climate can either further enhance warming or damp it. The Arctic is warming faster than the rest of the globe, and one of the largest sources of uncertainty in its climate projections is the cloud feedback. There are two popular methods to calculate the cloud feedback: the Adjusted Cloud Radiative Effect technique, and the Cloud Radiative Kernel technique. In this paper we compare the two methods in a suite of climate models by considering the extent to which changes in Arctic sea ice impact the cloud feedbacks. From this analysis we conclude that the Cloud Radiative Kernel method is less affected by sea ice loss. We then apply the Cloud Radiative Kernel technique to data from the two most recent generations of global climate models to investigate how polar day Arctic cloud feedbacks have changed between these generations. We find that the median value of these Arctic feedbacks is slightly positive in the newest generation of models, a change from slightly negative in the previous generation that is largely fueled by a weakening of the feedback associated with changes in cloud optical depth. Key Points: The Cloud Radiative Kernel method is less sensitive to surface albedo changes than the Adjusted Cloud Radiative Effect techniqueThe Cloud Radiative Kernel method provides poor radiative closure in a suite of global climate modelsThe median shortwave Arctic cloud feedback in recent climate models is slightly positive due to a weakened cloud optical depth feedback [ABSTRACT FROM AUTHOR]

Arctic Ocean freshwater storage increased since the mid‐1990s, but the cause was unknown. Jahn and Laiho (2020, https://doi.org/10.1029/2020GL088854) use ensemble runs of a coupled climate model to suggest that the observed increase is anthropogenic. The paper quantifies when the anthropogenic signals should emerge from the noise of natural variability. This result contextualizes research on the Arctic Ocean freshwater system and sketches an unprecedented opportunity. Future work should elucidate mechanisms, seek to observe the anthropogenic freshwater changes, and investigate the impacts on biogeochemistry and the North Atlantic Ocean circulation. Plain Language Summary: The Arctic is a region of clear man‐made climate change. Changes in the Arctic Ocean salinity and currents have been seen, but the cause was unknown. A new paper shows that the changes are probably due to man‐made climate change. The reason is they only occur in a climate model with man‐made climate forcing. This is an important result because it helps scientists focus their research into how the changes work. It also points to a valuable opportunity to watch the Arctic Ocean respond to man‐made climate change. There might be important future impacts on North Atlantic oceanography and North Atlantic climate that scientists can now look for. Key Points: A recent paper shows that observed increases in Arctic Ocean freshwater storage are anthropogenicThe paper anticipates future anthropogenic changes, which are testable predictions for observersThere are widespread impacts of anthropogenic freshwater change, both within the Arctic and the North Atlantic Oceans [ABSTRACT FROM AUTHOR]

Surface, aircraft, and satellite measurements indicate pervasive early cold season (Augut–September) CO2 emissions across Arctic regions, consistent with increased ecosystem metabolism in plants and soils. A key remaining question is whether cold season sources will become large enough to permanently shift the Arctic into a net carbon source. Polar orbiting GHG satellites provide robust estimation of regional carbon budgets but lack sufficient spatial coverage and repeat frequency to track sink‐to‐source transitions in the early cold season. Mission concepts such as the Arctic Observing Mission (AOM) advocate for flying imaging spectrometers in highly elliptical orbits (HEO) over the Arctic to address sampling limitations. We perform retrieval and flux inversion simulation experiments using the AURORA mission concept, leveraging a Panchromatic imaging Fourier Transform Spectrometer (PanFTS) in HEO. Our simulations demonstrate the potential benefits of increased CO2 sampling for detecting emissions during the early cold season. Plain Language Summary: The Arctic is warming rapidly, leading to an acceleration of carbon exchange across tundra and boreal ecosystems. These changing flows of carbon can be difficult to detect using traditional observing systems. We propose that measurement systems which observe Arctic ecosystems continuously from a quasi‐GEO orbit can more accurately detect these important changes, such that unexpected and dangerous feedbacks to climate warming can be monitored and accounted for. Key Points: The Arctic Fourier Transform Spectrometer Investigation (AURORA) mission concept addresses GHG sampling limitations in the ArcticAURORA uses a highly elliptical orbit (HEO) to increase repeat frequency, and a panchromatic iFTS for SWIR O2 and CO2 bands (0.7–2.5 μm)Simulation experiments show potential benefits of increased sampling frequency for grid scale detection of early cold season CO2 emissions [ABSTRACT FROM AUTHOR]

In a rapidly changing Arctic, multiple lines of evidence suggest that bowhead whale migration is changing. To explore these changes further, we used passive acoustic data to examine bowhead whale presence in the western Beaufort Sea (12 years) and Chukchi Plateau (11 years) spanning 2008 to 2022. Departure from the western Beaufort Sea shifted 45 days later over the 12‐year period. Summer presence increased at both sites, suggesting feeding areas within the Chukchi Sea are becoming more favorable. Likewise, findings from the Bering Strait suggest that some whales are remaining north of the Bering Strait for the winter instead of in the Bering Sea. These Pacific Arctic‐wide changes to migration have occurred over only one decade. Questions remain about prey availability in the Chukchi Sea, implications of migratory changes, such as a northward shift in the core overwintering area, and impact to communities south of the Bering Strait. Plain Language Summary: Bowhead whales are an important top predator in the Pacific Arctic. With increasing temperatures and decreasing sea ice, changes are occurring in the migration patterns of this "ecosystem sentinel" throughout the Pacific Arctic. We analyzed passive acoustic data from the western Beaufort Sea and Chukchi Plateau from 2008 to 2022. Whales are delaying their fall departure from the western Beaufort Sea and spending more time in the western Beaufort Sea and Chukchi Plateau, which, along with increased habitat use on the Chukchi Shelf, suggests that conditions there are becoming more favorable for feeding. Combined with previous data from the Bering Strait, which showed that some whales are spending winter in the southern Chukchi Sea rather than in the northern Bering Sea, these findings suggests that changes are occurring over a short period of time throughout the Pacific Arctic. A northward shift could put bowhead whales in the direct path of ships, especially along the western side of the Chukchi Sea, and impact whaling communities south of the Bering Strait. Key Points: Acoustic data reinforce known delay in bowhead fall departure from the western Beaufort Sea and overwintering in the southern Chukchi SeaIncreased presence in the western Beaufort Sea and Chukchi Plateau suggests these regions are becoming more favorable for bowhead feedingWhales are adapting to a rapidly changing Arctic, but changes and emerging threats may impact them and communities south of Bering Strait [ABSTRACT FROM AUTHOR]

Despite multiple advances in the understanding of the water cycle intensification in a warmer climate, climate models still diverge in their hydrological projections. Here we constrain annual runoff projections over individual and aggregated Arctic river basins. For this purpose, we use two ensembles of global climate models and two statistical methods: a regression scheme assuming similar runoff sensitivities at interannual versus climate change timescales, and a Bayesian method where models are used to derive a posterior runoff response conditioned on historical observations. While both techniques are shown to narrow model uncertainties, more or less substantially depending on rivers, the Bayesian method is less sensitive to the choice of the model ensemble and is more skillful when tested with synthetic observations. It has also been applied over the whole Arctic watershed, showing so far a limited narrowing of the inter‐model spread, but its skill will further improve with increasing climate change. Plain Language Summary: Despite considerable progress in understanding the intensification of the water cycle in response to global warming, projections of changes in the various components of the continental water balance remain highly model‐dependent. This is particularly the case for the evolution of runoff, which remains very sensitive to the way atmospheric and continental processes are represented. Here we evaluate and compare two statistical methods to constrain climate projections of annual runoff at high latitudes via available or synthetic observations. Our Bayesian method, based on historical observations, is found to be more robust than a previous method based on observed interannual climate variability. It underlines the importance of having reliable flow reconstructions to constrain runoff projections and of using empirical observational constraints with caution, as they are likely to lead to over‐confident projections. Key Points: Runoff sensitivity to temperature depends on the considered timescaleObservational constraints based on interannual variability can thus lead to overconfident projectionsObservational constraints based on historical trends can be effective if such trends are driven by human emissions of greenhouse gasses [ABSTRACT FROM AUTHOR]

While the annual mean Arctic Amplification (AA) index varied between two and three during the 1970–2000 period, it reached values exceeding four during the first two decades of the 21st century. The AA did not change in a continuous fashion but rather in two sharp increases around 1986 and 1999. During those steps the mean global surface air temperature trend remained almost constant, while the Arctic trend increased. Although the "best" CMIP6 models reproduce the increasing trend of the AA in 1980s they do not capture the sharply increasing trend of the AA after 1999 including its rapid step‐like increase. We propose that the first sharp AA increase around 1986 is due to external forcing, while the second step close to 1999 is due to internal climate variability, which models cannot reproduce in the observed time. Plain Language Summary: The rate of Arctic warming varied in time, while the rate of global warming was nearly constant over the period 1960–2020. This led to a variable Arctic Amplification (AA) defined as a ratio of the Arctic warming trend to mean global warming trend. In addition, the Arctic experienced sudden changes in the rate of warming with step‐like changes in annual mean Arctic Amplification around the years 1986 and 1999. Climate models do not capture the second observed sharp increase of the AA. We suggest that the first AA increase around 1986 is primarily due to external forcing (increasing concentration of carbon dioxide) while the second sharp increase around 1999 is dominated by internal climate variability which current models cannot capture accurately within the time scale of the physical phenomena. Key Points: Annual mean Arctic Amplification (AA) within the period 1970–2020 changed in steep steps around 1986 and 1999. It reached values over 4.0Even those CMIP6 models best at reproducing the AA did not reproduce the second sudden increase near 1999We conjecture that the first AA sharp increase is due to external forcing, while the second is due to internal climate variability [ABSTRACT FROM AUTHOR]

Arctic sea ice has substantially changed over the past four decades, with a large decrease in sea‐ice area and volume. The exact causes of these changes are not entirely known. In our study, we make use of the Swedish Meteorological and Hydrological Institute Large Ensemble. This ensemble consists of 50 members realized with the EC‐Earth3 global climate model and covers the period 1970‐2100. We apply for the first time the Liang‐Kleeman information flow method to analyze the cause‐effect relationships between Arctic sea ice and its potential drivers. We show that recent and future changes in Arctic sea ice are mainly driven by air and sea‐surface temperatures and ocean heat transport. Conversely, changes in Arctic sea ice also considerably impact temperature and ocean heat transport. Finally, we find a progressive decrease in the influence of sea‐ice area and volume on air temperature and ocean heat transport through the twenty‐first century. Plain Language Summary: The Arctic has been warming at a larger rate than the rest of the world, resulting in a substantial loss of sea ice since the late 1970s. This has had and will continue to have an impact on our climate and societies. The exact causes of the ongoing sea‐ice loss are not entirely known, and understanding them is important in order to better prepare our societies for future climate changes. In our study, we apply a relatively novel approach that quantifies the cause‐effect relationships between Arctic sea ice and its potential drivers. We make use of a large range of model simulations performed with the EC‐Earth3 global climate model covering the period 1970‐2100. We find that air temperature, sea‐surface temperature, and the transport of heat by the ocean are important drivers of the ongoing and future retreat of Arctic sea ice. Conversely, changes in Arctic sea ice also affect the three former quantities. Our study demonstrates the performance of causal inference methods in the quest for a better understanding of relationships between climate variables. The geophysical and climate communities could greatly benefit from using these methods more intensively. Key Points: The Liang‐Kleeman rate of information transfer allows quantification of the directional dependence between Arctic sea ice and its driversRecent and future changes in Arctic sea ice are mainly driven by air and sea‐surface temperatures and ocean heat transportThe influence of Arctic sea ice on air temperature and ocean heat transport progressively decreases through the twenty‐first century [ABSTRACT FROM AUTHOR]

Recent satellite observations confirm that the Arctic is absorbing more solar radiation now than at the start of this century in response to declining Arctic sea ice and snow covers. Trends in the solar radiation input to Arctic ocean and land surfaces now each exceed interannual variability at the 95% confidence level, although all‐sky trends have taken 20%–40% longer to emerge compared to clear‐sky conditions. Clouds reduce mean solar absorption and secular trends over both land and ocean, but the effect of clouds on natural variability depends on the underlying surface. While clouds increase the time needed to unambiguously identify trends in nearly all Arctic regions, their masking effects are strongest over oceans. Clouds have extended the time to emergence of already observed clear‐sky trends beyond the existing 21 years Clouds and Earth's Radiant Energy System record in half of eight Arctic seas, supporting the need for continued satellite‐based radiative flux observations over the Arctic. Plain Language Summary: The Arctic has been rapidly changing in response to rising greenhouse gases, including dramatic sea ice loss. Sea ice is bright and reflects most sunlight that hits it, so when it melts more sunlight is absorbed at the surface, leading to more surface melting or warming. However, when viewed from satellites in space, it can be difficult to distinguish between bright clouds and the bright surface. Because clouds also reflect a large amount of incoming sunlight, they reduce the amount of sunlight that reaches the surface. Without clouds, far more sunlight would have been absorbed into the Arctic over the last two decades. The presence of clouds has also made it more difficult to observe how the amount of sunlight being absorbed is changing. Nevertheless, the Arctic has been evolving so quickly that even with the masking effect of clouds we can measure trends in absorbed sunlight using 20 years of satellite observations, a relatively short amount of time compared to most other climate changes. Key Points: Significantly more solar radiation is being absorbed into the Arctic now than at the turn of the centuryClouds increase the time needed to detect trends in solar absorptionClouds exert the largest masking effect over oceans and areas with the greatest sea ice loss [ABSTRACT FROM AUTHOR]

State‐of‐the‐art climate models simulate a large spread in the projected decline of Arctic sea‐ice area (SIA) over the 21st century. Here we diagnose causes of this intermodel spread using a simple model that approximates future SIA based on present SIA and the sensitivity of SIA to Arctic temperatures. This model accounts for 70%–95% of the intermodel variance, with the majority of the spread arising from present‐day biases. The remaining spread arises from intermodel differences in Arctic warming, with some contribution from differences in the local sea‐ice sensitivity. Using observations to constrain the projections moves the probability of an ice‐free Arctic forward by 10–35 years when compared to unconstrained projections. Under a high‐emissions scenario, an ice‐free Arctic will likely (>66% probability) occur between 2036 and 2056 in September and between 2050 and 2068 from July to October. Under a medium‐emissions scenario, the "likely" date occurs between 2040 and 2062 in September and much later in the 21st century from July to October. Plain Language Summary: Arctic sea ice coverage has declined substantially over the past few decades and is projected to continue to decline over the next century. These projections, however, are marred by large uncertainties which arise primarily due to differences between climate models. In this study, we use a simple model that emulates the future evolution of Arctic sea ice as simulated by climate models to explain where this uncertainty comes from. We show that biases in simulating present‐day Arctic sea ice contribute most of the uncertainty, with differences in the simulated amount of Arctic warming from climate models contributing much of the rest. We use observations to constrain our simple model and show that under a high emissions scenario it is likely the Arctic will be free of sea ice in September sometime between 2036 and 2056 and from July to October sometime between 2050 and 2068. We also show that the emissions pathway impacts the length of ice free summers in the Arctic, indicating a low‐emissions pathway will reduce the likelihood of seeing ice‐free Arctic summers. Key Points: A model relating future sea‐ice area (SIA) to present SIA and local sea‐ice sensitivity is used to explain the intermodel spread in Arctic SIA projectionsBiases in simulating present‐day SIA contribute most to the spread, with model differences in Arctic warming contributing the restUnder a high‐emissions scenario, the Arctic will likely be ice‐free in September between 2036 and 2056 and from July to October between 2050 and 2068 [ABSTRACT FROM AUTHOR]

Climate change is projected to cause the Arctic soundscape to become noisier due to sea ice loss and increased anthropogenic activity. Many studies on underwater sound levels have been conducted in the western North American Arctic and Fram Strait, but the rest of the Arctic is full of geographic gaps. Han et al. (2021, https://doi.org/10.1029/2021gl093097) published a study in Geophysical Research Letters on underwater sound levels in the East Siberian Sea, providing the first estimates of seasonal trends and the natural and anthropogenic drivers of underwater sound levels in this region. This is an excellent first step in filling geographic gaps in the Russian Arctic, and I call on other researchers to continue to fill these geographic gaps throughout the Arctic so that we can set a baseline and study changes to underwater sound levels being caused directly and indirectly by climate change. Plain Language Summary: The Arctic marine environment can be one of the quietest on Earth, particularly under solid sea ice. Climate change is causing sea ice to melt at an alarming rate and is also allowing increased human shipping activity. Both sea ice loss and increased shipping activity will likely lead to a noisier environment underwater in the Arctic. Many studies have examined how loud the underwater environment is in the Arctic of western North America and between East Greenland and Svalbard, but there are many areas throughout the Arctic with no studies. Han et al. (2021, https://doi.org/10.1029/2021gl093097) just published the first study on the loudness of the underwater environment in the East Siberian Sea. This study fills an important gap in our knowledge, and I call on other researchers to continue expanding studies into areas of the Arctic where we have no data on underwater sound levels. More studies will help us track the changes in underwater sound levels being caused by climate change. Key Points: Han et al. (2021) published a study in Geophysical Research Letters on underwater sound levels in the East Siberian SeaI place this study in the context of broader effort to establish baselines of underwater sound levels in the ArcticI call on researchers to continue filling geographic gaps in studies of underwater sound levels, particularly in the Russian Arctic [ABSTRACT FROM AUTHOR]

Given uncertainty in the processes involved in polar amplification, elucidating the role of poleward heat and moisture transport is crucial. The Polar Amplification Model Intercomparison Project (PAMIP) permits robust separation of the effects of sea ice loss from sea surface warming under climate change. We utilize a moist isentropic circulation framework that accounts for moisture transport, condensation, and eddy transport, in order to analyze the circulation connecting the mid‐latitudes and the Arctic. In PAMIP's atmospheric general circulation model experiments, prescribed sea ice loss reduces poleward heat transport (PHT) by warming the returning moist isentropic circulation at high latitudes, while prescribed warming of the ocean surface increases PHT by strengthening the moist isentropic circulation. Inter‐model spread of PHT into the Arctic reflects the tug‐of‐war between sea‐ice and surface‐warming effects. Plain Language Summary: A major conundrum in current climate science is to understand what Arctic changes imply for the climate and environment in mid‐latitude regions. The Polar Amplification Model Intercomparison Project (PAMIP) designed a set of climate model experiments to specifically answer this question in a carefully designed, idealized framework. PAMIP's approach is to separate historic and projected climate change into parts associated with Arctic sea ice loss and ocean surface warming and investigate how these two contributions can influence the atmosphere. To isolate these effects, only models can be used, because, in reality, sea ice loss and ocean surface warming are strongly linked together. This letter focuses on what the PAMIP experiments imply for the transport and redistribution of heat and moisture in the atmosphere. In PAMIP, we learn that Arctic sea ice loss causes the atmosphere to reduce the transport of dry and cold air away from the Arctic while ocean warming causes more transport of moist warm air toward the Arctic. These two effects are in a tug‐of‐war, suggesting that climate change can cause a mix of competing impacts on the global energy transport from the tropics to the Arctic. Key Points: Sea ice loss exports static energy from the Arctic by warming the equatorward branch of the global mass circulationSea surface warming imports static energy into the Arctic by increasing the mid‐latitude mass transport, overwhelming the sea ice effectThere is more spread amongst models for the effect of sea‐surface warming than for sea ice loss [ABSTRACT FROM AUTHOR]

Arctic summer temperatures mostly cooled over the last ~7 kyr, owing to decreasing summer insolation. However, knowledge of the winter season is limited in the Arctic paleoclimate literature. Here we develop a composite record of δ18O from ice wedges—a winter precipitation archive—to reconstruct changes in winter climate in the northwestern Canadian Arctic since ~7.4 kyr b2k. Our record shows a long‐term δ18O enrichment (+(0.14 ± 0.10)‰ kyr−1), suggesting winter temperatures increased since the mid‐Holocene, a finding that is corroborated by reconstructions from the Siberian Arctic. Winter warming over the last ~7 kyr is consistent with increasing winter insolation and greenhouse gas forcing. This study provides some of the first insights on the sensitivity of winter temperatures in the Canadian Arctic to past, and potentially future, climate forcings, and contributes to a more seasonally holistic understanding of the Arctic system. Plain Language Summary: The history of climate change during the last 11,700 years, a period known as the Holocene Epoch, has been traditionally studied using natural climate proxies such as tree rings or pollen in the sedimentary record. Such records allow us to better understand past climate variability in response to changing greenhouse gas concentrations, solar radiation, and other boundary conditions. However, most traditional climate proxies are biological and sensitive mainly to growing‐season conditions, whereas changes in cold‐season conditions are not well described in the literature. This is especially true in the Arctic where recent climate warming has been most pronounced in the winter season, but few cold‐season‐specific proxy records are available. In this study, we develop a ~7,400‐year record of the δ18O isotope composition of relict ice wedges in the northwestern Canadian Arctic, a proxy type that is specifically sensitive to cold‐season conditions. We observe a long‐term increase in ice‐wedge δ18O over the past ~7,400 years, indicating warming winter temperatures since the mid‐Holocene. This warming corresponds to increasing winter solar radiation and greenhouse gas concentrations and is in agreement with recent reports from ice wedges in the Siberian Arctic. Key Points: Ice‐wedge δ18O reveals an enrichment trend over the last ~7.4 kyrThe enrichment reflects a long‐term winter warming trend, coinciding with increasing winter insolation and greenhouse gas forcingThis record provides key insights on winter Holocene climate not previously described by other records in this region [ABSTRACT FROM AUTHOR]

Abstract: One of the most dramatic indicators of climate change is the reduction in the extent and thickness of Arctic sea ice that has resulted in an increase in wind‐driven sea ice mobility. During April and May 2017, satellite observations indicated that the ice arch that forms between Nares Strait and the Lincoln Sea collapsed. Typically, this collapse occurs in July or August allowing multiyear ice to exit the Arctic through Nares Strait. Here we show that the period of the collapse was associated with the presence of a polynya in northern Nares Strait, thin ice in the Lincoln Sea, and an unusual wind regime characterized by strong northerly flow. We propose that these anomalous conditions resulted in the arch's early collapse. If the ice in the region continues to thin, early collapses may occur more frequently with implications for the regional as well as the downstream climate and ecosystems. [ABSTRACT FROM AUTHOR]