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The Arctic is impacted by some of the fastest temperature changes observed on Earth, but the impact on the terrestrial arthropod fauna is unclear. Acute physiological thermal limits of terrestrial ectotherms from high latitudes often exceed the local air temperatures, suggesting that they may be able to cope with increasing temperatures. However, knowledge on how Arctic terrestrial arthropods cope with elevated temperatures for longer periods is lacking.Here we investigate how acclimation temperature and exposure time affect the acute physiological heat tolerance of five terrestrial arthropod species (Neomolgus littoralis, Megaphorura arctica, Nysius groenlandicus, Psammotettix lividellus and Nabis flavomarginatus) immediately after collection in Arctic and sub‐Arctic habitats.We show that although acute heat tolerances are relatively high, even exposure to moderate (temperature span assessed ca. 3–29°C) acclimation temperatures for a 24 h period have strong negative effects on heat tolerance for four of the five species. Similarly, exposure time negatively affected heat tolerance, but depending on species and temperature.Together our results suggest that exposure to even moderately elevated temperatures for periods of 24 h or even shorter can lead to lower acute heat tolerance for cold adapted terrestrial arthropod species from sub‐Arctic and Arctic regions. Consequently, climate change leading to extended periods of mildly elevated temperatures may have strong negative effects on these species. We argue that this aspect is currently overlooked when assessing the ability of arthropods from Arctic and sub‐Artic regions to cope with climate changes as such predictions are typically based on acute heat tolerance estimates and with the assumption of beneficial acclimation responses. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

A significant and striking seesaw pattern of winter surface air temperature (SAT) has emerged, featuring pronounced warming Arctic and cooling Eurasian (referred to as WACE). This study investigates the subseasonal SAT modes across the mid‐ and high‐latitudes of Eurasia and their possible mechanisms based on daily reanalysis data from 1979 to 2022. Our results reveal that Eurasian winter SAT exhibits two distinct subseasonal modes, characterized by a correlated southeastward propagation of temperature and geopotential height anomalies (GHAs) in the middle and lower troposphere. Notably, the subseasonal SAT anomalies with eight phases constrained by the hydrostatic equilibrium, originate from the GHAs in the Arctic stratosphere and then transfer to the East Asia. The sixth phase of the transmitted subseasonal SAT mode is proved to be the key transition phase from the WACE pattern to its counterpart. Further analysis indicates that the strength of the transmitted subseasonal SAT mode is controlled by the tripolar sea surface turbulent heat flux anomalies over the north Atlantic. Plain Language Summary: Over recent decades, Earth's changing climate has brought about some significant temperature anomalies, particularly in the Arctic and mid‐latitude regions. This has led to severe socio‐ecological consequences, including increased damage to our ecosystems. A noticeable pattern in winter temperature is the warm Arctic‐cold Eurasian mode, which has been observed on multiple time scales. Here we show, on the subseasonal time scale, during the winter in Eurasia, there are two different patterns of temperature changes, and they move together toward the southeast in the troposphere. One of these patterns, called WACE, goes through a repeating cycle from the Arctic to East Asia. We specifically looked at the reversal phase of this cycle, where we found that changes in the stratosphere above the Arctic region kickstart the process, and then the turbulent heat near the surface contribute to the changes in the polar region by triggering a Rossby wave. Key Points: The detailed southeastward propagation of a transmitted subseasonal Eurasia winter surface air temperature (SAT) mode is revealedThe subseasonal SAT mode originates from the geopotential height anomaly in Arctic stratosphere constrained by the hydrostatic equilibriumThe strength of the subseasonal SAT mode is controlled by the tripolar sea surface turbulent heat flux anomalies over the North Atlantic [ABSTRACT FROM AUTHOR]

Diagnosing the role of internal variability over recent decades is critically important for both model validation and projections of future warming. Recent research suggests that for 1980–2022 internal variability manifested as Global Cooling and Arctic Warming (i‐GCAW), leading to enhanced Arctic Amplification (AA), and suppressed global warming over this period. Here we show that such an i‐GCAW is rare in CMIP6 large ensembles, but simulations that do produce similar i‐GCAW exhibit a unique and robust internally driven global surface air temperature (SAT) trend pattern. This unique SAT trend pattern features enhanced warming in the Barents and Kara Sea and cooling in the Tropical Eastern Pacific and Southern Ocean. Given that these features are imprinted in the observed record over recent decades, this work suggests that internal variability makes a crucial contribution to the discrepancy between observations and model‐simulated forced SAT trend patterns. Plain Language Summary: When comparing model simulations of Earth's recent warming to real‐world observations, differences may arise from several factors. Two important factors are the model errors in the simulated response to increased greenhouse gases, and natural fluctuations within the climate system that produced discrepancies between observations and models. Thus, quantifying the role of these natural fluctuations is important for the assessment of model‐observation differences. Previous studies have shown that natural climate variability has depressed global warming and enhanced Arctic warming. By compositing the multi‐decadal trend patterns from CMIP6 simulations in which natural variability warms the Arctic but has a global cooling effect, we find that the majority of these model simulations also produce enhanced warming in the Barents and Kara Seas and cooling in the Tropical Eastern Pacific and Southern Ocean due to natural variability. Since these are the exact features imprinted on observed surface temperature changes over 1980–2022, our work suggests that natural variability is an important component of several noteworthy differences between models and observations. Key Points: Internal variability has enhanced Arctic warming but suppressed global warming over 1980–2022This manifestation of internal variability is rare in model simulations but has a robust global surface air temperature (SAT) trend patternThis internal SAT pattern features warming in the Barents and Kara Sea and cooling of the Tropical Eastern Pacific and Southern Ocean [ABSTRACT FROM AUTHOR]

Arctic warming has significant environmental and social impacts. Arctic long‐term warming trend is modulated by decadal‐to‐multidecadal variations. Improved understanding of how different external forcings and internal variability affect Arctic surface air temperature (SAT) is crucial for explaining and predicting Arctic climate changes. We analyze multiple observational data sets and large ensembles of climate model simulations to quantify the contributions of specific external forcings and various modes of internal variability to Arctic SAT changes during 1900–2021. We find that the long‐term trend and total variance in Arctic‐mean SAT since 1900 are largely forced responses, including warming due to greenhouse gases and natural forcings and cooling due to anthropogenic aerosols. In contrast, internal variability dominates the early 20th century Arctic warming and mid‐20th century Arctic cooling. Internal variability also explains ∼40% of the recent Arctic warming from 1979 to 2021. Unforced changes in Arctic SAT are largely attributed to two leading modes. The first is pan‐Arctic warming with stronger loading over the Eurasian sector, accounting for 70% of the unforced variance and closely related to the positive phase of the unforced Atlantic Multidecadal Oscillation (AMO). The second mode exhibits relatively weak warming averaged over the entire Arctic with warming over the North American‐Pacific sector and cooling over the Atlantic sector, explaining 10% of the unforced variance and likely caused by the positive phase of the unforced Interdecadal Pacific Oscillation (IPO). The AMO‐related changes dominate the unforced Arctic warming since 1979, while the IPO‐related changes contribute to the decadal SAT changes over the North American‐Pacific Arctic. Plain Language Summary: The Arctic warms much faster than the rest of the world, leading to significant local and remote influences. Warming in the Arctic is not uniform over time, with decadal‐to‐multidecadal variations upon the long‐term trend. The changes in Arctic surface air temperature (SAT) can be attributed to either instrinct variability within the climate system or external forcings including anthropogenic factors such as greenhouse gases emission and natural factors such as volcanic eruptions. Understanding of the relative contributions of internal variability and external forcing to observed changes in Arctic SAT is crucial for improving Arctic climate projections in coming decades. By synthesizing multiple observational data sets and large‐ensemble climate simulations, we find that the Arctic experienced long‐term warming with some periods of slowdown in response to external forcing, which largely explains the overall change since 1900. Internal variability, particularly the multidecadal oscillation in the North Atlantic, dominates the early 20th century warming and mid‐20th century cooling and significantly contributes to the recent rapid warming since 1979. A regression‐based rescaling method removes systematic biases in model‐simulated response (in comparison with observations), ensuring that our results are not influenced by the choice of climate models, as long as they are under the same historical forcing. Key Points: Externally forced Arctic warming dominates the trend and variance in Arctic surface air temperature during 1900–2021Most of the internally generated Arctic temperature changes are related to the unforced Atlantic Multidecadal OscillationInternal variability explains 40% of the Arctic warming from 1979 to 2021, while greenhouse gases and natural forcings account for the rest [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]

Water quality and freshwater ecosystems are affected by river discharge and temperature. Models are frequently used to estimate river temperature on large spatial and temporal scales due to limited observations of discharge and temperature. In this study, we use physically based river routing and temperature models to simulate daily discharge and river temperature for rivers in 138 basins in Alaska, including the entire Yukon River basin, from 1990–2021. The river temperature model was optimized for ice free months using a surrogate‐based model optimization method, improving model performance at uncalibrated river gages. A common statistical model relating local air and water temperature was used as a benchmark. The physically based river temperature model exhibited superior performance compared to the benchmark statistical model after optimization, suggesting river temperature model optimization could become more routine. The river temperature model demonstrated high sensitivity to air temperature and model parameterization, and lower sensitivity to discharge. Validation of the models showed a Kling‐Gupta Efficiency of 0.46 for daily river discharge and a root mean square error of 2.04°C for daily river temperature, improving on the non‐optimized physical model and the benchmark statistical model, which had root mean square errors of 3.24 and 2.97°C, respectively. The simulation shows that rivers in northern Alaska have higher maximum summer temperatures and more variability than rivers in the Central and Southern regions. Furthermore, this framework can be readily adapted for use across models and regions. Plain Language Summary: Accurate data on the volume and temperature of river water are essential for understanding how changing river conditions affect water quality and freshwater ecosystems. However, direct measurements of river parameters are often lacking, leading researchers to rely on models for estimation. In this study, we utilized advanced models and techniques to compute daily water volume and temperature in 138 basins across Alaska, including the entirety of the Yukon River basin, spanning from 1990 to 2021. Our findings indicated that rivers in northern Alaska exhibited higher maximum summer water temperatures and more significant temperature fluctuations compared to those in the central and southern regions. Our analysis highlighted that adjusting air temperature and the model's internal variables were crucial in minimizing errors in river temperature prediction. We improved the accuracy of the river temperature model by applying a technique to refine the model output based on the limited available river measurements. Comparing our enhanced model to a simpler statistical approach, we observed superior performance once the necessary adjustments were implemented. Key Points: Our model system produced an accurate, high‐resolution, daily hindcast of Alaskan river temperature and discharge from 1990 to 2021We increased model performance by employing a new optimization of the River Basin Model and forcing it with a climate‐land surface modelA sensitivity analysis highlights important drivers of river temperatures in each region and the need for optimization [ABSTRACT FROM AUTHOR]

Global warming is destabilizing the cryosphere, with consequences for glaciers, permafrost, sea ice and lake ice. Polar lakes have short ice‐free seasons, and small changes in ice cover duration have the potential to provoke alterations to ecosystem structure. However, these lakes are understudied, and the consequences for mixing regimes, thermal structures and biogeochemical processes remain unclear. We measured three annual cycles of dissolved oxygen, temperature and specific conductivity in a lake at ∼83°N to investigate limnological processes and their interannual variability. There were sharp interannual contrasts in lake dynamics, with state shifts in mixing, stratification and oxygen regimes due to air temperature variability and meteorological events. We also observed unusual thermal profiles that were associated with solute gradients. These striking differences underscore the sensitivity of high Arctic lakes to interannual variations in meteorological forcing, and their susceptibility to regime shifts in response to ongoing global change. Plain Language Summary: Lakes are biodiversity refuges, climate regulators and providers of ecosystem services. High Arctic lakes experience brief summer ice‐free periods and their annual dynamics remain largely unexplored despite their location in one of the most rapidly warming regions on Earth. In particular, patterns of thermal structure and oxygen dynamics have rarely been measured. We studied three complete annual cycles in a coastal lake less than 100 km south of the northernmost land on Earth. The observed limnological dynamics highlight the potential for rapid regime shifts in polar lakes and underline their sensitivity to interannual differences in environmental conditions. Key Points: Pronounced shifts in lake oxygen and temperature dynamics occur due to interannual air temperature variation and meteorological episodesDivergent annual trajectories in lake structure and functioning highlight the vulnerability of high Arctic lakes to climate change [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]

Since 1980, the Arctic surface has warmed four times faster than the global mean. Enhanced Arctic warming relative to the global average warming is referred to as Arctic Amplification (AA). While AA is a robust feature in climate change simulations, models rarely reproduce the observed magnitude of AA, leading to concerns that models may not accurately capture the response of the Arctic to greenhouse gas emissions. Here, we use CMIP6 data to train a machine learning algorithm to quantify the influence of internal variability in surface air temperature trends over both the Arctic and global domains. Application of this machine learning algorithm to observations reveals that internal variability increases the Arctic warming but slows global warming in recent decades, inflating AA since 1980 by 38% relative to the externally forced AA. Accounting for the role of internal variability reconciles the discrepancy between simulated and observed AA. Plain Language Summary: The Arctic has been warming four times as quickly as the global mean since 1980. This so‐called Arctic Amplification (AA) has unprecedented impacts on Arctic environments and livelihoods. AA is robustly simulated by climate models, but simulations rarely reproduce the observed levels of AA for 1980–2022. This may be due to a model misrepresentation of the Arctic's sensitivity to increasing greenhouse gases. Another possibility is that the large, observed value of AA is inflated by natural fluctuations in the climate system. Here, we use machine learning to quantify the contribution of natural fluctuations to observed AA. We show that natural fluctuations have inflated AA by 38%, and thus reconcile model‐observation differences and suggest that the observed large AA over 1980 to present would not persist into the future. Key Points: Internally generated and externally forced temperature trends over the Arctic and globe can be partitioned using machine learning methodsInternal variability has enhanced Arctic warming while damping global warming over 1980‐2022Accounting for internal variability in observations reconciles discrepancies between simulated and observed Arctic Amplification [ABSTRACT FROM AUTHOR]

Arctic sea‐ice loss is influenced by multiple positive feedbacks, sparking concerns of accelerated loss in the coming years or even a tipping point, where a sea‐ice equilibrium disappears at a given CO2 value and sea ice rapidly evolves to a new steady state. Such a tipping point would imply a bi‐stability of the Arctic climate—where multiple steady‐state Arctic climates are possible at the same CO2 value. Previous works have sought to establish the existence of bi‐stability using a range of models, from zero‐dimensional sea ice thermodynamic models to fully coupled global climate models, with conflicting results. Here, we present a new model of the Arctic that includes both sea‐ice thermodynamics and key atmospheric feedbacks in a simple framework. We exploit the model's simplicity to identify physical mechanisms that control the timing and extent of sea‐ice bi‐stability, and the abruptness of ice loss. We show that longwave radiation feedbacks can have a strong influence on Arctic surface climate from atmospheric temperature increases alone, even without major contributions from clear‐sky moisture or convective clouds suggested previously. While winter sea‐ice bi‐stability is robust to changes in uncertain model parameters in this study, summer sea ice is more sensitive. Finally, our model indicates that positive feedbacks may modulate the CO2 threshold of sea‐ice loss and the width of bi‐stability much more strongly than the abruptness of loss. These results lead to a comprehensive understanding of the conditions that favor Arctic sea‐ice bi‐stability, particularly the role of atmospheric feedbacks, in both future and past climates. Plain Language Summary: Arctic sea ice is declining rapidly under global warming, threatening high‐latitude communities and ecologies. Some mechanisms may cause this sea ice loss to accelerate, leading to concerns about the possibility of a sea ice "tipping point," in which ice is lost very abruptly and irreversibly at a threshold value of CO2. Previous works have used a range of tools, from simple sea ice thermodynamic models to state‐of‐the‐art global climate models, to identify whether such a tipping point exists and have found conflicting results. In this work, we present a novel model of the Arctic climate that combines a thermodynamic model of sea ice with atmospheric feedbacks in a simple framework. We run this model across large ranges of climatic conditions to broadly identify the conditions that favor a sea ice tipping point. In addition, we isolate the mechanisms that are key to setting the timing and abruptness of complete sea ice loss, separating the contributions of different atmospheric feedbacks that have previously been unexplored. We find that both summer and winter sea ice tipping points are possible and that the responsible atmospheric mechanisms are different than those that have been suggested previously. Key Points: Winter sea ice bi‐stability is very robust across model parameters, while summer sea ice bi‐stability exists in narrower parameter regimesAtmospheric feedbacks determine the width of the model sea‐ice bi‐stability and the CO2 value at which Arctic sea ice loss occursLongwave feedbacks–a key contributor to the model bi‐stability–are driven more by tropospheric temperature than by clouds or moisture [ABSTRACT FROM AUTHOR]

Changes in ice‐sheet size impact atmospheric circulation, a phenomenon documented by models but constrained by few paleoclimate records. We present sub‐centennial‐scale records of summer temperature and summer precipitation hydrogen isotope ratios (δ2H) spanning 12–7 ka from a lake on Baffin Island. In a transient model simulation, winds in this region were controlled by the relative strength of the high‐pressure systems and associated anticyclonic circulation over the retreating Greenland and Laurentide ice sheets. The correlation between summer temperature and precipitation δ2H proxy records changed from negative to positive at 9.8 ka. This correlation structure indicates a shift from alternating local and remote moisture, governed by the two ice‐sheet high‐pressure systems, to only remote moisture after 9.8 ka, governed by the strong Greenland high‐pressure system after the Laurentide Ice Sheet retreated. Such rapid atmospheric circulation changes may also occur in response to future, gradual ice‐sheet retreat. Plain Language Summary: Continental ice sheets alter atmospheric circulation, influencing global heat and moisture distribution. Records of atmospheric circulation during previous periods of ice‐sheet retreat can provide insights into the changes that are possible in the future. This study examines summer atmospheric circulation in Baffin Bay from 12,000 to 7,000 years ago, a period of dramatic ice‐sheet retreat. Precipitation isotopes reflect moisture source, which responds to changes in air temperature and atmospheric circulation. This study uses records of temperature and precipitation isotopes from the same sediment archive to tease apart the influence of temperature from that of atmospheric circulation. The precipitation isotopes in this record distinct changes in moisture sources, which a climate model simulation suggests was caused by retreating ice sheets. Before about 10 ka, when the Laurentide Ice Sheet (LIS) covered eastern Canada, summer winds in Baffin Bay shifted regularly between south and north, carrying air with unique temperature and precipitation isotope signatures. As the LIS retreated, the Greenland Ice Sheet (GIS) remained relatively large and dominated atmospheric circulation, causing a rapid shift to southeasterly winds. As the GIS retreats in the future, atmospheric circulation may undergo similar rapid changes. Key Points: Summer precipitation isotopes in the Arctic reflect temperature and moisture transport historyPaired records of summer temperature and precipitation isotopes isolate the influence of temperature from that of transportMoisture delivery to the eastern Canadian Arctic changed dramatically due to Early Holocene Laurentide Ice Sheet retreat [ABSTRACT FROM AUTHOR]

Data assimilation of satellite microwave measurements is one of the important keys to improving weather forecasting over the Arctic region. However, the use of surface‐sensitive microwave‐sounding channel measurements for data assimilation or retrieval has been limited, especially during winter, due to the poorly constrained sea ice emissivity. In this study, aiming at more use of those channel measurements in the data assimilation, we propose an explicit method for specifying the surface radiative boundary conditions (namely emissivity and emitting layer temperature of snow and ice). These were explicitly determined with a radiative transfer model for snow and ice and with snow/ice physical parameters (i.e. snow/ice depths and vertical distributions of temperature, density, salinity, and grain size) simulated from the thermodynamically driven snow/ice growth model. We conducted 1D‐Var experiments in order to examine whether this approach can help to use the surface‐sensitive microwave temperature channel measurements over the Arctic sea ice region for data assimilation. Results show that (1) the surface‐sensitive microwave channels can be used in the 1D‐Var retrieval, and (2) the specification of the radiative boundary condition at the surface using the snow/sea ice emission model can significantly improve the atmospheric temperature retrieval, especially in the lower troposphere (500 hPa to surface). The successful retrieval suggests that useful information can be extracted from surface‐sensitive microwave‐sounding channel radiances over sea ice surfaces through the explicit determination of snow/ice emissivity and emitting layer temperature. [ABSTRACT FROM AUTHOR]

Quantitative temperature reconstructions from lacustrine organic geochemical proxies including branched glycerol dialkyl glycerol tetraethers (brGDGTs) and alkenones provide key constraints on past continental climates. However, estimation of air temperatures from proxies can be impacted by non‐stationarity in the relationships between seasonal air and water temperatures, a factor not yet examined in strongly seasonal high‐latitude settings. We pair downcore analyses of brGDGTs and alkenones measured on the same samples through the Holocene with forward‐modeled proxy values based on thermodynamic lake model simulations for a western Greenland lake. The measured brGDGT distributions suggest that stable autochthonous (aquatic) production overpowers allochthonous inputs for most samples, justifying the use of the lake model to interpret temperature‐driven changes. Conventional calibration of alkenones (detected only after 5.5 thousand years BP) suggests substantially larger temperature variations than conventional calibration of brGDGTs. Comparison of proxy measurements to forward‐modeled values suggests variations in brGDGT distributions monotonically reflect multi‐decadal summer air temperatures changes, although the length of the ice‐free season dampens the influence of air temperatures on water temperatures. Drivers of alkenone variability remain less clear; potential influences include small changes in the seasonality of proxy production or biases toward specific years, both underlain by non‐linearity in water‐air temperature sensitivity during relevant seasonal windows. We demonstrate that implied temperature variability can differ substantially between proxies because of differences in air‐water temperature sensitivity during windows of proxy synthesis without necessitating threshold behavior in the lake or local climate, and recommend that future studies incorporate lake modeling to constrain this uncertainty. Plain Language Summary: Reconstructions of past temperature change from the Arctic are necessary to constrain long‐term sensitivity of the region and the Greenland Ice Sheet to climate changes. We collected sediments from a western Greenland lake, which continuously accumulated for the past 9,000 years. In these sediments, we analyzed the chemical compositions of two temperature‐sensitive classes of molecules produced by microorganisms within the lake. Surprisingly, the two proxies suggest different magnitudes of temperature changes when compared using conventional calibration approaches. Although changes in both proxies are often linked to air temperatures, they are likely more directly sensitive to water temperatures, which can differ from air temperatures—particularly in strongly seasonal environments like the Arctic. We use a lake model to simulate changes in lake water temperatures and convert to proxy units, enabling us to compare air and water temperatures to proxy measurements within a common frame of reference. We show that proxy sensitivity to air temperature changes can differ substantially depending on exactly when the proxies are produced. Because air and lake water temperatures during likely periods of production rarely change at the same rate, we suggest that future studies interpreting water temperature‐sensitive proxies should incorporate lake modeling to constrain this uncertainty. Key Points: Downcore branched glycerol dialkyl glycerol tetraethers and alkenone measurements imply different magnitudes of Holocene air temperature variability on western GreenlandLake water temperatures during likely windows of biomarker production do not change at the same rate as air temperaturesLake water temperature‐sensitive proxies are impacted by lake dynamics in seasonal environments [ABSTRACT FROM AUTHOR]

The timing of ice freeze‐up and break‐up in the Arctic may be responding to climate change. Passive microwave remote sensing is a powerful technique for monitoring this timing. We processed low‐frequency microwave time series from the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission for a set of 31 satellite gauging reaches (SGRs) above 65°N between 2010 and 2020 to determine timing of freeze‐up and break‐up and annual river ice durations. We found indication of progressive ice cover reduction over more than half of the monitored river reaches, with possibly the fastest rate occurring over northeast Russia. Some rivers in high‐latitude North America experienced a slight increase in ice cover. Across the data set, we observed an average 2.2 days shift toward later ice freeze‐up in autumn and an average 0.6 days shift toward earlier ice break‐up in spring, resulting in an average decrease of 3.4 days in ice duration between 2010 and 2020. River reaches with the longest duration of ice cover appeared to have experienced the fastest rate of decrease. A possible reduction of the time lag between air temperature rise or fall and corresponding river ice break‐up and freeze‐up was also observed. Yet results on variability are carefuly interpreted given the short length of the time series (2010–2020) and the low statistical confidence rates calculated for the decadal tendency. Still outcomes are consistent with increases in global and Arctic surface air temperature. Following these time series over the next decade using passive microwave satellite sensors can monitor ice cover duration in the Arctic and will further determine temporal and regional trends. Key Points: A satellite passive microwave algorithm provides timing of river ice freeze‐up and break‐up verified by ground and independent informationRiver ice cover duration during 2010–2020 in northeast Russia was found to vary dissimilarly to that in North American riversResults are consistent with interannual air temperature variability and compatible to other investigations on river ice trends [ABSTRACT FROM AUTHOR]

The Arctic is rapidly warming, and tundra vegetation community composition is changing from small, prostrate shrubs to taller, erect shrubs in some locations. Across much of the Arctic, the sensitivity of shrub secondary growth, as measured by growth ring width, to climate has changed with increased warming, but it is not fully understood how shrub age contributes to shifts in climate sensitivity.We studied Siberian alder, Alnus viridis ssp. fruticosa, a large nitrogen‐fixing shrub that has responded to climate warming with northward range expansion over the last 50 years. We used serial sectioning of 26 individual shrubs and 94 cross‐sections to generate a 98‐year growth ring chronology, including one 142‐year‐old, Siberian alder in Northern Alaska. We tested how secondary growth sensitivity to climate has changed over the past century (1920–2017) and how shrub age affects climate sensitivity of alder growth through time.We found that over time, alder growth as expressed by the stand chronology became more sensitive to July mean monthly air temperature. Older shrubs displayed higher sensitivity to June and July temperature than younger alders. However, during the first 30 years of growth of any shrub, temperature sensitivity did not differ among individuals. In addition, the June temperature sensitivity of growth series from individual cross‐sections depended on the age of the attached shrub.Our results suggest that age contributes to climate sensitivity, likely through modifying internal shrub carbon budgets by changing size and reducing alder's dependence on N‐fixation over time. Older, more sensitive alder may enhance C and N‐cycling while having greater recruitment potential. Linking alder age to climate sensitivity, recruitment and total N‐inputs will enable us to better predict ecosystem carbon and nitrogen cycling in a warmer Arctic. Read the free Plain Language Summary for this article on the Journal blog. [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]

Atmosphere and surface properties are routinely retrieved from satellite measurements and extensively used in weather forecast and climate analysis. Satellite missions dedicated to fill the gap of far‐infrared (far‐IR) observations are scheduled to be launched this decade. To explore mid‐infrared (mid‐IR) and far‐IR joint retrievals for the future far‐IR satellite missions, this study uses an optimal‐estimation‐based method to retrieve atmospheric specific humidity and temperature profiles, surface skin temperature, and surface spectral emissivity from the Infrared Interferometer Sounder‐D (IRIS‐D) measurements in 1970, the only existing spaceborne far‐IR spectral observations with global coverage. Based on a set of criteria, two cases in the Arctic, which are most likely under clear‐sky conditions, are chosen for the retrieval experiments. Information content analysis suggests that the retrieved surface skin temperature and the mid‐IR surface spectral emissivity are highly sensitive to the true values while the retrieval estimates of far‐IR surface emissivity are subject to the variation of water vapor abundance. Results show that radiances based on the retrieved state variables are more consistent with the IRIS‐D observations compared to those based on the reanalysis data. Retrieval estimates of the state variables along with retrieval uncertainties generally fall within reasonable ranges. The relative uncertainties of retrieved state variables decrease compared to the a priori relative uncertainties. In addition, the necessity to retrieve surface emissivity is corroborated by a parallel retrieval experiment assuming a blackbody surface emissivity that has revealed significant distortions of retrieved specific humidity and temperature profiles in the Arctic lower troposphere. Key Points: Atmospheric profiles and surface properties are simultaneously retrieved from satellite observations made 50 years agoCompared to reanalysis data, the retrieval estimates produce radiances which are more consistent with the observationsRetrievals of humidity and temperature profiles in the lower troposphere can be considerably affected by the surface spectral emissivity [ABSTRACT FROM AUTHOR]

The Arctic is warming much faster than the global average. This is known as Arctic Amplification and is caused by feedbacks in the local climate system. In this study, we explore a previously proposed hypothesis that an associated wind feedback in the Barents Sea could play an important role by increasing the warm water inflow into the Barents Sea. We find that the strong recent decrease in Barents Sea winter sea ice cover causes enhanced ocean‐atmosphere heat flux and a local air temperature increase, thus a reduction in sea level pressure and a local cyclonic wind anomaly with eastward winds in the Barents Sea Opening. By investigating various reanalysis products and performing high‐resolution perturbation experiments with the ocean and sea ice model FESOM2.1, we studied the impact of cyclonic atmospheric circulation changes on the warm Atlantic Water import into the Arctic via the Barents Sea and Fram Strait. We found that the observed wind changes do not significantly affect the warm water transport into the Barents Sea, which rejects the wind‐feedback hypothesis. At the same time, the cyclonic wind anomalies in the Barents Sea increase the amount of Atlantic Water recirculating westwards in Fram Strait by a downslope shift of the West Spitsbergen Current, and thus reduce Atlantic Water reaching the Arctic basin via Fram Strait. The resulting warm‐water anomaly in the Greenland Sea Gyre drives a local anticyclonic circulation anomaly. Plain Language Summary: The Barents Sea has been experiencing a rapid decrease in its winter sea ice extent during the last 30 years. The loss of sea ice creates new areas where, in winter, the relatively warm ocean loses heat to the cold atmosphere. As warm air rises, the warming reduces the sea level air pressure, changing the atmospheric circulation to develop a local anticlockwise wind system centered over the northern Barents Sea. The associated eastward winds in the Barents Sea Opening and southeastward winds in Fram Strait affect how warm water from the North Atlantic moves toward the Arctic. There has been a long debate on whether this wind anomaly can increase the warm Atlantic Water transport into the Barents Sea and thus cause a positive feedback mechanism for further reducing the sea ice through melting. We find that the observed atmospheric circulation changes have no significant impact on the Barents Sea warm water inflow and thus reject the wind feedback as a strong player in contributing to Arctic Amplification. However, strong anomalous southeastward winds in Fram Strait and the northern Nordic Seas cause a southward shift of the warm Atlantic Water recirculation and reduce its flow toward the Arctic. Key Points: A hypothesis that a wind feedback contributes to Arctic Amplification is rejected by performing dedicated wind perturbation simulationsWinter sea ice retreat in the northern Barents Sea causes anomalous cyclonic winds by locally enhancing ocean heat lossAnomalous cyclonic winds result in less Atlantic Water transport through Fram Strait [ABSTRACT FROM AUTHOR]

Climate change in the Arctic has substantial impacts on human life and ecosystems both within and beyond the Arctic. Our analysis of CMIP6 simulations shows that some climate models project much larger Arctic climate change than other models, including changes in sea ice, ocean mixed layer, air‐sea heat flux, and surface air temperature in wintertime. In particular, dramatic enhancement of Arctic Ocean convection down to a few hundred meters is projected in these models but not in others. Interestingly, these models employ the same ocean model family (NEMO) while the choice of models for the atmosphere and sea ice varies. The magnitude of Arctic climate change is proportional to the strength of the increase in poleward ocean heat transport, which is considerably higher in this group of models. Establishing the plausibility of this group of models with high Arctic climate sensitivity to anthropogenic forcing is imperative given the implied ramifications. Plain Language Summary: Arctic climate is projected to change dramatically in the future based on the latest climate models. However, there is a large discrepancy between these climate models. We find that simulated Arctic climate change tends to be much larger in models using the community ocean model "NEMO" as their ocean component. Future Arctic climate change in winter strongly depends on the strength of the increase in poleward ocean heat transport, which is considerably higher in the NEMO‐family climate models. There are some indications that this group of models can better reproduce the observed winter sea ice decline and mixed layer depth in the Barents Sea in their historical simulations. We suggest that investigating the model physics in the NEMO‐family climate models in comparison with other models may ultimately help to reduce the overall uncertainty in climate change projections. Key Points: Future Arctic climate change in winter strongly depends on the strength of the increase in poleward ocean heat transport (OHT)Arctic climate change in the NEMO‐family climate models is much more pronouncedNEMO‐family climate models have larger increases in poleward OHT [ABSTRACT FROM AUTHOR]

During the winter of 2015–2016, an extraordinary warming event occurred in the troposphere in the Arctic region. The above‐normal temperatures extended from the surface to 300 hPa in the Arctic. The number of extremely warm days derived from the surface air temperature revealed that this event was the most significant warming event since 1980. It was found that the tropospheric warming anomaly was not fully dependent on the warming anomalies at lower levels, and it formed earlier than the lower anomalies. In December 2015, there were three obvious warm centers in the troposphere in the mid‐high latitude regions in eastern North America, northern Europe, and western Asia. Albeit the strongest warming anomaly occurred in North America, the prominent warm advection to the Arctic region was transported from northern Europe during the initial stage of the Arctic mid‐upper tropospheric warming. Further investigation revealed that the teleconnection wave train stretching across North America to the North Atlantic and northern Europe contributed significantly to the existence of a poleward transport channel from northern Europe to the Arctic. The wave train spread from west to east and produced a strong southerly wind disturbance over the warm region in northern Europe. As a result, extraordinary poleward heat and water vapour transport occurred across the polar boundary causing substantial warming in the Arctic mid‐upper troposphere. During the extreme Arctic tropospheric warming event, the dynamic processes related to the heat transport over northern Europe directly contributed to the advanced rapid warming in the Arctic mid‐upper troposphere; whereas, the dynamic and thermal processes associated with the transport across the Arctic boundary jointly maintained the late stage of Arctic warming. [ABSTRACT FROM AUTHOR]

Ice wedges are considered as a paleoarchive of winter air temperatures as their stable isotope composition has been widely used to reconstruct winter climatic conditions in the Arctic regions. Ice wedge stable isotope records, obtained in recent decades for many Arctic permafrost areas of Russia and North America, demonstrate a clear shift from lower to higher values between the Late Pleistocene and Holocene (by 5–10‰ for δ18O values in some regions of the Russian Arctic), which is widely accepted as evidence of winter air temperature increase. However, the evolution of winter air temperatures during the Holocene is less clear and, according to proxy reconstructions, winter climate trends are not synchronous and may significantly vary throughout the Arctic. In this study, we investigate the stable isotope composition of Holocene syngenetic ice wedges and modern ice veinlets of northwestern Siberia. Radiocarbon dating of enclosing sediments and a few dates of organic material from ice wedges demonstrate that ice wedges grew constantly within the study area during the Holocene though early–mid‐Holocene in northwestern Siberia is often considered as a thermal optimum. In fact, many proxy records indicate an increase of summer air temperatures followed by thermokarst activity, peatland formation, and northward advance of the treeline. According to our data, winter climate conditions in terms of mean air temperature of the coldest winter month (January) did not change significantly during the key Holocene stages, and during the Greenlandian and most of the Northgrippian stages (between 11.4 and 6 cal ka BP) mean January air temperature (TmJ) varied between −21 and −30°C, and from the end of the Northgrippian, during the Meghalayan stages of Holocene (5.2–0.9 cal ka BP), TmJ varied between −24 to −28°C. Mean January air temperature during the Holocene was generally 1–2°C lower than the modern one, meanwhile the submeridional direction of TmJ isotherms and eastward decrease of TmJ values in Holocene are similar to the modern pattern. [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]

Year‐to‐year forecasts of the Arctic climate conditions have drawn much interest in recent decades. This study investigates the primary drivers responsible for interannual variations (without multi‐decadal trends) of air temperature at 2 m (T2m) and sea ice concentration (SIC) over the Barents‐Kara Seas (BKS) during September from 1950 to 2021. The Arctic Dipole (AD), a leading factor in the BKS variability, plays an important role via influencing large‐scale atmospheric circulations and local thermodynamical feedbacks (i.e., vapor and albedo feedbacks). During a negative AD phase, the positive surface air temperature advection anomalies warm up the BKS region and promote sea ice melting, which in turn maintains the below‐normal sea ice and warmer‐than‐normal conditions via positive vapor and albedo feedbacks. Moreover, our results suggest that the sea surface temperature (SST) variability in the midlatitudes of the North Atlantic in the preceding month could also be an important driver of the SIC variability over the BKS area. The anomalous temperature advections from the surface to the upper troposphere are accompanied by a Rossby wave‐type atmospheric response, which intensifies the energy exchanges between the ocean and the atmosphere. Local SST anomalies associated with the surface heat flux anomalies further persist in the following month and influence sea ice variations due to their long‐lasting memory. A better understanding of the mechanisms of interannual climate variabilities over the BKS region in boreal early autumn is helpful to improving the Arctic regional climate predictions. Key Points: Understanding primary drivers of the interannual climate variabilities over the Arctic is essential to improve the regional prediction skillsThe Arctic Dipole is mainly responsible for driving the Barents‐Kara Seas (BKS) surface air temperature interannual variability in SeptemberThe North Atlantic sea surface temperature variability at 1‐month lead is associated with the early autumn sea ice cover variability in the BKS region [ABSTRACT FROM AUTHOR]

Reanalysis data and a numerical model are employed to explore how diffusion in the upper ocean evolves in different seasons and to understand its contribution to seasonal heat storage (SHS) and Arctic amplification. The numerical simulation results are closely consistent with observations. First, Arctic solar radiation absorption anomaly (maximum in June) due to ice‐loss is mainly stored as SHS (maximum in June and July) or warms the surface (minimum in July) in observations. Furthermore, the numerical simulation suggests that vertical diffusion dominates SHS formation/discharge. Second, surface ocean becomes warmer than surface air in cold season and releases SHS in Arctic. Sea‐ice loss allows more ocean be directly driven by wind; surface high pressure over Arctic may enhance the wind stress; increased water freeze leads to more salt rejection and additional dense water being produced and sinking downward; all of the occurrences strengthen vertical mixing and release more SHS to the atmosphere. As a result, Arctic surface warming reaches its maximum in cold season. In observations, much stronger outgoing longwave radiation due to the warmer surface in October causes Arctic surface warming to reach its maximum in November, although increased carbon dioxide forcing also contributes to maintain longwave radiation in November. Finally, Arctic surface (air) warming in cold season exhibits different spatial patterns from SHS discharge due to heat convergence/divergence induced by anomalous surface wind, which is determined by the variation in surface high pressure over the Arctic. Plain Language Summary: Due to little seasonal variation in global surface warming, seasonality of Arctic amplification (AA) is mainly determined by seasonal variation of Arctic surface warming. Seasonal heat storage (SHS) in the subsurface Arctic Ocean contributes to Arctic surface warming by holding anomalous heat in summer and releasing it in autumn and winter. As a result, there is significant seasonal variation in AA. In this study, we directly estimate the SHS with ocean data and focus on spatial feature discussions. (a) In summer, additional solar radiation is stored as SHS via vertical diffusion in the upper ocean, resulting in weak Arctic warming. (b) In cold season, more current is driven directly by wind due to sea‐ice loss; variation in surface high pressure over the Arctic enhances the wind stress; more dense water, which is produced due to additional water freezes, sink downward; all of which strengthen the vertical mixing and release more SHS, resulting in the Arctic warming maximum. (c) Although SHS discharge dominates Arctic warming in cold season, anomalous surface wind induces heat convergence/divergence and influences the spatial distribution of surface air temperature, which in turn impacts surface warming via air‐sea/air‐land interactions. Finally, the SHS anomaly and surface warming share different spatial patterns. Key Points: With (without) land surface warming occurring in June, the observational (numerical) Arctic warming/Arctic amplification reaches its minimum in July (June)Though seasonal heat storage (SHS) discharge dominates Arctic warming in cold season, anomalous wind makes their spatial patterns differentLess insulation by sea‐ice loss, wind acceleration or more dense water sinking increases vertical mixing and SHS discharge in cold season [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]

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]

The spatiotemporal variations of the climate of the last millennium provide the context for understanding the recent climate. However, there are few 1000‐year‐long spatiotemporally continuous climate reconstructions at hemispheric to global scales. Here, a millennial, spatiotemporally continuous and annually resolved air temperature dataset for the Northern Hemisphere (NH) was reconstructed using paleoclimate data assimilation (PDA) approach based on an expanded tree ring proxy dataset and artificial neural network‐based proxy system models. Verifications show the PDA‐based reconstruction agrees well with instrumental temperature, previous proxy‐based reconstructions and the Last Millennium Climate Reanalysis version 2 (LMRv2) dataset in space and time domains. Since the PDA‐based reconstruction is spatiotemporally continuous fields without missing value over the whole NH, which is a distinct advantage of the PDA‐based reconstruction over other proxy‐based NH‐averaged temperature reconstructions, we focussed on analysing the spatial variations of the NH temperature during the last millennium, for example, the primary modes of temperature variabilities and the spatial variabilities of the NH temperature in three typical climatic epochs of the millennium. Results show that the first‐leading mode (explained variance of 72.50%) of the NH temperature variability is a spatially consistent mode, while the second‐leading mode (explained variance of 10.60%) exhibits a different pattern that is different from the first‐leading empirical orthogonal function mode, particularly in the Arctic, which shows a dipole structure anomaly. The 20th century was the warmest, with 94.17% of the NH displaying positive anomalies. The 11th century was the second warmest century in the record, with 70.26% of the NH showing a positive anomaly. The 19th century was the coldest, with negative anomalies covering 86.97% of the NH. Northwest North America and the Northern Europe‐Barents Sea are two distinctly anomalous centres during these three centuries. Overall, the reconstructed air temperatures provide a new and reliable dataset for studying the millennial NH temperature variations. [ABSTRACT FROM AUTHOR]

Observations have shown subseasonal reversal of temperature anomalies between early and late winter over Eurasia, which is distinct from the seasonal mean condition. Based on the reanalysis data, the 1800‐year control simulation and the 40‐member ensemble simulations in 1920–2100 from the Community Earth System Model (CESM) Large Ensemble (CESM‐LE), this study reveals that the reversal of surface air temperature (SAT) anomalies between early and late winter is one of the dominant and intrinsic features of the Arctic‐Eurasian winter climate. Such a reversal is characterized by "colder Arctic, warmer Eurasia" in December (January–February) and "warmer Arctic, colder Eurasia" in January–February (December). Robust climate dynamic processes associated with the reversal of SAT anomalies, including subseasonal reversals of anomalies in the Ural blocking, midlatitude westerlies, and stratospheric polar vortex, are found in both reanalysis data and CESM simulations, indicating the important role of internal atmospheric variability. Further analysis reveals that the reversal of Ural blocking anomalies in late December can be a potential precursor for the reversal of SAT anomalies in late winter. The reversal of midlatitude westerly wind anomalies associated with the Ural blocking can affect upward propagation of planetary‐scale waves especially with wavenumber 1, subsequently promoting the contribution of stratospheric polar vortex to the reversal of SAT anomalies in late winter over the Arctic‐Eurasian regions. Such a troposphere‐stratosphere pathway triggered by the perturbation of tropospheric circulations is confirmed by the CESM‐LE simulations, and it may be useful for the prediction of subseasonal reversal of SAT anomalies. Plain Language Summary: Observations show that Eurasia may experience subseasonal reverse temperature anomalies from early to late winter. For example, the warmer‐than‐normal conditions in early winter can change to colder‐than‐normal conditions in late winter. Such a reverse temperature anomaly in Eurasia is usually concurrent with a reverse one in the Arctic. The "colder Arctic, warmer Eurasia" pattern in early winter followed by "warmer Arctic, colder Eurasia" pattern in late winter is robustly detected in climate model simulations, indicating that the subseasonal reversal of temperature anomalies is one of the intrinsic features of the Arctic‐Eurasian climate. This feature is associated with robust climate dynamic processes, including subseasonal reversals of the anomalies in the Ural blocking, the midlatitude westerly winds, and the stratospheric polar vortex. Because the Ural blocking can trigger the troposphere‐stratosphere interaction, the reversal of Ural blocking anomalies in late December can be a potential precursor for the reversal of surface air temperature anomalies in late winter. Key Points: Reversal of surface air temperature (SAT) anomalies between early and late winter is an intrinsic feature of the Arctic‐Eurasian climateThe changes of Ural blocking in late December may indicate whether the SAT in late winter will be reversed to early winterRobust climate dynamic processes associated with such a reversal of SAT are found in both reanalysis data and long‐term model simulations [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 Arctic has warmed three times the rate of the global average, resulting in extensive thaw of perennially frozen ground known as permafrost. While it is well understood that permafrost thaw will continue and likely accelerate, thaw rates are nonuniform due, in part, to the expansion of Arctic trees and tall shrubs that may increase ground temperatures. However, in permafrost regions with short‐stature vegetation (height < 40 cm), our understanding of how ground temperature regimes vary by vegetation type is limited as these sites are generally found in remote high‐latitude regions that lack in situ ground temperature measurements. This study aims to overcome this limitation by leveraging in situ shallow ground temperatures, remote sensing observations, and topographic parameters across 22 sites with varying types of short‐stature vegetation on Baffin Island, Canada, a remote region underlain by rapidly warming continuous permafrost. Results suggest that the type of short‐stature vegetation does not necessarily correspond to a distinct shallow ground temperature regime. Instead, in permafrost regions with short‐stature vegetation, factors that control snow duration, such as microtopography, may have a larger effect on evolving ground temperature regimes and thus permafrost vulnerability. These findings suggest that anticipating permafrost thaw in regions of short‐stature vegetation may be more nuanced than previously suggested. Plain Language Summary: Air temperatures across the Arctic are rapidly warming and causing perennially frozen ground known as permafrost to thaw. As permafrost thaws, it has the potential to accelerate global warming through carbon dioxide and methane release. Permafrost thaw rates vary from place to place due, in part, to the expansion of trees and tall shrubs, which is also occurring as the Arctic warms. This tall vegetation traps snow, which acts as a blanket and insulates the ground surface from cold air thawing permafrost. However, in places where permafrost occurs below shorter vegetation, our understanding of how vegetation influences permafrost thaw is lacking, largely because these regions of the Arctic are difficult to access. This study sheds light on this shortcoming by leveraging environmental data across permafrost sites with shorter vegetation on Baffin Island, Canada. Contrary to previous findings, we suggest that the exact type of short vegetation is not always the primary control on ground temperatures. Instead, ground temperatures in these regions seem to be controlled by how long snow is on the ground, due to other factors like small depressions or wind buffering. These findings help us anticipate permafrost thaw in remote, rapidly warming permafrost regions with short‐stature vegetation. Key Points: We examine the role of short‐stature vegetation type on shallow ground temperatures in a remote region underlain by continuous permafrostContrary to prior results, the type of short‐stature vegetation does not necessarily correspond to a distinct ground temperature regimeUnderstanding controls on snow duration is more critical than classifying short‐stature vegetation types when predicting permafrost thaw [ABSTRACT FROM AUTHOR]

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

We provide the northernmost permafrost thermal analysis in Greenland through the ground temperature time series (2014–2021) and cryostratigraphy of two 20‐m deep boreholes (SN1 and SN2) at Villum Research Station, Station Nord (81°N). Three sedimentary units are identified in the stratigraphy: glacial, glaciomarine, and beach deposits. These sandy and gravelly deposits are interpreted to comprise a deglaciation and isostatic emergence sequence. Ice‐poor epigenetic permafrost grew downwards into the deposits following subaerial exposure. Relatively high salinity values (up to 70 ppt) are observed in the glaciomarine unit, resulting in freezing point depressions between 0 and −4°C. The Prinsesse Ingeborg Halvø study area has a polar tundra climate and is unique compared to other high Arctic areas because of a thick (>1 m), long‐lasting snow cover. This snow cover results in relatively high permafrost temperatures for the climate and latitude and the warmest known permafrost north of 80°N. Over the seven‐year study period, average 20 m permafrost temperature was −7.87°C at SN1 and −7.06°C at SN2. The warming rate at 20 m depth was 0.07°C/year at SN1 and 0.05°C/year at SN2, rates which are similar to those of other high Arctic sites. Active layer thickness, extrapolated from the temperature measurements, varied between 0.5 and 1.16 m. The interplay between snow dynamics and seasonal air temperature controls ground thermal regime in the study area. Air temperatures during autumn and midwinter, the fastest warming seasons, influence the ground thermal regime through the gradually developing, dense snowpack. Plain Language Summary: Permafrost, ground that is frozen for at least two consecutive years, is commonly found in high mountains and polar environments. Permafrost samples and long‐term permafrost temperature records are necessary to fully understand permafrost and how it is changing with a warming climate. We present results of permafrost research from Villum Research Station at Station Nord, the northernmost permafrost monitoring site in Greenland and second northernmost worldwide. We collected core samples from two different 20‐m deep boreholes and measured temperature in the boreholes for over seven years to understand the permafrost's physical and thermal properties, and how the permafrost reacts to the weather and climate. The permafrost began to form more than 8,000 years ago, after the study area was deglaciated and the sea level lowered. A major reason this permafrost is warmer than other sites in the high Arctic is because the area has more than 1 m of snow in the winter, which is unusual for the polar tundra and acts as an insulating layer. Permafrost at 20 m depth has warmed 0.05–0.07°C per year from 2014 to 2021; these rates are similar to those at other high Arctic sites. Key Points: The presented permafrost thermal record is the second northernmost in the Arctic and reveals the warmest known permafrost north of 80°NThe warming rate at 20 m depth was 0.07°C/year and 0.05°C/year at the two sites from 2014 to 2021 despite thick and long‐lasting snow coverEpigenetic permafrost grew into sands and gravels deposited during deglaciation and isostatic emergence of the Prinsesse Ingeborg Halvø [ABSTRACT FROM AUTHOR]

Arctic freshwaters are facing multiple environmental pressures, including rapid climate change and increasing land___use activities. Freshwater plankton assemblages are expected to reflect the effects of these stressors through shifts in species distributions and changes to biodiversity. These changes may occur rapidly due to the short generation times and high dispersal capabilities of both phyto___ and zooplankton.Spatial patterns and contemporary trends in plankton diversity throughout the circumpolar region were assessed using data from more than 300 lakes in the U.S.A. (Alaska), Canada, Greenland, Iceland, the Faroe Islands, Norway, Sweden, Finland, and Russia. The main objectives of this study were: (1) to assess spatial patterns of plankton diversity focusing on pelagic communities; (2) to assess dominant component of __ diversity (turnover or nestedness); (3) to identify which environmental factors best explain diversity; and (4) to provide recommendations for future monitoring and assessment of freshwater plankton communities across the Arctic region.Phytoplankton and crustacean zooplankton diversity varied substantially across the Arctic and was positively related to summer air temperature. However, for zooplankton, the positive correlation between summer temperature and species numbers decreased with increasing latitude. Taxonomic richness was lower in the high Arctic compared to the sub___ and low Arctic for zooplankton but this pattern was less clear for phytoplankton. Fennoscandia and inland regions of Russia represented hotspots for, respectively, phytoplankton and zooplankton diversity, whereas isolated regions had lower taxonomic richness. Ecoregions with high __ diversity generally also had high __ diversity, and turnover was the most important component of __ diversity in all ecoregions.For both phytoplankton and zooplankton, climatic variables were the most important environmental factors influencing diversity patterns, consistent with previous studies that examined shorter temperature gradients. However, barriers to dispersal may have also played a role in limiting diversity on islands. A better understanding of how diversity patterns are determined by colonisation history, environmental variables, and biotic interactions requires more monitoring data with locations dispersed evenly across the circumpolar Arctic. Furthermore, the importance of turnover in regional diversity patterns indicates that more extensive sampling is required to fully characterise the species pool of Arctic lakes. [ABSTRACT FROM AUTHOR]

Warming in the Arctic is predicted to change freshwater biodiversity through loss of unique taxa and northward range expansion of lower latitude taxa. Detecting such changes requires establishing circumpolar baselines for diversity, and understanding the primary drivers of diversity.We examined benthic macroinvertebrate diversity using a circumpolar dataset of >1,500 Arctic lake and river sites. Rarefied α diversity within catchments was assessed along latitude and temperature gradients. Community composition was assessed through region‐scale analysis of β diversity and its components (nestedness and turnover), and analysis of biotic–abiotic relationships.Rarefied α diversity of lakes and rivers declined with increasing latitude, although more strongly across mainland regions than islands. Diversity was strongly related to air temperature, with the lowest diversity in the coldest catchments. Regional dissimilarity was highest when mainland regions were compared with islands, suggesting that connectivity limitations led to the strongest dissimilarity. High contributions of nestedness indicated that island regions contained a subset of the taxa found in mainland regions.High Arctic rivers and lakes were predominately occupied by Chironomidae and Oligochaeta, whereas Ephemeroptera, Plecoptera, and Trichoptera taxa were more abundant at lower latitudes. Community composition was strongly associated with temperature, although geology and precipitation were also important correlates.The strong association with temperature supports the prediction that warming will increase Arctic macroinvertebrate diversity, although low diversity on islands suggests that this increase will be limited by biogeographical constraints. Long‐term harmonised monitoring across the circumpolar region is necessary to detect such changes to diversity and inform science‐based management. [ABSTRACT FROM AUTHOR]

Studies have indicated that marine heatwaves (MHWs) have had severe impacts on the marine ecosystem in the Pacific, Atlantic, and Indian Oceans, but there have been few studies focused on MHWs in the Arctic. On the other hand, amplified rapid warming in the Arctic region makes it a hotspot strategically and economically worldwide. In this study, we documented that the average intensity of MHWs in the Arctic was comparable with that in the other regions of the global oceans. The annual intensity, frequency, duration, and areal coverage of MHWs have increased significantly in recent decades. The increase of the annual duration is mainly owing to the postponed end time, thus the prolonged periods, of the MHW seasons. Our analysis indicates that the increasing trends of the annual intensity, frequency, duration, and areal coverage in the Arctic are closely associated with the increasing surface air temperature and decreasing sea‐ice concentration under the global warming environment. These features are robust across three different sea surface temperature (SST) products and using different MHW criteria. Plain Language Summary: Events of extremely warm waters in the oceans are known as marine heatwaves (MHWs). Past MHW research has used sea surface temperature (SST) to diagnose MHWs and has focused on the tropical and subtropical oceans. The questions we address here are: (a) Are there any MHW events in the Arctic region where SSTs are generally low? and (b) Are the MHWs weaker or stronger in the Arctic than in the other oceans? Our study indicates that: (a) MHWs do exist in the Arctic, (b) their strengths increase with time, and (c) they are stronger than those in the other oceans in the most recent decades. These MHWs may have a strong impact on the Arctic bio‐ecosystem due to their low heat tolerance since the seasonal variation of SST in the Arctic is small. Key Points: The average marine heatwaves (MHWs) in the Arctic are as strong as in the other ocean basins in 1982–2020The annual intensity are stronger in 2000–2020 than in 1982–2000, which is consistent with changes in air temperature, sea‐ice, and cloudThe increase of annual duration is largely associated with the postponed end time of the MHW seasons [ABSTRACT FROM AUTHOR]

Radiation changes at the Earth's surface alter climate, however, the causes of observed surface radiation changes are not precisely quantified globally. With complete global coverage by ERA‐Interim, the drivers of the clear sky surface downwelling longwave irradiance (SDLI) trends from 1984 to 2017 are quantifiable everywhere. Trends in atmospheric temperature and water vapor contributed significantly (∼90%) to clear sky SDLI trends, including trends consistent with Arctic warming and Southern Ocean cooling. CO2 contributed ∼10% and other greenhouse gases (CH4, N2O, CFC‐11, and CFC‐12) ∼1% to the SDLI trends. These observation‐based results are consistent with early CO2‐doubling climate model calculations wherein temperature and water vapor changes drove ∼90% of the SDLI change. The well‐mixed greenhouse gases drive location‐dependent SDLI trends that are strongest over regions with climatologically high temperatures and low water vapor amounts. Plain Language Summary: Using ERA‐Interim analyzed fields, we show how downward longwave radiation has changed at the Earth's surface from 1984 to 2017. The longwave radiation changes primarily occurred as a consequence of air temperature and water vapor changes. Air temperatures and water vapor amounts increased over most locations. The CO2 increase alone contributed to about 10% of the change in downward longwave radiation that occurred over the last 34 years. This ∼10% change in CO2 was associated with rises in water vapor and atmospheric temperatures that in turn dominated the remaining ∼90% of the change in downward longwave radiation at the surface. Compared to CO2, we find that the other greenhouse gases (methane, nitrous oxide, and chlorofluorocarbons) did not contribute significantly to surface warming from 1984 to 2017. Finally, we show that the greenhouse gases contributed to greater amounts of downward longwave radiation over high latitudes due to lower water vapor amounts. Key Points: Surface downwelling longwave irradiance changes contributed to surface warming over the Arctic and surface cooling over the Southern OceanAtmospheric temperature and water vapor trends drove ∼90% of the surface downwelling longwave irradiance trend and CO2 contributed ∼10%Well‐mixed greenhouse gases caused spatially varying irradiance trends due to spatial variations in the water vapor and temperature fields [ABSTRACT FROM AUTHOR]

Whether sea‐ice loss or lapse‐rate feedback dominates the Arctic amplification (AA) remains an open question. Analysis of data sets based upon observations reveals a 1.11 K per decade surface warming trend in the Arctic (70°–90°N) during 1979–2020 cold season (October–February) that is five times higher than the corresponding global mean. Based on surface energy budget analysis, we show that the largest contribution (∼82%) to this cold season warming trend is attributed to changes in clear‐sky downward longwave radiation. In contrast to that in Arctic summer and over tropics, a reduction in lower‐tropospheric inversions plays a unique role in explaining the reduction of the downward longwave radiation associated with atmospheric nonuniform temperature and corresponding moisture changes. Our analyses also suggest that Arctic lower‐tropospheric stability should be considered in conjunction with sea‐ice decline during the preceding warm season to explain AA. Plain Language Summary: Observations and climate models have consistently shown a stronger surface warming in the Arctic than the global mean, a.k.a. Arctic amplification (AA), which has a strong asymmetry between the cold season and warm season. Previous studies suggested that key contributors to AA are the positive surface‐albedo feedback and lapse‐rate feedback. However, the lapse‐rate feedback itself depends on temperature profiles and sea‐ice loss. Whether sea‐ice loss or lapse‐rate feedback dominates AA remains an open question. Here, by analyzing the latest generation of observationally‐based reanalysis data (1979–2020), we present a unique role of lower‐tropospheric temperature inversion changes in representing the contribution of vertically inhomogeneous atmospheric temperature and associated moisture changes to clear‐sky downward longwave radiation during the cold season. This unique role is not found either in the tropics or during Arctic summertime. We further link the inversion during the cold season to sea‐ice loss during the preceding warm season. These results reinforce previous findings not only that lapse‐rate feedback and sea‐ice loss play a key role in AA but also that lapse‐rate feedback in the cold season is likely a consequence of sea‐ice albedo feedback during the preceding warm season. Key Points: An increase in clear‐sky downward longwave radiation (rldsclr) explains 82% of the recent cold season Arctic surface warming trendReduced low inversion largely explains the Arctic rldsclr reduction due to vertical nonuniform temperature and related moisture changesLapse‐rate feedback in the Arctic cold season is likely a consequence of sea‐ice albedo feedback during the preceding warm season [ABSTRACT FROM AUTHOR]

In this work it is shown that the prediction of individual midlatitude waves in a global forecast framework may benefit from the assimilation of cloud-cleared radiances (CCRs) from the Atmospheric Infrared Sounder (AIRS). The assimilation of CCRs, relative to clear-sky radiances, provides more information in high-latitude areas affected by broken low-level stratus clouds, which are common over north polar latitudes during the summer and autumn seasons. This added information in cloudy regions produces slightly lower low-level temperatures and lower mid-tropospheric heights (through hydrostatic adjustment) over the Arctic and part of northeastern Siberia. In areas that are both dynamically unstable (with the potential for rapid error growth) and data void (as observed by clear-sky radiances), the assimilation of CCRs provides valuable information that can improve the representation of individual baroclinic waves and their subsequent forecasts. The assimilation of AIRS CCRs slightly modifies the geopotential height gradients between the Arctic and the midlatitudes, leading to improvements in the forecast of individual baroclinic waves, as is shown through three case-studies. The set of observing system experiments (OSEs) is performedwith theNASAGoddard EarthObserving System (GEOS) data assimilation and forecast system during boreal autumn 2014. AIRS CCRs are thinned to approximately one quarter the density of operationally assimilated AIRS radiances, consistent with their higher information content. Global 6-hourly analyses are produced from 01 September to 10 November 2014 and seven-day forecasts are initialized at 0000 UTC daily. Since the CCR methodology is widely applicable, these findings are also relevant to other infrared sensors. [ABSTRACT FROM AUTHOR]

A model study shows that the decline of Arctic sea ice volume (SIV) slows down during 2007–2020 with increasingly warm atmospheric and oceanic conditions. The slowdown of the SIV decline is because the decrease in ice export from the Arctic exceeds the decrease in net ice production within the Arctic. The relatively strong decrease in ice export occurs when the increase in ice motion is lower than the decrease in SIV. The relatively weak decrease in net ice production is due to strong increases in ice growth as thinner ice grows faster than thicker ice under freezing conditions. The ice growth increases are closely correlated with and benefit from increases in open water creation caused by enhanced ice divergence and shear as thinner ice is easier to deform. Plain Language Summary: Results from the Pan‐arctic Ice‐Ocean Modeling and Assimilation System (PIOMAS) show significant decline of Arctic sea ice volume (SIV) in the past decades. However, the SIV decline is slowing down during 2007–2020 with increasingly higher air and ocean temperatures, which is in line with satellite CryoSat‐2 observations of largely stabilized SIV since 2011. The slowdown of the SIV decline is because of relatively strong decreases in ice export from the Arctic and increases in ice growth in the Arctic. The relatively strong increase in ice growth in 2007–2020 is because thinner and less compact ice, which is the norm in recent years, has much higher growth rates than thicker ice under freezing conditions. Thinner ice also moves faster and deforms more, which tends to create more open water to stimulate ice growth in 2007–2020. Thus, the ice export and growth processes play a role in slowing down the SIV decline in recent years and may continue to play that role in the future. Key Points: The decline of Arctic sea ice volume has slowed down in recent years under increasingly warm atmospheric and oceanic conditionsThe slowdown is due to weak ice export and strong ice growth which serve as a negative feedback to retard the ice volume declineIncreases in dynamic open water creation because of an accelerating thin ice cover play a role in stimulating ice growth in recent years [ABSTRACT FROM AUTHOR]

Climate change has ecosystem‐wide cascading effects. Little is known, however, about the resilience of Arctic marine ecosystems to environmental change. Here we quantify and compare large‐scale patterns in rocky intertidal biomass, coverage and zonation in six regions along a north‐south gradient of temperature and ice conditions in West Greenland (60–72°N). We related the level and variation in assemblage composition, biomass and coverage to latitudinal‐scale environmental drivers. Across all latitudes, the intertidal assemblage was dominated by a core of stress‐tolerant foundation species that constituted > 95% of the biomass. Hence, canopy‐forming macroalgae, represented by Fucus distichus subsp. evanescens and F. vesiculosus and, up to 69°N, also Ascophyllum nodosum, together with Semibalanus balanoides, occupied > 70% of the vertical tidal range in all regions. Thus, a similar functional assemblage composition occurred across regions, and no latitudinal depression was observed. The most conspicuous difference in species composition from south to north was that three common species (the macroalgae Ascophyllum nodosum, the amphipod Gammarus setosus and the gastropod Littorina obtusata) disappeared from the mid‐intertidal, although at different latitudes. There were no significant relationships between assemblage metrics and air temperature or sea ice coverage as obtained from weather stations and satellites, respectively. Although the mean biomass decreased > 50% from south to north, local biomass in excess of 10 000 g ww m−2 was found even at the northernmost site, demonstrating the patchiness of this habitat and the effect of small‐scale variation in environmental characteristics. Hence, using the latitudinal gradient in a space‐for‐time substitution, our results suggest that while climate modification may lead to an overall increase in the intertidal biomass in north Greenland, it is unlikely to drive dramatic functional changes in ecosystem structure in the near future. Our dataset provides an important baseline for future studies to verify these predictions for Greenland's intertidal zone. [ABSTRACT FROM AUTHOR]

Summary: The Gypsum Hill (GH) springs on Axel Heiberg Island in the Canadian high Arctic are host to chemolithoautotrophic, sulfur‐oxidizing streamers that flourish in the high Arctic winter in water temperatures from −1.3 to 7°C with ~8% salinity in a high Arctic winter environment with air temperatures commonly less than −40°C and an average annual air temperature of −15°C. Metagenome sequencing and binning of streamer samples produced a 96% complete Thiomicrorhabdus sp. metagenome‐assembled genome representing a possible new species or subspecies. This is the most cold‐ and salt‐extreme source environment for a Thiomicrorhabdus genome yet described. Metaproteomic and metatranscriptomic analysis attributed nearly all gene expression in the streamers to the Thiomicrorhabdus sp. and suggested that it is active in CO2 fixation and oxidation of sulfide to elemental sulfur. In situ geochemical and isotopic analyses of the fractionation of multiple sulfur isotopes determined the biogeochemical transformation of sulfur from its source in Carboniferous evaporites to biotic processes occurring in the sediment and streamers. These complementary molecular tools provided a functional link between the geochemical substrates and the collective traits and activity that define the microbial community's interactions within a unique polar saline habitat where Thiomicrorhabdus‐dominated streamers form and flourish. [ABSTRACT FROM AUTHOR]

Warming and hydrological changes have already affected and shifted environments in the Arctic. Arctic wetlands are complex systems of coupled hydrological, ecological, and permafrost‐related processes, vulnerable to such environmental changes. This review uses a systems perspective approach to synthesize and elucidate the various interlinked responses and feedbacks of Arctic wetlands to hydroclimatic changes. Starting from increased air temperatures, subsequent permafrost thaw and concurrent hydrological changes are identified as key factors for both shrinkage and expansion of wetland area. Other diverse factors further interact with warming, hydrological changes, and permafrost thaw in altering the Arctic wetland systems. Surface albedo shifts driven by land cover alterations are powerful in reinforcing Arctic warming, while vegetation‐related factors can balance and decelerate permafrost thaw, causing negative feedback loops. With the vast amounts of carbon stored in Arctic wetlands, their changes in turn affect the global carbon cycle. Overall, the systems perspectives outlined and highlighted in this review can be useful in structuring and elucidating the interactions of wetlands with climate, hydrological, and other environmental changes in the Arctic, including the essential permafrost‐carbon feedback. This article is categorized under:Water and Life > Nature of Freshwater EcosystemsWater and Life > Stresses and Pressures on EcosystemsScience of Water > Water and Environmental Change [ABSTRACT FROM AUTHOR]

Surface air temperature trends and extreme events are of global concern and they are related. Here, we show that the occurrence of record hot years over different latitudes from 1960 to 2019 are more strongly correlated with the observational annual mean temperature trends normalized by internal variability. Compared with the raw trends showing Arctic amplification, the normalized trends show a tropical amplification over land. Two hot spots with more frequent occurrence of record hot years are identified: northern hemisphere ocean (vs. land) and southern hemisphere tropical land (vs. mid‐ and high‐latitude lands). Ensemble mean results from 32 Earth system models agree with observations better than individual models, but they do not reproduce observed large differences in correlations across latitudes between normalized trends and record‐breaking events over land versus ocean. Our results enable the quantification of record hot year occurrence through normalized warming trends and provide new metrics for model evaluation and improvement. Plain Language Summary: Surface air temperature trends and extreme hot events are of global concern and they are related. Based on generic time series, it was argued that the occurrence of extreme events depends on the normalized, rather than the raw, trends. However, it remains unknown whether this dependence is relevant to the comparison of extreme hot event occurrences over different regions, such as the Arctic versus Amazon. Here, we show that the occurrence of record hot years over different regions from 1960 to 2019 are more strongly correlated with the observational annual mean temperature trends normalized by internal variability. Compared with the raw trends showing Arctic amplification, the normalized trends show a tropical amplification over land. Two hot spots with more frequent occurrence of record hot years are identified: Northern hemisphere ocean (vs. land) and southern hemisphere tropical land (vs. mid‐ and high‐latitude lands). Results averaged from 32 Earth system models agree with observations better than individual models, but they do not reproduce observed large differences in correlations across latitudes between normalized trends and record‐breaking events over land versus ocean. Our results enable the quantification of record hot year occurrence through normalized warming trends and provide new metrics for model evaluation and improvement. Key Points: Occurrence of record hot years in different latitudes is better correlated with normalized, rather than raw, temperature trendsCompared with the raw trends showing Arctic amplification, the normalized trends show a tropical amplification over landEarth system models' correlations between normalized trends and record‐breaking events are as high over land as over ocean, unlike in observations [ABSTRACT FROM AUTHOR]

The Arctic has experienced prominent climate warming, at the beginning of the 20th century and currently. Comparing the driving mechanism during these periods helps to explain the causes of contemporary climate change. Our study explores the impact of regional circulation on Svalbard's surface air temperature (SAT, 2 m above ground). We used air temperature data from Svalbard Airport, Bjørnøya stations, and three regional circulation indices that describe the frequency of cyclonic conditions, zonal circulation, and meridional circulation. The indices were calculated for four circulation areas with differing circulation conditions and, therefore, may have various impacts on long‐term changes in SAT. This was checked for the entire study period (1920–2018), and 30‐year sub‐periods representing the most prominent climatic events: the early 20th‐century Arctic warming (ETCAW), contemporary Arctic warming (CAW), and a cold period between them (CAP). In autumn and winter, the deviations in SAT from the long‐term average during warm and cold periods were almost twice as large at Svalbard Airport as at Bjørnøya. In these seasons, the ETCAW was significantly warmer than the subsequent cold period, which was not the case for summer and spring. However, long‐term trends in the regional circulation indices were more evident in summer and spring than in autumn and winter. Air temperature was the most strongly influenced by meridional circulation over the eastern circulation areas, with the exception of spring, when air temperature variability was more affected by zonal circulation. The recent warming weakened the relationship between SAT and the indices in summer. We attributed the ETCAW in autumn to a southerly advection of sensible heat. During the same historical period, the impact of the indices was much weaker in winter. In winter during the CAP, there was a higher frequency of northern air advection, particularly over the northern part of the Greenland Sea. [ABSTRACT FROM AUTHOR]

The El Niño Southern Oscillation (ENSO) is a well‐known modulator of global climate and is correlated with observed temperature variations over the Barents‐Kara Sea (BKS). However, the origins and causality of this observed correlation are unclear. Here, we show that historical climate model simulations, on average, fail to reproduce the observed ENSO‐BKS correlation. However, individual realizations do show a relationship as observed. We find that the internal variability of BKS sea ice is the main factor between realizations that reproduce the ENSO‐BKS correlation and those that do not. Furthermore, we find that atmospheric model simulations prescribed with observed sea ice variability reproduce the ENSO‐BKS correlation. We conclude that ENSO‐correlated winter BKS temperature variations are dependent on coincidental sea ice changes. Plain Language Summary: Naturally occurring changes in the tropical Pacific Ocean, for example, the El Niño Southern Oscillation or ENSO, are known to affect weather and climate all across the planet. The influence of ENSO on Europe and North America is relatively well known but if and how ENSO affects Arctic weather and climate is less clear. In this study, we identify a correlation between ENSO and winter temperatures in the Arctic focusing specifically on the Barents and Kara Seas. We then examine a large collection of climate model experiments to see if they reproduce the observed correlation. We find that models, on average, do not. However, a small selection of the model experiments do show a correlation as large or larger than observed. The experiments that do reproduce the observed correlation are those that, by chance, have sea ice variations similar to observed; or are experiments in which sea ice is constrained to perfectly match observations. We conclude that Barents and Kara Sea winter temperature variations are primarily governed by local sea ice changes, which by coincidence, may on occasion correlate with ENSO. Key Points: Observed near‐surface air temperature variations over the Barents‐Kara Sea (BKS) are correlated with El Nino Southern Oscillation (ENSO)Models can reproduce the ENSO‐BKS correlation, but only in realizations that have similar or identical sea ice variations as observedSea ice variations are the proximal cause of ENSO‐correlated BKS temperature changes and may be a manifestation of internal variability [ABSTRACT FROM AUTHOR]

During the early 20th century, the Arctic experienced a period of remarkable warming, often called the early 20th century warming (ETCW). However, the degree of the response to external climate forcing on the Arctic surface air temperature is not well understood. Climate simulations using a state‐of‐the‐art climate model of Meteorological Research Institute (MRI‐ESM2.0) and multimodel analyses were conducted to better understand ETCW. The MRI‐ESM2.0 historical simulations successfully reproduced the observed ETCW and the corresponding decreases in sea ice extent. Detection and attribution experiments using MRI‐ESM2.0 suggest that internal climate variability and external natural forcings by solar and volcanic activities had major influences on the model‐simulated ETCW, rather than external anthropogenic forcings. Multimodel analyses indicate that the Arctic warming trend during 1911–1940 induced by natural forcings is comparable to the unforced multidecadal internal variability, suggesting major contributions of the internal dynamics and natural forcings to ETCW. Plain Language Summary: Instrumental records show that there was significant warming in the Arctic during the first half of the 20th century, known as the early 20th century warming (ETCW). Climate simulations using a state‐of‐the‐art climate model of Meteorological Research Institute (MRI‐ESM2.0) suggest that external natural forcings, i.e., long‐lasting quiet volcanic activity and increased solar activity, influenced the model‐simulated ETCW and associated sea ice decrease. Multimodel analyses indicate the robustness of the MRI‐ESM2.0 results and suggest that the climatic response of Arctic surface air temperature to external natural forcings in the ETCW period is comparable to the unforced multidecadal internal variability of the models, suggesting a major contribution of unforced multidecadal internal variability and natural forcings to ETCW. Key Points: Climate model MRI‐ESM2.0 reproduces the Arctic surface air temperature rising and associated sea ice loss observed in the early 20th centuryMRI‐ESM2.0 results indicate that the natural forcings and the internal variability are main contributors to Arctic warming during 1920–1940Multimodel analyses suggest the Arctic warming response to natural forcings in 1911–1940 is comparable to the unforced internal variability [ABSTRACT FROM AUTHOR]

Tundra dominates two‐thirds of the unglaciated, terrestrial Arctic. Although this region has experienced rapid and widespread changes in vegetation phenology and productivity over the last several decades, the specific climatic drivers responsible for this change remain poorly understood. Here we quantified the effect of winter snowpack and early spring temperature conditions on growing season vegetation phenology (timing of the start, peak, and end of the growing season) and productivity of the dominant tundra vegetation communities of Arctic Alaska. We used daily remotely sensed normalized difference vegetation index (NDVI), and daily snowpack and temperature variables produced by SnowModel and MicroMet, coupled physically based snow and meteorological modeling tools, to (1) determine the most important snowpack and thermal controls on tundra vegetation phenology and productivity and (2) describe the direction of these relationships within each vegetation community. Our results show that soil temperature under the snowpack, snowmelt timing, and air temperature following snowmelt are the most important drivers of growing season timing and productivity among Arctic vegetation communities. Air temperature after snowmelt was the most important control on timing of season start and end, with warmer conditions contributing to earlier phenology in all vegetation communities. In contrast, the controls on the timing of peak season and productivity also included snowmelt timing and soil temperature under the snowpack, dictated in part by the snow insulating capacity. The results of this novel analysis suggest that while future warming effects on phenology may be consistent across communities of the tundra biome, warming may result in divergent, community‐specific productivity responses if coupled with reduced snow insulating capacity lowers winter soil temperature and potential nutrient cycling in the soil. [ABSTRACT FROM AUTHOR]

Questions: Shrub vegetation has been expanding across much of the rapidly changing Arctic. Yet, there is still uncertainty about the underlying drivers of shrub community composition. Here, we use extensive vegetation surveys and a trait-based approach to answer the following questions: which abiotic and biotic factors explain abundance of shrub species and functional groups in the Arctic tundra, and can we interpret these relationships using plant traits related to resource acquisition? Location: Nuup Kangerlua (Godthåbsfjord), western Greenland. Methods: We tested the power of nine climatic, topographic and biotic variables to explain the abundances of nine shrub species using a Bayesian hierarchical modelling framework. Results: We found highly variable responses among species and functional groups to both abiotic and biotic environmental variation. The overall most important abiotic explanatory variable was annual air temperature variability, which was highly correlated with winter minimum air temperature. Functional community composition and graminoid abundance were the most influential biotic factors. While we did not find systematic patterns between shrub abundances and abiotic variables with regard to resource acquisition traits, these traits did explain relationships between shrub abundances and biotic variables. Conclusions: Shrub abundance responses to abiotic variables rarely aligned with expectations based on plants’ resource acquisition traits or functional groups. Our results, therefore, indicate that approaches exclusively based on resource acquisition traits might be limited in their ability to predict abundances of individual groups and species, particularly in response to complex abiotic environments. However, integrating community theory and functional trait concepts represents a promising pathway to better predict biotic interactions and ultimately responses of dominant shrub vegetation to rapid environmental changes across the arctic tundra biome. [ABSTRACT FROM AUTHOR]

The National Oceanic and Atmospheric Administration (NOAA) maintains an operational analysis for monitoring trends in global surface temperature. Because of limited polar coverage, the analysis does not fully capture the rapid warming in the Arctic over recent decades. Given the impact of coverage biases on trend assessments, we introduce a new analysis that is spatially complete for 1850–2018. The new analysis uses air temperature data in the Arctic Ocean and applies climate reanalysis fields in spatial interpolation. Both the operational analysis and the new analysis show statistically significant warming across the globe and the Arctic for all periods examined. The analyses have comparable global trends, but the new analysis exhibits significantly more warming in the Arctic since 1980 (0.598°C dec−1 vs. 0.478°C dec−1), and its trend falls outside the 95% confidence interval of its operational counterpart. Trend differences primarily result from coverage gaps in the operational analysis. Plain Language Summary: NOAA provides a suite of climate services to government, business, academia, and the public to support informed decision‐making. Among these services is the State of the Climate report, which is a collection of monthly summaries recapping climate‐related occurrences across the globe. This report relies heavily upon NOAA's global surface temperature data set to depict recent monthly conditions and long‐term changes. Our research introduces a new edition of this flagship data set that is based upon additional temperature data and improved scientific methods. The new data set extends back to 1850 and has complete coverage of all land and ocean areas for the first time. These improvements are particularly important in the Arctic, which has warmed more rapidly than the rest of the planet in recent decades, and the new data set likewise has larger trends than its predecessor in that part of the world. The introduction of this new data set is consistent with the NOAA practice of periodically developing improved versions of its foundational datasets, the goal being to ensure the best possible representation of historical conditions across the globe. The results of this study suggest that the new data set can substantially contribute to future NOAA monitoring and assessment activities. Key Points: NOAA's global surface temperature analysis has limited polar coverage, resulting in a small cold bias in recent decadesWe create a spatially complete analysis for 1850–2018 using Arctic air temperatures and climate reanalysis fieldsFull coverage has a slight impact on global trends, but it significantly increases warming rates in the Arctic since at least the 1980s [ABSTRACT FROM AUTHOR]

Arctic animals inhabit some of the coldest environments on the planet and have evolved physiological mechanisms for minimizing heat loss under extreme cold. However, the Arctic is warming faster than the global average and how well Arctic animals tolerate even moderately high air temperatures (Ta) is unknown.Using flow‐through respirometry, we investigated the heat tolerance and evaporative cooling capacity of snow buntings (Plectrophenax nivalis; ≈31 g, N = 42), a cold specialist, Arctic songbird. We exposed buntings to increasing Ta and measured body temperature (Tb), resting metabolic rate (RMR), rates of evaporative water loss (EWL), and evaporative cooling efficiency (the ratio of evaporative heat loss to metabolic heat production).Buntings had an average (±SD) Tb of 41.3 ± 0.2°C at thermoneutral Ta and increased Tb to a maximum of 43.5 ± 0.3°C. Buntings started panting at Ta of 33.2 ± 1.7°C, with rapid increases in EWL starting at Ta = 34.6°C, meaning they experienced heat stress when air temperatures were well below their body temperature. Maximum rates of EWL were only 2.9× baseline rates at thermoneutral Ta, a markedly lower increase than seen in more heat‐tolerant arid‐zone species (e.g., ≥4.7× baseline rates). Heat‐stressed buntings also had low evaporative cooling efficiencies, with 95% of individuals unable to evaporatively dissipate an amount of heat equivalent to their own metabolic heat production.Our results suggest that buntings' well‐developed cold tolerance may come at the cost of reduced heat tolerance. As the Arctic warms, and this and other species experience increased periods of heat stress, a limited capacity for evaporative cooling may force birds to increasingly rely on behavioral thermoregulation, such as minimizing activity, at the expense of diminished performance or reproductive investment. [ABSTRACT FROM AUTHOR]