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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]

Both historical observations and recent modeling studies reveal a faster warming in the Arctic compared to the Antarctic. To understand the role of the Antarctic Circumpolar Circulation (ACC) in this warming asymmetry, we simulate the climate mean state and climate response to doubled CO2 under different climate mean ACC states by closing or opening the Drake Passage (DP) with the Community Earth System Model. From closed to open DP, a stronger climate mean ACC leads to a stronger climate mean Atlantic Meridional Overturning Circulation (AMOC), as well as a colder Antarctic but a warmer Arctic in the climate mean state. The less climate mean sea ice coverage in a warmer Arctic implies less extensive sea ice melting under global warming. This causes a reduced asymmetry in warming between the two poles in response to the doubled CO2. Plain Language Summary: To understand the role of the Antarctic Circumpolar Circulation (ACC) in the asymmetric Arctic and Antarctic warming, we conduct two numerical model experiments. We consider two different climate states by closing or opening the Drake Passage (DP). The former yields a weak ACC, while the latter results in a strong ACC. A stronger climate mean ACC leads to a colder Antarctic but a warmer Arctic, due primarily to a concurrent stronger Atlantic Meridional Overturning Circulation (AMOC). The diminished coverage of sea ice in the warmer Arctic signifies a reduction in sea ice melting under global warming. Consequently, this leads to a reduction in the asymmetry in warming between the two poles in response to doubled CO2. These findings highlight a significant impact of the ACC on the global climate mean state and polar warming asymmetry, and shed light on the uncertainties in the coordinated interaction between major ocean circulation systems (e.g., AMOC and ACC) and on those in inter‐hemisphere interactions. Key Points: A stronger climate mean Antarctic Circumpolar Circulation (ACC) is accompanied by a stronger mean Atlantic Meridional Oceanic Circulation (AMOC)A stronger climate mean AMOC results in a warmer Arctic with less climate mean sea ice coverageThe less asymmetric polar warming in the presence of stronger climate mean ACC and AMOC is largely due to less sea ice melting in Arctic [ABSTRACT FROM AUTHOR]

A novel sub‐sampling method has been used to isolate the dynamic effects of the response of the North Atlantic Oscillation (NAO) and the Siberian High (SH) from the total response to projected Arctic sea‐ice loss under 2°C global warming above preindustrial levels in very large initial‐condition ensemble climate simulations. Thermodynamic effects of Arctic warming are more prominent in Europe while dynamic effects are more prominent in Asia/East Asia. This explains less‐severe cold extremes in Europe but more‐severe cold extremes in Asia/East Asia. For Northern Eurasia, dynamic effects overwhelm the effect of increased moisture from a warming Arctic, leading to an overall decrease in precipitation. We show that the response scales linearly with the dynamic response. However, caution is needed when interpreting inter‐model differences in the response because of internal variability, which can largely explain the inter‐model spread in the NAO and SH response in the Polar Amplification Model Intercomparison Project. Plain Language Summary: The projected loss of Arctic sea‐ice under 2°C global warming will cause large warming in the Arctic region and climate and weather anomalies outside the Arctic. The warming in the Arctic will mean warmer airmasses coming from the Arctic and also more moisture from the open Arctic Ocean. Furthermore, it will also change atmospheric circulation. These effects together will determine the impacts of Arctic warming. In this study, we introduce a novel sub‐sampling method to isolate atmospheric circulation change in response to the Arctic warming. The method involves selecting members of simulations from the experiment with future Arctic sea‐ice conditions, the average of which is equal to the average of the members of simulations in the experiment with present‐day Arctic sea‐ice conditions. We found that atmospheric circulation change in European regions is relatively weak so that warming effects will dominate the climate and weather response there. On the other hand, atmospheric circulation change will dominate the climate and weather response in East Eurasia. We also found that stronger atmospheric circulation changes will generally increase the response to the Arctic warming. We suggest caution when assessing whether different responses in different models can be interpreted as true differences in model physics. Key Points: A novel sub‐sampling method is introduced to isolate the role of dynamics in the response to projected Arctic sea‐ice lossA dynamical Siberian High response dominates the temperature response over East Eurasia while that of the North Atlantic Oscillation is weakInter‐model differences in Polar Amplification Model Intercomparison Project likely contain a large fraction of internal variability due to the unconstrained dynamic effects [ABSTRACT FROM AUTHOR]

We investigate the role of ocean heat transport (OHT) in driving the decadal variability of the Arctic climate by analyzing the pre‐industrial control simulation of a high‐resolution climate model. While the OHT variability at 65°N is greater in the Atlantic, we find that the decadal variability of Arctic‐wide surface temperature and sea ice area is much better correlated with Bering Strait OHT than Atlantic OHT. In particular, decadal Bering Strait OHT variability causes significant changes in local sea ice cover and air‐sea heat fluxes, which are amplified by shortwave feedbacks. These heat flux anomalies are regionally balanced by longwave radiation at the top of the atmosphere, without compensation by atmospheric heat transport (Bjerknes compensation). The sensitivity of the Arctic to changes in OHT may thus rely on an accurate representation of the heat transport through the Bering Strait, which is difficult to resolve in coarse‐resolution ocean models. Plain Language Summary: We studied how ocean heat transport (OHT) affects decade‐timescale variability in the Arctic climate using a high‐resolution climate model. Specifically, we compared the impacts of heat entering the Arctic Ocean through the Nordic Seas from the Atlantic and through the Bering Strait from the Pacific. Though more heat is transported from the Atlantic, Arctic surface temperature and sea ice respond more strongly to changes in OHT through the Bering Strait. Unlike Atlantic OHT, changes in Bering Strait OHT impact local air temperatures directly, without compensating changes in atmospheric heat transport. Proper representation of the Arctic's sensitivity to future increased OHT may thus rely on correctly representing OHT through Bering Strait, which is challenging in coarse‐resolution ocean models. Key Points: Ocean heat transport variability through the Bering Strait has an outsized effect on Arctic sea ice cover and surface temperatureAtlantic ocean heat transport anomalies into the Arctic are compensated by atmospheric heat transport anomalies on decadal timescales [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]

Models struggle to accurately simulate observed sea ice thickness changes, which could be partially due to inadequate representation of thermodynamic processes. We analyzed co‐located winter observations of the Arctic sea ice from the Multidisciplinary Drifting Observatory for the Study of the Arctic Climate for evaluating and improving thermodynamic processes in sea ice models, aiming to enable more accurate predictions of the warming climate system. We model the sea ice and snow heat conduction for observed transects forced by realistic boundary conditions to understand the impact of the non‐resolved meter‐scale snow and sea ice thickness heterogeneity on horizontal heat conduction. Neglecting horizontal processes causes underestimating the conductive heat flux of 10% or more. Furthermore, comparing model results to independent temperature observations reveals a ∼5 K surface temperature overestimation over ice thinner than 1 m, attributed to shortcomings in parameterizing surface turbulent and radiative fluxes rather than the conduction. Assessing the model deficiencies and parameterizing these unresolved processes is required for improved sea ice representation. Plain Language Summary: Numerical sea ice models rely on conceptual simplifications of the sea ice and snow conditions observed in the Arctic and Southern Ocean. In particular, we cannot account for the variations in sea ice thickness and snow depth at the meter scale because we have limited computing capabilities and lack a detailed understanding of the processes defining how the sea ice system evolves. Furthermore, when designing sea ice models, we assume that the heat can flow only vertically, while in reality, this exchange is also horizontal and depends on the local topography. Thanks to observations collected during the Multidisciplinary Drifting Observatory for the Study of Arctic Climate expedition, we can better quantify model errors when using thermodynamic approximations. Our findings suggest that slightly more heat flows through the sea ice system than we can simulate with a simplified sea ice model and that the surface temperature of the model is too warm for thin ice and snow conditions. Learning the nature of these errors is useful because we could formulate corrections for our models, investigate the occurrence of climate feedback mechanisms, and possibly provide more reliable predictions about the current state of the sea ice and its future evolution, which is currently heavily impacted by global warming. Key Points: Multidisciplinary Drifting Observatory for the Study of Arctic Climate observations enable improved thermodynamic process understanding and representation in sea ice modelsResolved meter‐scale ice and snow thickness heterogeneity and horizontal heat conduction enhance conductive heat flux by up to 10% in modelsA positive surface temperature model bias up to 5 K suggests a misrepresentation of the surface energy balance over thin ice [ABSTRACT FROM AUTHOR]

The Arctic is notable as a region where the greatest rate of increase in precipitation associated with global warming is anticipated. The Arctic precipitation simulated by the Coupled Model Intercomparison Project Phase 6 models showed a strong increasing trend since the 1980s. We found that the forcing factor of the trend is a combination of the continued strengthening of greenhouse gas forcing and the leveling off of aerosol forcing dominated in earlier periods. From an energetic perspective, we found that the increased atmospheric radiative cooling and reduced sensible heat transport from lower latitudes contributed equally to the recent increase in Arctic precipitation. The combination of these two energetic factors suggests a doubling of the Arctic amplification factor for precipitation relative to that for temperature. Future Arctic precipitation will change in proportion to the temperature change, and the fractional contributions of the energetic factors will remain stable across various scenarios. Plain Language Summary: The Arctic region is inherently a low‐precipitation area. However, because of global warming, precipitation is expected to increase substantially in the Arctic region compared with the global average when viewed as a percentage change from the original precipitation. This severely affects climate change in the Arctic environment. The latest climate model simulations show that there has been a rapid increase in precipitation in the Arctic region in recent decades. The driving factors behind the rapid increase are the effects of the accelerating growth of greenhouse gas concentrations, which were previously suppressed by the increasing anthropogenic aerosol emissions before the 1980s. Based on the heat budget of the atmosphere, we identified important factors contributing to these precipitation changes. These include enhanced radiative cooling (responding locally to increased air temperature) and reduced heat transport from lower latitudes due to greater temperature increases at higher latitudes. Future precipitation will change in proportion to the temperature change while maintaining consistent fractional contributions across different scenarios. Key Points: Trends in Arctic precipitation in the recent and future decades are examined from multimodel simulationsThe recent rapid increase is driven by accelerating greenhouse gas concentrations and plateauing growth in anthropogenic aerosol emissionsIncreased radiative cooling and reduced poleward sensible heat transport equally contributed to the Arctic precipitation changes [ABSTRACT FROM AUTHOR]

Tropospheric reactive bromine (Bry) influences the oxidation capacity of the atmosphere by acting as a sink for ozone and nitrogen oxides. Aerosol acidity plays a crucial role in Bry abundances through acid‐catalyzed debromination from sea‐salt‐aerosol, the largest global source. Bromine concentrations in a Russian Arctic ice‐core, Akademii Nauk, show a 3.5‐fold increase from pre‐industrial (PI) to the 1970s (peak acidity, PA), and decreased by half to 1999 (present day, PD). Ice‐core acidity mirrors this trend, showing robust correlation with bromine, especially after 1940 (r = 0.9). Model simulations considering anthropogenic emission changes alone show that atmospheric acidity is the main driver of Bry changes, consistent with the observed relationship between acidity and bromine. The influence of atmospheric acidity on Bry should be considered in interpretation of ice‐core bromine trends. Plain Language Summary: Reactive bromine in the air impacts major oxidants in our atmosphere, which remove pollutants and greenhouse gases and has changed over time in the Russian Arctic. Ice‐core bromine and acidity show a significant increase from pre‐industrial to the 1970s followed by a decrease. Our study suggests that human activities caused changes in bromine through the emissions of acidic gases from fossil fuel combustion. Considering relationships between atmospheric acidity and bromine is crucial to interpreting bromine variations in ice cores. Key Points: Bromine (Br) concentrations increased 3.5‐fold from pre‐industrial to 1975 and declined 50% by 1999 in a Russian Arctic ice‐coreA robust correlation between ice‐core Br and acidity highlights acidity's key role in influencing the atmospheric Br budgetModel shows acid‐catalyzed sea‐salt debromination is the largest source of reactive Br and drives ice‐core Br trends [ABSTRACT FROM AUTHOR]

Sea ice topography information can be obtained from altimetry but these data are spatially and temporally limited compared to recent synthetic aperture radar (SAR) missions such as the RADARSAT Constellation Mission (RCM). We analyze the relationship between sea ice roughness and height obtained from three Ice, Cloud, and Land Elevation Satellite (ICESat)‐2 tracks on two dates in March 2022, with RCM backscatter from 17 images in the McClintock Channel, Canadian Arctic. We analyze how this relationship varies with ice type, polarization, and incidence angle. We find particularly notable relationships between sea ice roughness and horizontal‐transmit/vertical‐receive backscatter for first‐year ice, and sea ice height and backscatter for multi‐year ice. We develop a preliminary model for winter sea ice roughness retrieval using RCM. In comparison with independent ICESat‐2 data in our study region, we find the model performs effectively at estimating a roughness distribution and key roughness statistics, and characterizes spatial variations in roughness at a sub‐kilometer scale. Plain Language Summary: Sea ice topography estimates are important for improving ocean‐climate models, understanding sea ice evolution, and planning ice travel. Estimates can be obtained from altimetry missions, but these data are spatially and/or temporally limited compared to recent synthetic aperture radar missions such as the C‐band RADARSAT Constellation Mission (RCM). By comparing RCM backscatter with measurements of height and roughness obtained using Ice, Cloud, and Land Elevation Satellite (ICESat)‐2 in the Canadian Arctic, we demonstrate the potential for using RCM to estimate sea ice topography. We show there is a notable relationship between sea ice roughness and backscatter on first‐year ice in late winter, particularly in the horizontal‐transmit/vertical‐receive channel, and a notable relationship between sea ice height and backscatter on multi‐year ice. We also observe that the relationship between the RCM signal and roughness varies with incidence angle. Based on this analysis we develop a preliminary model for winter sea ice roughness retrieval using RCM. In comparison with ICESat‐2 data, we find the model performs effectively at estimating key roughness statistics, and characterizes spatial variations in roughness at a sub‐kilometer scale. These findings will facilitate the use of RCM to validate geophysical models, map rough areas of ice, assess ice evolution and develop new topographic models. Key Points: Sea ice roughness measured by Ice, Cloud, and Land Elevation Satellite (ICESat)‐2 and horizontal‐transmit/vertical‐receive RADARSAT Constellation Mission (RCM) backscatter exhibit a notable relationship on late‐winter first‐year iceSea ice height, as measured by ICESat‐2, and RCM backscatter exhibit a notable relationship on late‐winter multi‐year iceWe develop/validate a model, based on comparison with ICESat‐2 data, for estimating sea ice roughness using RCM backscatter in the Arctic [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]

In this study, we perform online sea ice bias correction within a Geophysical Fluid Dynamics Laboratory global ice‐ocean model. For this, we use a convolutional neural network (CNN) which was developed in a previous study (Gregory et al., 2023, https://doi.org/10.1029/2023ms003757) for the purpose of predicting sea ice concentration (SIC) data assimilation (DA) increments. An initial implementation of the CNN shows systematic improvements in SIC biases relative to the free‐running model, however large summertime errors remain. We show that these residual errors can be significantly improved with a novel sea ice data augmentation approach. This approach applies sequential CNN and DA corrections to a new simulation over the training period, which then provides a new training data set to refine the weights of the initial network. We propose that this machine‐learned correction scheme could be utilized for generating improved initial conditions, and also for real‐time sea ice bias correction within seasonal‐to‐subseasonal sea ice forecasts. Plain Language Summary: Climate models contain errors which often lead to predictions which are consistently out of agreement with what we observe in reality. In some cases we know the origin of these errors, for example, predicting too much sea ice as a result of consistently cool ocean temperatures. In reality, however, there are typically numerous model errors interacting across the atmosphere, ocean and sea ice, and to manually parse through large volumes of climate model data in an attempt to isolate these errors in time and space is highly impractical. Machine learning on the other hand is a framework which is well‐suited to this task. In this work we take a machine learning model which, at any given moment, ingests information about a climate model's atmosphere, ocean and sea ice conditions, and predicts how much error there is in the climate model's representation of sea ice, without seeing any actual sea ice observations. We use this to adjust the sea ice conditions in one particular climate model as it is running forward in time making predictions, and we find that this significantly reduces the model's sea ice errors globally. Key Points: We use a convolutional neural network (CNN) to perform online sea ice bias correction within global ice‐ocean simulationsThe CNN systematically reduces the free‐running model bias in both the Arctic and AntarcticThe online performance can be improved by combining CNN and data assimilation corrections in order to iteratively augment the training data [ABSTRACT FROM AUTHOR]

We simulated the seasonal temperature evolution in the atmosphere of Antarctica and the Arctic focusing on infrared processes. Contributions by other processes were parametrized and kept fixed throughout the simulations. The model was run for current CO2 and CH4 and for doubled concentrations. For doubling CH4 the warming in Antarctica is restricted to the lowest few hundred meters above the surface while in the Arctic we find a warming in the whole troposphere. We find that the amount of water is the main driver for the differences between both polar regions. When increasing both, CO2 and CH4 from pre‐industrial values to current concentrations, and averaged over the whole troposphere, we find a warming of 0.42 K for the Arctic and a slight cooling of 0.01 K for Antarctica. Our results contribute to the understanding of the lack of warming seen in Antarctica throughout the last decades. Plain Language Summary: In 2015 we have initiated a discussion on a fundamental property of the radiation in the atmosphere over Antarctica: The negative greenhouse effect (Schmithüsen et al., 2015, https://doi.org/10.1002/2015GL066749). A negative greenhouse effect means, the atmosphere emits more radiation to space than it receives from the surface. This results in a cooling somewhere in the Antarctic atmosphere during some months of the year, when increasing CO2. We now simulate how the Antarctic atmospheric temperature responds in all altitude levels to CO2 and CH4 increases, and show this is different from the temperature response in the Arctic. We show for example, that an increase in CH4 cools nearly the whole troposphere, although the response for CH4 is much lower in amplitude than for CO2. We find that the amount of water is the main driver for the differences between both polar regions. Since the amount of water vapor strongly depends on temperature, the colder Antarctic atmosphere responds differently to the Arctic when greenhouse gases increase. Our studies could be one important factor when understanding the lack of warming in Antarctica throughout the last decades. Key Points: We simulate the temperature development in both polar regions in the infrared and find that doubling CO2 and CH4 lead to opposing forcingsThe different amount of water vapor shows to be responsible for the differences in warming/cooling in both polar regionsIn Antarctica doubling CH4 leads to a cooling of almost the whole troposphere, a future increase in H2O could invert this [ABSTRACT FROM AUTHOR]

The relative importance of radiative feedbacks and emissions scenarios in controlling surface warming patterns is challenging to quantify across model generations. We analyze three variants of the Community Earth System Model (CESM) with differing equilibrium climate sensitivities under identical CMIP5 historical and high‐emissions scenarios. CESM1, our base model, exhibits Arctic‐amplified warming with the least warming in the Southern Hemisphere middle latitudes. A variant of CESM1 with enhanced extratropical shortwave cloud feedbacks shows slightly increased late‐21st century warming at all latitudes. In the next‐generation model, CESM2, global‐mean warming is also slightly greater, but the warming is zonally redistributed in a pattern mirroring cloud and surface albedo feedbacks. However, if the nominally equivalent CMIP6 scenario is applied to CESM2, the redistributed warming pattern is preserved, but global‐mean warming is significantly greater. These results demonstrate how model structural differences and scenario differences combine to produce differences in climate projections across model generations. Plain Language Summary: Earth System Models are used to project climate change through the 21st century. Such projections are constrained by a range of assumptions about emissions of greenhouse gases as well as other climate‐relevant human activities like deforestation and emissions of aerosols. These assumptions are carefully evaluated and represented in an emissions scenario. In a coordinated set of experiments, a given emissions scenario is applied to a number of different Earth System Models to test differences in climate projections that arise from physical (or "structural") differences among the models. However, over time, models are updated and improved, and emissions scenarios are updated as well. This continuous updating makes it difficult to track whether a new set of climate projections is different from its predecessor due to model changes or due to scenario changes. In this paper, we disentangle these two factors, clarifying the role of each. For the Earth System Model that we use, the emissions scenario largely controls the amount of global‐mean warming projected for the 21st century, but the model or structural differences matter greatly for the regional patterns of warming. Key Points: Higher equilibrium climate sensitivity, from more positive cloud feedbacks, only slightly increases 21st century transient warmingCloud and surface albedo feedbacks redistribute warming from the middle and high northern latitudes to lower latitudesThese warming pattern differences result from feedback differences, not CMIP5 to CMIP6 forcing scenario differences [ABSTRACT FROM AUTHOR]

The Pacific oceanic input to the Arctic via the Bering Strait (important for western Arctic ice retreat, water properties, and nutrient supply) has been increasing for three decades. Using satellite Ocean Bottom Pressure (OBP) and Dynamic Ocean Topography (DOT) data, we show that long‐term trends in mooring data for a well‐sampled sub‐period (2003–2014) relate to summer OBP and DOT drop in the Arctic's East Siberian Sea (ESS), in turn caused by stronger westward ESS winds, and increased fall westward winds in the Bering Sea. OBP/DOT differences imply strong (0.17 psu/year) ESS salinization, likely caused by hitherto unappreciated increased Pacific inflow to that region. We find ESS OBP trends are (erroneously) reversed in older data versions, and estimate that ESS salinization may significantly mediate Bering Strait flow increase. These facts may explain why models assimilating older OBP data, or with erroneous Bering Strait salinities, fail to simulate observed Bering Strait flow increase. Plain Language Summary: Direct year‐round, in‐water measurements show the Pacific oceanic flow to the Arctic (which is only via the narrow Bering Strait) has been increasing for three decades. This flow is important to the region as it triggers seasonal ice retreat in the Pacific side of the Arctic, the "western Arctic," and strongly influences the temperature, salinity, and nutrient content of western Arctic waters. Using satellite data sets that measure the height of the sea surface, and how it changes, we find we can explain the 2003–2014 observed flow increase by increased westward winds in the Arctic in summer and in the Bering Sea in fall. These satellite data sets also imply parts of the coastal western Arctic have become much saltier over this period, likely due to previously unsuspected increased Pacific input to the region. This increased salinity acts to slow the increasing flow to the Arctic. We find older versions of some of these satellite data sets are inconsistent with the observed flow increase. Most model simulations of the Arctic do not currently capture the observed flow increase. We suggest this may be due to fitting these models to older (erroneous) satellite data sets, or having poor representation of the salinity of Pacific waters. Key Points: Satellite data show long‐term Bering Strait flow increase may be due to increasing westward winds in the summer Arctic and fall Bering SeaData imply large (0.17 psu/year) East Siberian Sea salinization, likely due to hitherto unappreciated increasing Pacific inflow to that regionUse of older Ocean Bottom Pressure data or poor salinity representation may explain failure of models to simulate observed flow increase [ABSTRACT FROM AUTHOR]

Reliable boundary‐layer turbulence parametrizations for polar conditions are needed to reduce uncertainty in projections of Arctic sea ice melting rate and its potential global repercussions. Surface turbulent fluxes of sensible and latent heat are typically represented in weather/climate models using bulk formulae based on the Monin‐Obukhov Similarity Theory, sometimes finely tuned to high stability conditions and the potential presence of sea ice. In this study, we test the performance of new, machine‐learning (ML) flux parametrizations, using an advanced polar‐specific bulk algorithm as a baseline. Neural networks, trained on observations from previous Arctic campaigns, are used to predict surface turbulent fluxes measured over sea ice as part of the recent MOSAiC expedition. The ML parametrizations outperform the bulk at the MOSAiC sites, with RMSE reductions of up to 70 percent. We provide a plug‐in Fortran implementation of the neural networks for use in models. Plain Language Summary: Heat can make its way into or out of sea ice via unpredictable air movements, known as turbulence, near the sea surface. In order to predict how quickly Arctic sea ice will melt in the future, we need to know how much heat the turbulence can transport in different weather conditions. Traditionally, turbulence calculations have been performed using sophisticated mathematical formulae from physics. In this study, we test an alternative method for predicting turbulent heat exchange: a computer algorithm known as an artificial neural network. By showing turbulence data, measured in the Arctic during previous scientific expeditions, to the network, it can be "trained" to make predictions in a process known as machine learning. We compare turbulence measurements, taken above sea ice in the recent MOSAiC expedition, with predictions from trained neural networks. We find that the neural networks are better than the traditional physics at predicting what the scientists at MOSAiC observed. The trained neural networks have been made publicly available so that they can be used by scientists for predicting climate change. Key Points: Neural networks trained on previous Arctic campaigns predict surface turbulent fluxes from MOSAiC more accurately than bulk methodsUpdated parametrizations using the MOSAiC data have been developed and implemented in Fortran for deployment in weather/climate modelsModest performance gains (up to +7% R2) from recalibration on MOSAiC indicate good generalizability to the pan‐Arctic sea ice domain [ABSTRACT FROM AUTHOR]

Permafrost warming and degradation is well documented across the Arctic. However, observation‐ and model‐based studies typically consider thaw to occur at 0°C, neglecting the widespread occurrence of saline permafrost in coastal plain regions. In this study, we document rapid saline permafrost thaw below a shallow arctic lake. Over the 15‐year period, the lakebed subsided by 0.6 m as ice‐rich, saline permafrost thawed. Repeat transient electromagnetic measurements show that near‐surface bulk sediment electrical conductivity increased by 198% between 2016 and 2022. Analysis of wintertime Synthetic Aperture Radar satellite imagery indicates a transition from a bedfast to a floating ice lake with brackish water due to saline permafrost thaw. The regime shift likely contributed to the 65% increase in thermokarst lake lateral expansion rates. Our results indicate that thawing saline permafrost may be contributing to an increase in landscape change rates in the Arctic faster than anticipated. Plain Language Summary: In this study, we combine direct field measurements, near‐surface geophysical studies, and remote sensing change detection to document the rapid thaw of saline permafrost below a shallow thermokarst lake on the Arctic Coastal Plain of northern Alaska. Thaw of ice‐rich saline permafrost resulted in an increase in the lake depth by 0.6 m over a 15‐year period. The transition from a bedfast ice lake to a floating ice lake with brackish water is responsible for the increase near‐surface bulk sediment electrical conductivity and likely contributed to an increase in the lateral expansion rate of the lake. Our findings indicate that active permafrost thaw is likely occurring below shallow arctic lakes at temperatures below 0°C. Key Points: We document the rapid thaw and subsidence of saline permafrost below a shallow thermokarst lake in Arctic AlaskaWe hypothesize that rapid saline permafrost degradation is occurring below shallow arctic lakes at sub‐zero temperaturesThawing saline permafrost may be contributing to an increase in landscape change rates in the Arctic [ABSTRACT FROM AUTHOR]

Observed trends in tropospheric ozone, an important air pollutant and short‐lived climate forcer (SLCF), are estimated using available surface and ozonesonde profile data for 1993–2019, using a coherent methodology, and compared to modeled trends (1995–2015) from the Arctic Monitoring Assessment Program SLCF 2021 assessment. Increases in observed surface ozone at Arctic coastal sites, notably during winter, and concurrent decreasing trends in surface carbon monoxide, are generally captured by multi‐model median trends. Wintertime increases are also estimated in the free troposphere at most Arctic sites, with decreases during spring months. Winter trends tend to be overestimated by the multi‐model medians. Springtime surface ozone increases in northern coastal Alaska are not simulated while negative springtime trends in northern Scandinavia are not always reproduced. Possible reasons for observed changes and model performance are discussed including decreasing precursor emissions, changing ozone dry deposition, and variability in large‐scale meteorology. Plain Language Summary: The Arctic is warming much faster than the rest of the globe due to increases in carbon dioxide, and other trace constituents like ozone, also an air pollutant. However, improved understanding is needed about long‐term changes or trends in Arctic tropospheric ozone. A coherent methodology is used to identify trends in surface and regular profile measurements over the last 20–30 years, and results from six chemistry‐climate models. Increases in observed ozone are found at the surface and in the free troposphere during winter in the high Arctic. Paradoxically, decreases in nitrogen oxide emissions at mid‐latitudes appear to be leading to increases in ozone during winter, but associated increases in Arctic tropospheric ozone tend to be overestimated in the models. Increases are also found at the surface in northern Alaska during spring but not reproduced by the models. The causes are unknown but could be related to changes in local sources or sinks of Arctic ozone or in large‐scale weather patterns. Declining mid‐latitude emissions, or increased dry deposition to northern forests, may explain negative surface ozone trends over northern Scandinavia in spring that are not always captured by the models. Further work is needed to understand changes in Arctic tropospheric ozone. Key Points: Coherent ozone trend analysis methodology applied to multi‐decade, pan‐Arctic surface and ozonesonde datasets and multi‐model mediansIncreasing winter Arctic tropospheric ozone overestimated by models in the free troposphere, and spring surface changes not capturedSpring (summer) decreases (increases) in observed ozone throughout the troposphere, not always simulated by models [ABSTRACT FROM AUTHOR]

Attenuation of ocean waves by ice is a crucial process of the interaction between waves and sea ice in marginal ice zone (MIZ), while such interaction can contribute to the retreating of sea ice in the Arctic. Based on the retrieved two‐dimensional ocean wave spectra by spaceborne Synthetic Aperture Radar, we investigated the attenuation of ocean waves in the MIZ in Svalbard and Greenland. The results show that the energy attenuation rate ranges from 0.126 × 10−4/m to 0.618 × 10−4/m. Quantitative analysis suggests that the attenuation rate is significantly related to wave height and peak wave period of coming waves. It is further found that the waves decay faster in the area with ice thickness exceeding 0.5 m. We compared the derived wave attenuation rates in the present study with those in previous studies based on in situ measurements, which reveals that waves are becoming less attenuated by sea ice in the Arctic. Plain Language Summary: The interaction between sea ice and ocean waves is one of the key processes that accelerates the retreat of sea ice in the Arctic. The attenuation of ocean waves by sea ice is crucial to understanding the wave‐ice interaction mechanism and predicting ice changes. Spaceborne Synthetic Aperture Radar (SAR), capable of imaging ocean waves and sea ice in two‐dimension with high spatial resolution, has shown tremendous potential in studies on wave‐ice interaction. In this study, SAR images acquired in ice‐covered areas near Svalbard and east of Greenland were collected, and then ocean wave spectra were retrieved from these SAR images. Ocean wave spectra depict sea states elaborately by showing the wave energy distribution in different frequencies and directions. Subsequently, we derived the wave attenuation rate in sea ice from these wave spectra. By comparing the derived attenuation rates with previous field observations, the study reveals a lower attenuation rate, which suggests the waves were less attenuated by ice in past decades under ongoing retreating and thinning of sea ice in the Arctic. This indicates that waves can penetrate sea ice easier and deeper, which may further induce the retreating of sea ice. Key Points: Wave attenuation rate in sea ice was derived based on non‐linear inversion of two‐dimensional ocean wave spectra by Synthetic Aperture Radar in the Arctic marginal ice zone (MIZ)The attenuation rate generally follows the exponential law, varying with sea state (wave height and period) and sea ice conditionsCombining previous studies and this one, we may infer that the wave attenuation in the Artic MIZ is weakening due to sea ice retreat [ABSTRACT FROM AUTHOR]

Arctic amplification has been proposed to promote temperature extremes by slowing the midlatitude jet and increasing the amplitude of its meanders. Observational and modeling studies have used a variety of metrics to quantify jet waviness. These studies show conflicting changes in jet waviness depending on the metric used and period examined. Here, we evaluate common metrics for dry idealized model simulations in which we apply polar warming of varying depth and meridional extent. In all simulations, polar warming increases the spatial extent of jet meanders, but reduces the magnitudes of ridges and troughs within the wave. As a result, geometric and anomaly‐amplitude measures of jet waviness can yield opposing responses. This contrast between metrics is particularly evident when warming extends into the midlatitudes. In all simulations, midlatitude temperature anomalies weaken as the poles warm, suggesting that a wavier jet need not imply stronger temperature extremes. Plain Language Summary: The Arctic is warming faster than anywhere else on Earth, and this has been suggested to affect weather over midlatitude regions in Eurasia and North America. It has been proposed that, as the pole warms, the equator‐to‐pole temperature gradient is reduced and the atmospheric jet stream slows down and undergoes larger, slower‐moving meanders, which bring long‐lasting extreme temperatures. However, theories for understanding waves in the jet stream actually suggest that these waves could weaken when the equator‐to‐pole temperature gradient decreases. This study uses simple model simulations to test how different metrics for describing jet waviness respond when the pole is warmed. We find that the overall scale of meanders does seem to increase, but the associated temperature anomalies decrease, suggesting a wavier jet stream need not imply stronger temperature extremes. Key Points: Spatial extent of midlatitude waves is increased by polar amplificationMagnitudes of ridges and troughs within waves are decreased by polar amplificationAccordingly, geometric, and anomaly‐amplitude measures of jet waviness can yield opposing responses [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]

Taking advantage of the Polar Amplification Model Intercomparison Project simulations and using a Lagrangian objective feature tracking algorithm, we determine the response of extratropical cyclones to sea‐ice loss and consequent weakening of the equator‐to‐pole near‐surface temperature gradient. The wintertime storm tracks are found to shift equatorward in the North Atlantic and over Europe, and eastward in the North Pacific. In both regions, cyclones become weaker and slower, particularly on the poleward flank of the storm tracks. On average, there are fewer individual cyclones in the extratropics each winter, they last longer, are weaker, and travel more slowly. These changes are greatest over the Arctic, but still statistically significant in midlatitudes despite being small compared to internal variability. Inter‐model spread in cyclone responses are not strongly correlated with that in Arctic warming or Arctic amplification. Little change in summertime cyclones is found. Plain Language Summary: Using identically performed experiments from eight different climate models, we study how low pressure systems, known as cyclones or storms, may change as Arctic sea ice diminishes. An algorithm is used to identify the weather systems and track them across their lifecycle. In the wintertime, the typical path of storms over the Atlantic Ocean shifts southward toward the equator. Over the Pacific, the storm tracks shifts toward North America. Arctic sea‐ice loss causes there to be fewer storms each winter across the northern midlatitudes, and these tend to be weaker, slower moving, but longer lasting. These changes are largest over the Arctic itself but also found over mid‐latitudes. These changes may be important because the number, location, and character of storms control the winter weather over Europe, North America and Asia. In the summertime, we did not find any detectable impact of Arctic sea‐ice loss on storms. Key Points: The Northern Hemisphere winter storm tracks shift south and/or east in response to Arctic sea‐ice lossSea ice loss leads to fewer, slower, longer lasting, and weaker wintertime cyclonesResponses are small compared to internal variability, but larger in winter than summer [ABSTRACT FROM AUTHOR]

Reanalysis data and numerical model are employed to uncover the mechanisms of spring (March–April) Arctic surface warming. Different from other seasons, little additional solar radiation absorption or seasonal heat storage release contributes to Arctic surface warming in spring. Both observation and numerical results suggest that horizontal heat advection dominates Arctic surface air warming. However, horizontal advection originates from lower latitudes instead of local energy redistribution as in other seasons. Furthermore, Arctic warming weakens the meridional potential vorticity gradient, which strengthens the synoptic atmospheric blocking event. As a result, more warm (cold) air is transported to higher (lower) latitudes along the edge of high pressure, which is an accumulation of atmospheric blocking events. The results suggest that anomalous meridional heat transport plays more important roles in Arctic surface warming when the anomalous radiative forcing is weak. Without being absorbed by the ocean, additional available energy induces strong Arctic springtime surface warming. Plain Language Summary: Arctic spring warming does not occur due to local forcing and feedback, which means surface albedo feedback (solar radiation anomaly) and seasonal heat storage do not dominate Arctic surface warming in spring. Synoptic activities, such as atmospheric blocking or eddies, are highly influenced by climate change. Alternatively, atmospheric blocking or eddy anomalies influence the climate, that is, enhance horizontal temperature advection, which becomes the dominant warming mechanism in the spring Arctic. In this study, we focus on remote forcings. Key Points: Surface albedo feedback and seasonal heat storage have much smaller influences on Arctic spring warming than other seasonsLate winter Arctic warming triggers a weaker meridional potential vorticity gradient in spring, resulting in atmospheric blocking with greater strengthLonger‐existing and stronger atmospheric blocking events induce anticyclonic wind, transporting additional energy meridionally in spring [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]

Climatic warming and permafrost thaw are predicted to increase Arctic riverbank erosion, threatening communities and accelerating sediment, carbon and nutrient cycling between rivers and floodplains. Existing theory assumes that pore‐ice thaw sets riverbank erosion rates, but overpredicts observed erosion rates by orders of magnitude. Here, we developed a simple model that predicts more modest rates due to a sediment‐entrainment limitation and riverbank armoring by slump blocks. Results show that during times of thaw‐limited erosion, the river rapidly erodes permafrost and undercuts its banks, consistent with previous work. However, overhanging banks generate slump blocks that must thaw and erode by sediment entrainment. Sediment entrainment can limit bank and slump block erosion rates, producing seasonally averaged rates more consistent with observations. Importantly, entrainment‐limited riverbank erosion does not depend on water temperature, indicating that decadal erosion rates may be less sensitive to warming than predicted previously. Plain Language Summary: Riverbank erosion in the Arctic is a major hazard for riverside communities and infrastructure. Arctic rivers flow through regions of permanently frozen ground, and this ground is thawing as the climate warms. Therefore, there is major concern that riverbank erosion will accelerate in the future because the ground loses its strength when thawed. However, in order for a riverbank to erode, the river must satisfy two conditions: it must thaw the frozen ground and entrain the thawed sand and mud. Our model and analyses suggest that riverbank erosion in many Arctic rivers can be limited by the river's ability to entrain and transport the sand and mud, rather than the canonical view that erosion is limited by the rate of ground thaw. Applying our model to the Yukon River indicates that thaw rates are so fast that they cannot set the rate of erosion for the melt season. Instead, bank erosion for part of the time is controlled by the ability of the river to move the bank sediment, making riverbank erosion less sensitive to warming river waters. Key Points: A new model shows that permafrost bank erosion depends both on pore ice thaw and sediment entrainmentSediment entrainment from thawed banks and slump blocks can be rate‐limiting in some cases, which helps explain slow bank migration ratesWhere limited by sediment entrainment, decadal erosion rates may be less sensitive to warming river water than predicted previously [ABSTRACT FROM AUTHOR]

The role of the mid‐latitude seaway between the proto‐Paratethys and the North Sea on the early Paleogene ocean circulation is examined with a state‐of‐art earth system model. The early Eocene simulations here demonstrate that the open mid‐latitude seaway captures most relatively fresh surface water from the Arctic and Greenland‐Norwegian Sea and prohibits them from leaking into the Labrador Sea, thus benefiting the Atlantic meridional overturning circulation (AMOC). However, the closure of the seaway triggers the AMOC reduction as more relatively fresh surface water enters the Labrador Sea, and the AMOC finally shuts down. Together with geological reconstructions, our results also provide insights into understanding the evolution of the Atlantic‐Arctic oceanic gateways during the Paleogene. Plain Language Summary: Recent geological evidence demonstrated that a mid‐latitude seaway connected the proto‐Paratethys sea and the North Sea during the early Eocene. Then, this connection was closed since the late Eocene‐early Oligocene. Here, using climate modeling, we investigated the effects of this mid‐latitude seaway evolution, particularly in modulating the Atlantic meridional overturning circulation (AMOC). Our simulations show that the open seaway prohibits the relatively fresh Arctic surface water from leaking into the Labrador Sea and thus favors the formation of AMOC. On the contrary, the closed seaway allows more relatively fresh Arctic surface water to influence the Labrador Sea, thus triggering the AMOC reduction. Our study pinpoints a controlling role of the mid‐latitude seaway in modulating global ocean circulation during the early Paleogene. Key Points: The evolution of the mid‐latitude seaway in the early Paleogene influences ocean circulationThe opening of the seaway favors the Atlantic meridional overturning circulation (AMOC), while its closing leads to AMOC shutdown [ABSTRACT FROM AUTHOR]

Estimates of nitrate loading to the Arctic Ocean are limited by the lack of field observations within deltas partly due to logistical constraints. To overcome this limitation, we use a remote sensing framework to estimate retention of nitrate in Arctic deltas. We achieve this by coupling hydrological and biogeochemical process models at the network scale for five major Arctic deltas. Binary masks of delta channels were used to simulate flow direction and magnitude through networks. Models were parameterized using historical and seasonal observations. Simulated nitrate retention ranged from 2.9% to 15% of the incoming load. Retention rates were largest during winter but smallest during spring conditions when increased discharges export large nitrate masses to the coast. Under future climate scenarios, retention rates fall by ∼1%–10%. Arctic deltas have an important effect on the magnitude of nitrate entering Arctic seas and the inclusion of processing in deltas can improve flux estimates. Plain Language Summary: The Arctic Ocean is the smallest and shallowest of the world's oceans but receives the largest riverine input per basin volume. Thus, the flux of nitrate from land to sea through rivers in the circumpolar Arctic can have large impacts on coastal life and global biogeochemical cycles. To assess the impact of terrestrially derived nitrate on Arctic Ocean chemistry under current and future scenarios, accurate accounting of nitrate loading is needed. Deltas act as filters that reduce nitrate loads, but current estimates of flux exclude the effects of Arctic deltas on nitrate export. We use a novel approach based on satellite imagery to estimate the potential impact of deltas on nitrate retention on five Arctic deltas, representing a range of morphologies and sizes. Our analysis shows seasonal and morphological differences in nitrate processing rates in each delta with retention rates ranging from 2.9% to 15% of incoming load and most retention occurring during winter months. Under future climate scenarios, the efficiency of nitrate retention decreases by up to 10%. Our models suggest that Arctic deltas alter the magnitude of nitrate entering the ocean and future predictions of loading or current earth system models could be improved by incorporating their effect. Key Points: Remotely sensed data provide a useful tool for revealing patterns of nitrate retention in Arctic deltasChannel networks of Arctic deltas are most efficient at retaining nitrate during spring and winterHotspots of nitrate removal cluster according to network structure and discharge on Arctic deltas [ABSTRACT FROM AUTHOR]

The existence of a cool sea surface skin layer in the global ocean during both day and night is generally recognized. However, a warm skin should be present if the total surface net heat flux (Qnet ${Q}_{\mathrm{n}\mathrm{e}\mathrm{t}}$) were to be from the atmosphere into ocean. Saildrone, an advanced uncrewed surface vehicle, has been shown to be able to provide sufficiently accurate sea skin temperature (SSTskin) and subsurface temperature (SSTdepth) data at high latitudes. Using those SST data along with meteorological parameters from a Saildrone deployed in the Arctic in the summer of 2019, some warm skin layers were identified due to the Qnet ${Q}_{\mathrm{n}\mathrm{e}\mathrm{t}}$ gain resulting from the combined effect of positive air‐sea temperature difference, humid surface air and cloudy skies. Furthermore, most warm skins here were found during and shortly after rainfall events. It is essential to incorporate the ability to simulate warm skin layers in the present cool skin models. Plain Language Summary: In most cases, the sea‐surface temperature of the skin of the ocean (SSTskin) is cooler than the temperature at the base of skin layer, which is a layer in which the vertical transport of heat is primarily by molecular conduction rather than turbulent mixing. By analyzing the Saildrone data measured in 2019 summer at the Pacific sector of the Arctic Ocean, some unusual warmer SSTskin signals were revealed and which are shown to be physically reasonable. This finding indicates the near‐surface thermal structure needs to be better understood and further studied. Key Points: Using skin and subsurface ocean temperatures and atmospheric variables from Saildrones to identify warm skin layers at high latitudesWarm skins are mostly present with positive air‐sea temperature difference and humid air under cloudy skiesWarm skin is often associated with the occurrence of rainfall and model schemes for the warm skin necessarily need to be established [ABSTRACT FROM AUTHOR]

We evaluate Linear Inverse Models (LIMs) trained on last millennium model data to predict Arctic sea‐ice concentration, thickness, and other atmospheric and oceanic variables on monthly timescales. We find that more than 500 years of training data and 100 years of validation data are needed to reliably estimate LIM forecast skill. The best LIM has skill up to 8 months lead time and outperforms an autoregressive model of order one (AR1) forecast at all locations, with particularly large outperformance near the ice edge. However, for out‐of‐sample validation tests using data from various different model simulations and reanalysis products, they underperform an AR1 model due to differences in the location of the sea‐ice edge from the training data. We present a metric for predicting LIM forecast skill, based on the spatial correlation of the variance in the training and validation data sets. Plain Language Summary: Rapid changes in sea‐ice concentration in recent decades have produced new navigational challenges and hazards in the region, elevating the importance of seasonal sea‐ice forecasts. Arctic sea ice has been shown to contain inherent predictability on seasonal timescales, yet current predictions generally show poor skill. Here, we employ a statistical technique referred to as Linear Inverse Modeling, which uses linearized dynamical modes estimated from a training data set to predict sea‐ice conditions on monthly timescales. We find a Linear Inverse Model is able to outperform a baseline statistical model throughout the Arctic when initialized on the data derived from the same model. Key Points: A Linear Inverse Model is evaluated using last millennium model simulations for Arctic climate predictionThe Linear Inverse Model successfully predicts Arctic conditions when the same model simulation is used for training and validationLinear Inverse Model forecast skill is proportional to the spatial correlation of variance in the validation and training data [ABSTRACT FROM AUTHOR]

Melt ponds forming on Arctic sea ice in summer significantly reduce the surface albedo and impact the heat and mass balance of the sea ice. Therefore, their areal coverage, which can undergo rapid change, is crucial to monitor. We present a revised method to extract melt pond fraction (MPF) from Sentinel‐2 satellite imagery, which is evaluated by MPF products from higher‐resolution satellite and helicopter‐borne imagery. The analysis of melt pond evolution during the MOSAiC campaign in summer 2020, shows a split of the Central Observatory (CO) into a level ice and a highly deformed ice part, the latter of which exhibits exceptional early melt pond formation compared to the vicinity. Average CO MPFs are 17% before and 23% after the major drainage. Arctic‐wide analysis of MPF for years 2017–2021 shows a consistent seasonal cycle in all regions and years. Plain Language Summary: In the Arctic summer, puddles of surface melt water, called melt ponds, form on the sea ice. These melt ponds reduce the ability of the surface to reflect the sunlight. Instead, they absorb more solar energy and pave the way into the ocean beneath where the energy is also absorbed. Thus, it is important to know where these melt ponds develop and what fraction of the surface they cover. To investigate this, we present a classification algorithm that is used to extract the areal fraction of melt ponds from satellite measurements. The special focus of this study is the MOSAiC campaign in summer 2020, where the research vessel Polarstern drifted with an ice floe for 1 year. We can see a separation of this floe into two parts. One of them shows melt pond formation much earlier than the other. This is because of different ice age and surface properties. Additionally, we use the classification algorithm to analyze the differences of melt pond fraction between different dates and regions in the Arctic. Key Points: Algorithm to extract melt pond and open water areas from Sentinel‐2 imagery with maximum uncertainty of 6%Exceptional early melt pond formation on MOSAiC Central Observatory, summer 2020, compared to broader vicinityHigh spatial and temporal variability of melt pond fraction on local and regional scales [ABSTRACT FROM AUTHOR]

Previous studies have found inconsistent responses of the North Atlantic jet to Arctic sea‐ice loss. The response of wintertime atmospheric circulation and surface climate over the North Atlantic‐European region to future Arctic sea‐ice loss under 2°C global warming is analyzed, using model output from the Polar Amplification Model Intercomparison Project. The models agree that the North Atlantic jet shifts slightly southward in response to sea‐ice loss, but they disagree on the sign of the jet speed response. The jet response induces a dipole anomaly of precipitation and storm track activity over the North Atlantic‐European region. The changes in jet latitude and speed induce distinct regional surface climate responses, and together they strongly shape the North Atlantic‐European response to future Arctic sea‐ice loss. Constraining the North Atlantic jet response is important for reducing uncertainty in the North Atlantic‐European precipitation response to future Arctic sea‐ice loss. Plain Language Summary: Variations in the North Atlantic jet affect temperature, precipitation, and storminess in Europe. It is not well understood how the jet and European climate will respond to future sea‐ice loss in the Arctic under human‐caused increases in global temperature. We study how atmospheric circulation and surface climate in winter over the North Atlantic‐European region would respond to future Arctic sea‐ice loss under 2°C global warming, using an unprecedented number of coordinated simulations from different climate models. In many models the North Atlantic jet stream in winter responds by shifting southward, but the response of its speed is less clear. These jet stream changes are found to strongly shape the responses in precipitation and storm track activity. More precise estimates of the jet stream response are key to reducing uncertainty in the North Atlantic‐European precipitation response to future Arctic sea‐ice loss. Key Points: Projected Arctic sea‐ice loss causes a robust equatorward shift of the North Atlantic jet across models, but no robust change in jet speedChanges in jet position and speed strongly shape the European winter surface climate response to projected Arctic sea‐ice lossConstraining the jet response is important for reducing uncertainty in the European precipitation response to future Arctic sea‐ice loss [ABSTRACT FROM AUTHOR]

While previous studies have suggested a substantial role of ozone‐depleting substances (ODSs) in historical climate change, their relative contribution to historical anthropogenic warming has not been quantified before. Analyzing all‐but‐one‐forcing, 20‐member ensembles of historical simulations with a state‐of‐the‐art Earth System Model, we find that over the 1955–2005 period ODSs are responsible for 30% of global warming, 37% of Arctic warming, and 33% of summertime Arctic sea ice loss. Effective Radiative Forcing (ERF) calculations reveal that the global warming response to ODSs per unit of ERF is about 20% larger than for CO2, which may be due to stronger feedbacks and the difference in temporal evolution with ODSs having leveled off and CO2 still increasing in 2005. While the response to both peaks in the Arctic, the ODS ERF opposes Arctic amplification more than the CO2 ERF. Our findings highlight the importance of the Montreal Protocol for mitigating future climate change. Plain Language Summary: Ozone‐depleting substances (ODSs) are chemicals developed in the 1920s and 1930s for use in spray cans, refrigerators and plastic foams. Their commercial use increased rapidly in the 1950s and 1960s, but their phase out is underway since the signing of the Montreal Protocol in the 1987, following the identification of their devastating impact on the stratospheric ozone layer. It is well known that ODSs are powerful greenhouse gases, with the second largest warming effect between 1955 and 2005. However, their relative contribution to past global warming has not been quantified previously using comprehensive climate models. Here we show that ODSs were responsible for roughly a third of late 20th Century global warming, Arctic warming and Arctic sea ice decline. In addition, we find that the impact of ODSs on global temperatures is about 20% larger than expected based on the impacts they have on the radiative balance. The impacts of ODSs peak in the Arctic, while their radiative forcing peaks in the tropics, and thus opposes Arctic warming amplification. These findings enhance our understanding of drivers of past climate change, and highlight the importance of the Montreal Protocol for future climate change mitigation. Key Points: Between 1955 and 2005, global warming from ozone‐depleting substances (ODSs) was more than half of that due to CO2, and about one third of total anthropogenic warmingODSs have been about 20% more effective than CO2 at causing global warming per unit radiative forcingODS warming peaks in the Arctic and is 66% of that due to CO2, while their Effective Radiative Forcing (ERF) opposes Arctic amplification more than the CO2 ERF [ABSTRACT FROM AUTHOR]

Polycyclic aromatic hydrocarbons (PAHs) are continuously released from multiple sources and are prone to long‐range transport. Little is known regarding their presence, transport and fate in remote and deep oceans. Polyethylene passive samplers were hence deployed at deep moorings and surface seawater in the Fram Strait and Canadian Archipelago, as well as in air and surface water of the lower Great Lakes, a potential high‐emission region, to understand the transport of PAHs to the Arctic. Dissolved PAHs showed significantly higher concentrations in the lower Great Lakes than those in the high Arctic. Concentrations of dissolved PAHs (Σ19PAHs) ranged from 33 to 300 pg/L in the Fram Strait; the vertical profiles generally exhibited a decreasing trend toward deep waters, which was potentially influenced by hydrological and biogeochemical processes. PAHs were exported from the Arctic Ocean to the North Atlantic through the Fram Strait and the Davis Strait. Plain Language Summary: Polycyclic aromatic hydrocarbons (PAHs) are continuously released from multiple sources, mainly from combustion processes situated in populated and industrial regions. They are capable of long‐distance transport to reach remote and deep oceans. To better understand PAH transport and fate, polyethylene passive samplers were deployed in deep waters of the Fram Strait, surface seawater of the Canadian Archipelago, as well as in air and surface water of the mid‐latitude Great Lakes. Concentrations of dissolved PAHs in the lower Great Lakes were significantly higher than those in the high Arctic, indicating the presence of emission sources in the Great Lakes. The vertical profiles of dissolved PAHs generally exhibited a "surface enrichment and depth depletion" pattern in the Fram Strait, which was potentially affected by hydrological and biogeochemical processes. Pyrogenic sources were the dominant origin of PAHs in both the Arctic and Great Lakes, with some biomass burning sources possibly from wild fires in the sub‐Arctic boreal forest regions. PAHs were exported from the Arctic Ocean to the North Atlantic, with small fluctuations of mass transport through the Fram Strait due to the continuous release of contaminants in mid‐low latitude regions, as well as those primary and secondary sources within the Arctic. Key Points: Polycyclic aromatic hydrocarbons (PAHs) generally exhibited a surface enrichment and depth depletion pattern throughout the water in the Fram StraitPAHs are released from the Arctic Ocean to the North Atlantic through the deep‐water passage Fram Strait and surface pathway Davis StraitPAHs in the Arctic and Great Lake regions were mainly derived from pyrogenic sources, with the existence of some biomass burning sources [ABSTRACT FROM AUTHOR]

The sizes and shapes of ice crystals influence the radiative properties of clouds, as well as precipitation initiation and aerosol scavenging. However, ice crystal growth mechanisms remain only partially characterized. We present the growth processes of two complex ice crystal habits observed in Arctic mixed‐phase clouds during the Ny‐Ålesund AeroSol Cloud ExperimeNT campaign. First, are capped‐columns with multiple columns growing out of the plates' corners that we define as columns on capped‐columns. These ice crystals originated from cycling through the columnar and plate temperature growth regimes, during their vertical transport by in‐cloud circulation. Second, is aged rime on the surface of ice crystals having grown into faceted columns or plates depending on the environmental conditions. Despite their complexity, the shapes of these ice crystals allow to infer their growth history and provide information about the in‐cloud conditions. Additionally, these ice crystals exhibit complex shapes and could enhance aggregation and secondary ice production. Plain Language Summary: Snowflakes formed in the atmosphere have a wide variety of shapes and sizes and no two snowflakes are identical. The reason for this infinite number of shapes is that the environmental temperature and relative humidity prevailing during the snowflakes' growth determine their exact aspects. Thus, the prevailing environmental conditions can be determined from the shape of snowflakes, and become more complicated with increased shape complexity. During a measurement campaign in the Arctic, we identified two complex snowflake types and the history of environmental conditions in which they grew in. We inferred that some snowflakes were recirculating to higher or lower parts of the clouds and that others had collided with cloud droplets that froze on their surface at the early stage of their growth. These snowflakes may enhance the formation of new snowflakes and the initiation of precipitation. Key Points: A large variety of ice crystal sizes and shapes were observed in Arctic mixed‐phase clouds with a holographic imagerThe growth history of two types of complex ice crystals was inferred from their shapesThese ice crystals could enhance aggregation and secondary ice production [ABSTRACT FROM AUTHOR]

The Arctic is warming at almost four times the global rate. An estimated sixty percent of greenhouse‐gas‐induced Arctic warming has been offset by anthropogenic aerosols, but the contribution of aerosols to radiative forcing (RF) represents the largest uncertainty in estimating total RF, largely due to unknown preindustrial aerosol abundance. Here, sulfur isotope measurements in a Greenland ice core show that passive volcanic degassing contributes up to 66 ± 10% of preindustrial ice core sulfate in years without major eruptions. A state‐of‐the‐art model indicates passive volcanic sulfur emissions influencing the Arctic are underestimated by up to a factor of three, possibly because many volcanic inventories do not include hydrogen sulfide emissions. Higher preindustrial volcanic sulfur emissions reduce modeled anthropogenic Arctic aerosol cooling by up to a factor of two (+0.11 to +0.29 W m−2), suggesting that underestimating passive volcanic sulfur emissions has significant implications for anthropogenic‐induced Arctic climate change. Plain Language Summary: Sulfate aerosols are particles in the atmosphere that have a net cooling effect on the climate. One of the most uncertain aspects of climate modeling is the abundance of sulfate aerosols during the preindustrial era. Without knowing the amount of sulfate aerosols during the preindustrial, it is difficult to estimate how much anthropogenic sulfate aerosols have offset warming from anthropogenic greenhouse gases. In this study, we examine preindustrial sulfate aerosols in a Greenland ice core. We find that sulfate aerosols from passive (i.e., non‐eruptive) volcanic degassing contribute almost two thirds of preindustrial Arctic sulfate aerosols in years without major volcanic eruptions. We compare this result to a state‐of‐the‐art global model and find that most climate models use a volcanic emissions inventory that underestimates preindustrial passive volcanic sulfur emissions. That volcanic inventory only includes one type of sulfur emission (sulfur dioxide), but studies have shown that volcanoes emit hydrogen sulfide, which can also form sulfate aerosols. We show that higher emissions of volcanic sulfur during the preindustrial era decrease the estimated cooling effect of anthropogenic aerosols during the industrial era. Thus, the underestimate of preindustrial volcanic emissions in current climate models has significant implications for anthropogenic climate change in the Arctic. Key Points: Sulfur isotopes in a Greenland ice core show that passive volcanic degassing contributes 66% of preindustrial Arctic sulfateThe volcanic inventory used by most climate models underestimates passive degassing, possibly due to missing hydrogen sulfide emissionsElevated preindustrial passive volcanic degassing reduces the estimated cooling effect of anthropogenic sulfate in the Arctic [ABSTRACT FROM AUTHOR]

While variations in crustal structure beneath the Denali fault in Alaska are well‐documented, the existence of fault‐correlated structures throughout the entire thickness of the continental lithosphere is not. A new model of shear‐wave velocity structure obtained through joint inversion of surface wave and converted body wave data shows a northward increase in lithospheric thickness and velocity occurring across the Denali fault system. In northern Alaska, a dramatic increase in lithospheric thickness at the southern margin of the Arctic‐Alaska terrane lies in the vicinity of the Kobuk fault system. These correlations support the view that transpressive deformation tends to localize at the margins of thicker, higher‐strength lithosphere. Plain Language Summary: Major faults in Earth's tectonic plates, such as Alaska's Denali fault, begin as brittle fractures of the shallow crust and progress to include ductile shearing of the deeper crust. Changes in tectonic plate thickness or internal temperature have been observed beneath some faults, consistent with feedback between the strength of the deeper plate and the location of the fault. Using global earthquake signals, we built a new 3‐D model of seismic velocity structure throughout Alaska, extending from the surface to hundreds of kilometers in depth. According to the model, the Denali fault coincides with a northward thickening and an apparent abrupt temperature increase within Alaska's plate. Further north, at another boundary between geological provinces near the Kobuk fault, we also find an abrupt thickening of the plate. These relationships are consistent with faults being located near the edges of thicker, stronger regions of the tectonic plates. Key Points: A new model of seismic shear‐wave velocity beneath Alaska was obtained by jointly inverting surface wave and Sp body wave dataThe Denali fault lies just south of the margin of thicker and higher velocity upper plate lithosphere, as does the Kobuk faultThese results support the view that gradients in lithospheric strength can be key to the localization of major continental strike‐slip faults [ABSTRACT FROM AUTHOR]

There are established El Niño‐Southern Oscillation (ENSO) and Quasi‐biennial Oscillation (QBO) teleconnections to the extratropics that alter the strength of the polar vortex. Here, we demonstrate non‐linearity in the stratospheric polar vortex response to ENSO and QBO combined, in climate model simulations and observational data. We show that the combined effect of El Niño and QBO easterly phase (QBO‐E) on the polar vortex is greater than the linear combination of the individual responses to El Niño and QBO‐E separately. Observations support the model results, despite a relatively small sample of observed cases. We propose that non‐linearity in the teleconnection to ENSO and QBO is caused by the combined effects of an increase in wave driving from El Niño and more poleward propagation of wave activity during QBO‐E. Our results have implications for extreme winters when both El Niño and QBO‐E are active. Plain Language Summary: The El Niño‐Southern Oscillation (ENSO) describes cycles of warmer and cooler sea surface temperatures in the tropical Pacific Ocean. The Quasi‐biennial Oscillation (QBO) is a cycle of alternating easterly and westerly winds in the tropical stratosphere, around 15–40 km above ground. Although these climate cycles occur in the tropics, their impacts are felt far outside the tropics. Both ENSO and QBO are known to affect the stratospheric polar vortex, a band of strong winds that encircle the Arctic in winter. Here, we use climate model experiments and observations to quantify the effects of ENSO and QBO on the polar vortex, when these factors occur alone and in combination. Warm ENSO conditions, known as El Niño, and the easterly QBO phase both cause the polar vortex to weaken. We show that the polar vortex weakens more when El Niño and QBO easterly occur together than would be expected by the sum of their individual effects. Our results are relevant to seasonal forecasting of winter weather over Europe and North America, as a weakened polar vortex is often followed by abnormally cold weather. Our results imply that cold winters are more likely when both El Niño and easterly QBO conditions occur together, such as in 2009/10. Key Points: Stronger weakening of the stratospheric polar vortex is found during Quasi‐biennial Oscillation‐easterly phase and El Nino combinedNon‐linear polar vortex weakening is found in both model and observationsThe polar vortex non‐linearity impacts surface pressure and temperature, which has implications for seasonal forecasting [ABSTRACT FROM AUTHOR]

Warming temperatures and increasing disturbance by wildfire and extreme weather events is driving permafrost change across northern latitudes. The state of permafrost varies widely in space and time, depending on landscape, climate, hydrologic, and ecological factors. Despite its importance, few approaches commonly measure and monitor the changes in deep (>1 m) permafrost conditions with high spatial resolution. Here, we use electrical resistivity tomography surveys along two transects in interior Alaska previously disturbed by wildfire and more recently by warming temperatures and extreme precipitation. Long‐term point observations of permafrost depth, temperature, and water content inform geophysical measurements which, in turn, are used to extrapolate interpretations over larger areas and with high spatial fidelity. We contrast gradual loss of recently formed permafrost driven by warmer temperatures and increased snowfall, with rapid permafrost loss driven by changes in air temperature, snow depth, and extreme summer precipitation in 2014. Plain Language Summary: Permafrost, or ground that remains perennially frozen, is thawing across Arctic and sub‐Arctic regions, driven in part by climate warming, wildfire, and changes in the amount and timing of rain and snow. When permafrost thaws, previously frozen carbon can be released to the atmosphere as greenhouse gases, water flow and storage is altered, and community land use and access are impacted. Permafrost landscapes can be mapped over large areas from satellites or airborne remote sensing methods, but only at the surface with limited information obtained at depth. Measurements of deeper permafrost properties are often limited to point observations. We use geophysical measurements to indirectly map and monitor high spatial resolution changes in permafrost characteristics within the ground. Combined with point observations of soil temperature and moisture content, and thaw depths, geophysical measurements help to extend our ability to measure changing permafrost conditions over time. At two nearby transects in interior Alaska, we document the long‐term trajectory of permafrost thaw following wildfire. Our results show similar yet distinct responses in shallow permafrost recovery and more recent degradation, both gradual and rapid, caused by warming temperatures, increased snowfall, and extreme summer rainfall events. Key Points: Changes in the state of permafrost can be highly variable in both space and timeDisturbance or changes in climate and precipitation influence the long‐and short‐term trajectory of permafrost and seasonally frozen groundGeophysical measurements and monitoring complement direct permafrost observations by providing high resolution information at depth [ABSTRACT FROM AUTHOR]

Tropospheric trends in long‐lived source gases N2O and the chlorofluorocarbons cause trends in O3 through changes in their reactive product gases. Transport affects the product gases because it controls the distribution of the long‐lived source gases. We find that large changes in tropical upwelling 10–5 hPa since 2012 have strengthened the northern branch of the upper stratospheric (UpS) transport circulation, dramatically altering the abundances of N2O and its odd nitrogen product gases, NOx and HNO3. Increased upwelling is connected to stronger and more frequent Quasi‐Biennial Oscillation easterly winds at 10 hPa and above. We use simulations with and without time varying MERRA2 meteorology to quantify the impact of dynamical changes on O3 loss via the NOx and ClOx cycles. We find that dynamical impacts on these cycles explain the mid‐stratospheric tropical O3 increase and Arctic UpS O3 decrease since 2005. Plain Language Summary: Changes in the upper stratospheric circulation over the past decade have altered composition between 30 and 40 km altitude. In the tropics, faster ascent carried greater amounts of nitrous oxide (N2O), a gas produced at the surface, to the upper stratosphere. This increased the amount of the ozone‐destroying nitrogen radicals produced from N2O. Most of the extra nitrogen radicals traveled to the Arctic above ∼32 km, where they increased ozone destruction. Below the altitude where the radicals are produced (about 35 km), the faster tropical ascent carries reduced amounts of nitrogen radicals to the middle stratosphere (∼26 to 35 km), leading to an ozone increase. Observations by satellite instruments revealed changes in the composition. Model simulations showed that circulation change caused the composition changes that affected ozone. The circulation change was connected to changes in the tropical winds that circulate around the globe and change from easterly to westerly on a fairly regular basis. During the last 10 years, this long‐standing pattern changed. This could be variability or the start of a trend; it's too soon to tell. Either way, it complicates the identification and attribution of the ozone increases we expect due to international treaties that banned the use of manmade chlorocarbons. Key Points: Tropical upwelling 10–5 hPa increased up to 30% from 2005 to 2021, increasing upper stratospheric N2O and reactive nitrogen productionIncreased upwelling is connected to stronger and more frequent Quasi‐Biennial Oscillation easterlies at 10 hPa and aboveIncreased upwelling changed NOx‐driven O3 losses, increasing tropical O3 from 15 to 7 hPa while reducing Arctic O3 from 15 to 2 hPa [ABSTRACT FROM AUTHOR]

Though thermohaline staircases exist in a large fraction of the Arctic halocline, the interactions of such staircases with shear and turbulence are still largely unexplored. We perform a series of three‐dimensional Direct Numerical Simulations with and without shear and demonstrate the capacity of shear to disrupt Arctic staircases. We force an oscillating shear throughout the domain in order to represent the effects of passing internal waves of wavelengths much larger than the simulated domain. Shear is shown to disrupt staircases when the Richardson number falls below 1/4 for small layer heights (0.5 m thick), but larger layers (1 m thick) are more resistant. We determine the presence and strength of the layers using measures of steppiness from the literature, finding that a metric based on the rms temperature gradient proves most accurate. This work demonstrates that double‐diffusive interfaces can be surprisingly robust, sometimes even maintaining their structure in strong, dynamically unstable shears. Plain Language Summary: In the Arctic, there exists a large mass of relatively warm water that originates from the Atlantic Ocean. Near the top of this watermass, where the temperature decreases rapidly, stacks of layers are present, each about 1–3 m tall, within which temperature and salinity are uniform. These peculiar structures are known as "staircases," and they tend to form in regions that are deep enough that these layers are shielded from the near‐surface ocean turbulence. Because they exist above the warmer water of Atlantic origin and below the cooler water below the sea ice, the heat fluxes through them affect the rate at which heat from the Atlantic water propagates upward. Once this heat passes through these staircases, it inevitably reaches the sea ice and promotes sea‐ice melt. Thus, staircases serve as a gatekeeper protecting the sea ice from the warm water of Atlantic origin. We investigate the sensitivity of these structures to destruction by common wave‐induced motions. Key Points: We establish conditions for the disruption of staircases by strong vertical shear associated with internal wavesThin layers are more easily disrupted by shear than thick onesWe evaluate the efficacy of previous steppiness metrics, finding that the rms temperature gradient yields accurate results [ABSTRACT FROM AUTHOR]

Understanding influence of vegetation on past temperature changes in the Arctic region would help isolate uncertainty and build understanding of its broader climate system, with implications for paleoclimate reconstructions and future climate change. Using an Earth system model EC‐Earth, we conduct a series of simulations to investigate the impact of vegetation‐climate feedback on the Arctic climate during the mid‐Holocene. Results show Arctic greening induced by the warming resulting from stronger orbital forcing, further amplifies the Arctic warming. The increased vegetation contributes 0.33°C of Arctic warming and 0.35 × 106 km2 of Arctic sea ice loss. Increased Arctic vegetation leads to reduced land surface albedo and increased evapotranspiration, both of which cause local warming in spring and summer. The resultant sea ice loss causes warming in the following seasons, with atmospheric circulation anomalies further amplifying the warming. Our results highlight the significant contribution of vegetation‐climate feedback to Arctic climate under natural conditions. Plain Language Summary: Vegetation‐climate feedback is an essential process between the terrestrial biosphere and the atmosphere. Greening of the Arctic can be invoked by increased solar radiation, for example, during the mid‐Holocene (6,000 years ago), or increased greenhouse gas, for example, ongoing global warming. Here we perform simulations of vegetation and climate interactions during the mid‐Holocene and demonstrate the impact of vegetation‐climate feedback on the Arctic climate. We show that compared to the pre‐industrial period (1850 CE), the Arctic region experiences an expansion of vegetation under a warm climate due to increased solar radiation during the mid‐Holocene. The greening leads to reduced land albedo and enhanced evapotranspiration. These changes and resultant sea ice loss, in combination with associated atmospheric circulation changes, further amplify the Arctic warming. These changes alone are responsible for 0.33°C increase in surface air temperature and 0.35 × 106 km2 increase in sea ice loss. Given the facts of observed ongoing Arctic greening in recent decades, our modeling results suggest that the effect of the vegetation‐climate feedback will amplify the future Arctic warming and sea ice loss even more. Key Points: The Earth system model EC‐Earth reproduced the expansion of vegetation in northern high latitudes during the mid‐Holocene compared to the PIThe mid‐Holocene Arctic greening contributes 0.33°C increase in annual Arctic warming and 0.35 × 106 km2 of sea ice lossThe increased evapotranspiration and decreased surface albedo due to the Arctic greening amplify the Arctic warming in the growing season [ABSTRACT FROM AUTHOR]

The forecast skill of numerical weather prediction (NWP) models and the intrinsic predictability can be different among weather regimes. Here, we examine the predictability of distinct Pacific‐North American weather regimes during extended boreal summer. The four identified weather regimes include Pacific trough, Arctic low, Arctic high, and Alaskan ridge. The medium range forecast skill of these regimes is quantified in the ECMWF and the National Centers for Environmental Prediction models from the TIGGE project. Based on anomaly correlation coefficient, persistence, and transition frequency, the highest forecast skill is consistently found for the Arctic high regime. Based on the instantaneous local dimension and persistence from a dynamical systems analysis, the Arctic high regime has the highest intrinsic predictability. The analysis also suggests that overall, the Pacific trough regime has the lowest intrinsic predictability. These findings are consistent with the forecast skills of the NWP models, and highlight the link between prediction skill and intrinsic predictability. Plain Language Summary: Midlatitude circulation is characterized by chaotic dynamics, which makes weather prediction difficult. Due to the impact of the recurring large‐scale patterns (weather regimes) on extreme events, we need to measure (and improve) the numerical weather predictions' skill for these regimes. In this study, we have identified the summertime weather regimes over the Pacific‐North American region during extended summer (June–September). Then, we measure prediction skill associated with each of the identified regimes in two leading operational weather forecast models. We have found that the forecast models have the highest prediction skill for the regime with the high‐pressure system over the Arctic. Our results indicate a connection between the prediction skill in the forecast models and the complexity and persistence of each weather regime, quantified using a dynamical systems analysis. Key Points: We identified four summertime weather regimes over Pacific‐North America and their corresponding surface impactsNumerical weather prediction models have the highest prediction skills for a regime associated with the Arctic highPrediction skills for these weather regimes are linked to their intrinsic predictability via dynamical systems analysis [ABSTRACT FROM AUTHOR]

Based on statistical analysis using observations and idealized model simulations, previous studies have revealed the potential response of early‐winter atmospheric circulation and temperature anomalies to November Ural blocking (UB) anomalies. Using a large number of coupled simulations, this study found that the response is sensitive to the intensity of November mid‐latitude westerly jet over Eurasia. Stronger‐than‐normal November UB without a significantly weakened westerly jet could not cause significant atmospheric response in early‐winter. By contrast, stronger‐than‐normal November UB with a significantly weakened jet would be followed by a warmer Arctic‐colder Eurasia (WACE) pattern in December. The significantly weakened westerly jet favors stronger upward propagation of planetary waves, which causes stronger weakening and longer persistence of the stratospheric polar vortex. This stratospheric response persists into December and propagates downward into the troposphere interfering with planetary waves (especially wavenumber‐1). The lead‐lag UB‐WACE linkage modulated by mid‐latitude jet may have implications for sub‐seasonal predictability. Plain Language Summary: Observations and idealized model simulations have shown that strong Ural blocking (UB) anomalies in November can induce the "warmer Arctic, colder Eurasia" anomaly in the following December. In this study, a large number of coupled simulations are employed. The results show that the impact of November UB on early‐winter Arctic‐Eurasian temperature is sensitive to the intensity of November mid‐latitude (around 60°N) westerly jet over Eurasia. When November UB anomalies are accompanied by a significantly weakened mid‐latitude westerly jet, early‐winter would experience a warmer Arctic‐colder Eurasia pattern. The significantly weakened westerly wind waveguide is favorable for stronger upward propagation of planetary waves caused by UB anomalies, which leads to persistent atmospheric response in the following December. Key Points: Early‐winter atmospheric response to November Ural blocking (UB) anomalies is sensitive to the background state of westerly jetStrong UB with sufficiently weakened westerly jet in November can induce a warmer Arctic‐colder Eurasia pattern in DecemberThe weakened westerly wind waveguide promotes stronger upward propagation of planetary waves forced by UB anomalies [ABSTRACT FROM AUTHOR]

Multidecadal variability of Atlantic Meridional Overturning Circulation (AMOC) has been reconstructed by various proxies, simulated in climate models, and linked to multidecadal Arctic salinity variability. Here we construct a simple conceptual model to understand the two‐way interactions of the Arctic with multidecadal AMOC variability through a delayed oscillator mechanism. We revise Stommel's Two‐Box Model by including an advective time delay for the Arctic density/salinity anomalies to reach the subpolar North Atlantic and a coupled negative feedback between the AMOC and the freshwater flux entering the Arctic through atmosphere and/or sea ice responses. Self‐sustained multidecadal AMOC oscillations exist in the revised Stommel's Two‐Box model if the oceanic advective time delay is longer than the oscillation threshold, and the periods of the AMOC delayed oscillator depend crucially on this advective time delay. The coupled freshwater feedback provides additional delayed negative feedback and reduces the advective time delay threshold required for the oscillations. Plain Language Summary: Stommel's Two‐Box Model provides a pioneering and powerful theoretical framework to study the mechanisms of steady Atlantic Meridional Overturning Circulation (AMOC) states and abrupt AMOC changes. However, Stommel's Two‐Box Model itself does not include a self‐sustained multidecadal AMOC oscillation solution. In our study, we revise Stommel's Two‐Box model by considering the delayed oceanic advective time lag for the Arctic density/salinity anomalies to reach the subpolar North Atlantic and the dependence of the freshwater flux entering the Arctic on the AMOC strength. The revised Stommel's Two‐Box Model is able to obtain the AMOC delayed oscillator at multidecadal timescales and suggests the important role of the Arctic salinity anomalies and associated delayed negative feedback in the multidecadal AMOC variability. The regimes and multidecadal periods of the AMOC delayed oscillator depend crucially on the advective time scale of the Arctic signal reaching the subpolar North Atlantic. The AMOC‐related coupled freshwater feedback provides additional delayed negative feedback and reduces the threshold of the advective time delay needed for the multidecadal AMOC oscillations. Key Points: Multidecadal Atlantic Meridional Overturning Circulation (AMOC) variability exists in revised Stommel's Two‐Box Model with advective time delay and coupled freshwater feedback includedRegimes/periods of the AMOC delayed oscillator depend on the advective time lag of Arctic salinity signal and freshwater feedback strengthThe model suggests an important role of the Arctic salinity and delayed negative freshwater feedback in the multidecadal AMOC variability [ABSTRACT FROM AUTHOR]

Mixed‐phase clouds (MPCs), which consist of both supercooled cloud droplets and ice crystals, play an important role in the Earth's radiative energy budget and hydrological cycle. In particular, the fraction of ice crystals in MPCs determines their radiative effects, precipitation formation and lifetime. In order for ice crystals to form in MPCs, ice‐nucleating particles (INPs) are required. However, a large‐scale relationship between INPs and ice initiation in clouds has yet to be observed. By analyzing satellite observations of the typical transition temperature (T*) where MPCs become more frequent than liquid clouds, we constrain the importance of INPs in MPC formation. We find that over the Arctic and Southern Ocean, snow and sea ice cover significantly reduces T*. This indicates that the availability of INPs is essential in controlling cloud phase evolution and that local sources of INPs in the high‐latitudes play a key role in the formation of MPCs. Plain Language Summary: Mixed‐phase clouds (MPCs), which consist of both liquid droplets and ice crystals, play an important role for the Earth's climate system. For example, the number of ice crystals in MPCs determines how much sunlight is reflected by the cloud and how efficiently the cloud can form precipitation. The formation of ice crystals in MPCs requires a special subset of aerosol particles called ice‐nucleating particles (INPs). INPs are required for liquid cloud droplets to freeze at temperatures warmer than −36°C. However, a large‐scale relationship between INPs and ice formation in clouds has yet to be observed. Using satellite observations, we determine the transition temperature (T*) where MPCs become more frequent than liquid clouds and find that T* is strongly dependent on snow and sea ice cover over the Arctic and Southern Ocean. This indicates that sea ice and snow cover act as a lid that inhibits the emission of INPs from the ocean. In a warming world with retreating sea ice and snow cover, our results suggest that clouds in these regions will contain ice crystals at warmer temperatures than previously estimated and, thus, have potential implications for future warming predictions. Key Points: Ice‐nucleating particles (INPs) control ice formation in high‐latitude cloudsSea ice and snow cover inhibit the local emission of INPs, which directly influences cloud phase in the Arctic and Southern OceanThis has implications for the predicted negative cloud phase feedback with future warming and the associated sea ice and snow cover loss [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]

The thick multiyear sea ice that once covered large parts of the Arctic is increasingly being replaced by thinner and weaker first‐year ice, making it more vulnerable to breakup by winds. We use the neXtSIM sea ice model to investigate the driving mechanisms behind a large breakup event in the Beaufort Sea during winter 2013. Our simulations are the first to successfully reproduce the timing, location, and propagation of sea ice leads associated with wind‐driven breakup and highlight the importance of accuracy of the atmospheric forcing, sea ice rheology, and changes in sea ice thickness. We found that the breakup resulted in enhanced export of multiyear ice from the Beaufort Sea. Overall, this leads to a relatively thinner and weaker simulated ice cover that potentially preconditions earlier breakup in spring and accelerates sea ice loss. Finally, our simulations indicate that large breakup events could become more frequent as Arctic sea ice continues to thin. Plain Language Summary: The loss of thick multiyear sea ice in the Arctic leads to weaker sea ice that is more easily broken up by strong winds. As a consequence, extreme sea ice breakup events may become more frequent, even during the middle of winter when the sea ice cover is frozen solid. This can lead to an earlier onset of the melt season and potentially accelerate Arctic sea ice loss. Such extreme breakup events are generally not captured by climate models, potentially limiting our confidence in projections of Arctic sea ice. We investigated the driving forces behind sea ice breakup events during winter and how they change in a future climate. Our sea ice model is the first to reproduce such breakup events and reveals that the combination of strong winds and thin sea ice is a key factor for these breakups. We found that winter breakups have a large effect on local heat and moisture transfer and cause enhanced sea ice production, but also increase the overall movement of the sea ice cover, making it more vulnerable. Finally, we show that if the Arctic sea ice continues to thin, these extreme breakup events could become even more frequent. Key Points: An extreme winter breakup event in the Beaufort Sea is accurately simulated with the neXtSIM sea ice modelHigh‐resolution and skillful atmospheric forcing, as well as appropriate sea ice rheology, are necessary to simulate such breakupsIn the model, thinning Beaufort Sea ice is more vulnerable to breakup, which may accelerate loss of multiyear ice [ABSTRACT FROM AUTHOR]

Using ERA5 reanalysis we find positive trends in poleward transport of moisture and heat during 1979–2018 over the winter Barents Sea sector and summer East Siberian Sea sector. The increase in blocking occurrence (blocking days) can explain these trends. Blocking occurrence over the Barents Sea sector significantly increased in the last 40 winters, inducing increasingly stronger poleward transport of moisture and heat. The high linear correlation between poleward energy transports and temperature over the Barents Sea sector suggests that poleward energy transports dominate the regional warming trend there. Meanwhile, in summer, more frequently occurring blocking over the Beaufort Sea sector causes a positive trend of poleward moist and heat transport over the East Siberian Sea sector. The high linear correlation between the blocking occurrence and temperature suggests that the increasing shortwave radiation and subsidence within the more frequently occurring blocking contribute to the regional warming trend. Plain Language Summary: During last 40 year, Anticyclones become more frequent over the Arctic. To the west of these more frequently occurring Anticyclones, warm and moist air are transported into the Arctic region more frequently. In winter, these more frequent transports of moisture and heat into the Arctic lead to the amplified regional warming trend over the Barents Sea. However, these transports do not contribute significantly to the summer regional warming trend. Instead, the amplified summer regional warming always occurs over the region with more frequently occurring anticyclones, suggesting that the increasing solar radiation and subsidence within the more frequently occurring anticyclones lead to the summer regional warming trend. Key Points: The more frequently occurring blocking anticyclones contribute to the increasing poleward energy transport during last 40 yearIn winter, this increasing poleward energy transport leads to regional warming trend over the Barents SeaIn summer, regional warming trend is dominated by the subsidence and solar radiation inside the more frequently occurring blocks [ABSTRACT FROM AUTHOR]

On 25 February 2022 Antarctic sea ice extent dropped to a satellite‐era record low level of 1.92 × 106 km2, 0.92 × 106 km2 below the long‐term mean. The area of sea ice was also at a record low level of 1.24 × 106 km2. Although no individual sector was at a record low, at the minimum there were negative sea ice anomalies in all sectors of the Southern Ocean, with the largest in the Ross (contributing 46%) and Weddell Seas (26%). The Amundsen Sea Low had a record low depth in October/November 2021, with a series of very deep depressions giving strong offshore winds. These accelerated ice loss during the melt season, creating a 1.00 × 106 km2 coastal polynya in the Ross Sea. In the northern Weddell Sea, westerly winds of record strength led to ice export from the region. Plain Language Summary: Sea ice is a critical part of the Antarctic climate system that is an important breeding habitat for seals and other marine biota, as well as playing an important part in the global ocean circulation. Unlike the Arctic, where sea ice extent has decreased over recent decades, sea ice around the Antarctic actually increased in extent for a large part of the record starting in the late 1970s. However, on 25 February 2022 the extent dropped to a record low level of 1.924 million square kilometers, 1 million square kilometers below the long‐term average. The origins of the sea ice loss can be traced back to extremely deep storms in the Ross Sea in October and November 2021, and the very strong southerly winds that the storms had on their western flank. These moved sea ice away from the Antarctic coast, exposing the ocean and allowing solar heating to warm the ocean and give further sea ice melt. An additional factor was the very strong westerly winds north of the Weddell Sea that moved sea ice out of this basin and toward the east. Key Points: Antarctic sea ice extent dropped to a record low level of 1.92 × 106 km2 on 25 February 2022There were negative sea ice anomalies in all sectors of the Southern Ocean, with the largest in the Ross and Weddell SeasDeep storms in October/November 2021 led to low sea ice concentration and a large coastal polynya that accelerated sea ice loss [ABSTRACT FROM AUTHOR]

The wind profiles measured by the Aeolus satellite mission are unique and valuable wind products for numerical weather prediction. However, just like any other remote sensing measurements, it has a footprint extending over a number of model grid cells, especially in high‐resolution mesoscale models. The spatial representation of Aeolus Rayleigh‐clear observations has been assessed in a mesoscale limited‐area model called AROME‐Arctic by using a footprint observation operator. The footprint representation provides small, but consistent reduction in the standard deviation of background departures and an observing system experiment comparing the default and the footprint operator based on Aeolus data assimilation showed a small positive impact on AROME‐Arctic forecasts. Plain Language Summary: The Aeolus satellite mission provides unique and pioneering wind measurements in a global distribution that helps to unveil the wind structures of sparsely observed regions like the Arctic. These observations are also very useful for improving weather prediction, however, the use of Aeolus data is usually conservative and imperfect. In this study, the added value and advanced use of Aeolus wind observations are presented and discussed in an Arctic weather prediction model. Key Points: The footprint of Aeolus wind profiles may extend over many grid points of a high‐resolution numerical weather prediction modelThe footprint can be represented through the observation operator in data assimilation to improve the use of Aeolus data in the analysisThe applied footprint operator helps to extend the observation impact in forecast lead time and to improve slightly the forecast quality [ABSTRACT FROM AUTHOR]

The global warming potential of Ozone‐depleting substances (ODS) has long been known to be thousands of times larger than the one of CO2, but their climate impacts as greenhouse gases, i.e. unmediated ozone depletion, has received relatively little attention. Focusing on the period 1955–2005, we here present results from offline radiative forcing (RF) calculations from a global chemistry climate model. Using realistic distributions of ODS and consistent stratospheric ozone, we show that ODS dominate the adjusted stratospheric warming of the lower stratosphere, where CO2 has little radiative impact. We also show that the global mean RF of stratospheric ozone only cancels a fraction of the RF of ODS, leaving an important ODS contribution to anthropogenic forcing. Finally we show that the RF of ODS opposes Arctic amplification, its equator‐to‐pole gradient being larger than the one of CO2. Plain Language Summary: In the decades following World War II, organic compounds of chlorine and bromine, widely used in refrigerators and spray cans, entered the atmosphere and led to the formation of the ozone hole. However, these compounds, are also powerful greenhouse gases and are important for global warming. Here we study their warming effects in the stratosphere and at the surface. We find that, over the period 1955–2005, they were the dominant atmospheric gas warming the tropical lower stratosphere, where CO2 is largely inactive; that their surface warming effect (their radiative forcing) amounted to approximately one third of the CO2 value, even after accounting for reductions due to the ozone depletion they induce; and, finally that, even more than CO2, their radiative effects warmed the equatorial more the polar regions and, as such, cannot be the reason why the Arctic is warming more than the rest of the planet. Key Points: The radiative effect of Ozone‐depleting substances on lower stratospheric temperatures is the largest of all well‐mixed greenhouse gasesTheir radiative forcing is only partially (∼25%) canceled by the stratospheric ozone depletion they induceTheir radiative forcing is weaker at the pole than at the equator opposing Arctic amplification even more than CO2 forcing [ABSTRACT FROM AUTHOR]