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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]

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]

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]

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]

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]

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]

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]

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]

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

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

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

Most climate models neglect cloud longwave (LW) scattering because scattering is considered negligible compared to strong LW absorption by clouds and greenhouse gases. While this rationale is valid for simulating extrapolar regions, it is questionable for the polar regions, where the atmosphere is dry and hence has weak absorption, and ice clouds that have strong scattering capability frequently occur. Using the slab‐ocean Community Earth System Model, we show that ice cloud LW scattering can warm winter surface air temperature by 0.8–1.8 K in the Arctic and 1.3–1.9 K in the Antarctic, while this warming becomes much weaker in polar summer. Such scattering effect cannot be correctly assessed when sea surface temperature and sea ice are prescribed as this effect is manifested through a surface‐atmosphere coupling. Cloud LW scattering is a necessity for the correct simulation of polar climate and surface radiation budget, especially in the winter. Plain Language Summary: Cloud longwave scattering has never been deemed as a necessity in climate models. Out of all climate models in the IPCC fifth and sixth assessments, only three modeling centers have longwave scattering included in their models. Our study explained why the traditional wisdom of neglecting longwave scattering breaks down for the simulation of high‐latitude climate in the fully coupled models. We showed the critical importance of atmosphere‐surface radiative coupling for correctly assessing the role of cloud longwave scattering in the model simulation of climate mean state as well as climate changes, an issue overlooked by all previous studies. We argued that the cloud longwave scattering is a necessity in climate models, not an option. Key Points: Cloud longwave scattering is more important in the polar regions than the extrapolar regionsBy surface‐atmosphere radiative coupling, cloud longwave scattering can warm the polar surface, more in the winter than in the summerCloud longwave scattering is a necessity instead of an option for correctly simulating polar climate and surface energy budget [ABSTRACT FROM AUTHOR]

Mercury is found in Arctic marine mammals that are important in the diet of northern Indigenous peoples. The objectives of the present long‐term study, spanning a 45‐yr period, were to 1) investigate the temporal trends of total mercury (THg; muscle and liver) and selenium (Se; liver) in ringed seals (Pusa hispida) from different regions of the Canadian Arctic; and 2) examine possible relationships with age, diet, and climate parameters such as air temperature, precipitation, climatic indices, and ice‐coverage. Ringed seals were collected by hunters in northern communities in the Beaufort Sea, Central Arctic, Eastern Baffin Island, Hudson Bay, and Ungava/Nunatsiavut regions (Canada) between 1972 and 2017. Mercury levels did not change through time in seal liver, but THg levels in muscle decreased in seals from Hudson Bay (−0.91%/yr) and Ungava/Nunatsiavut (−1.30%/yr). Carbon stable isotope values in seal muscle decreased significantly through time in 4 regions. Selenium‐to‐THg ratios were found to be >1 for all years and regions. Variation partitioning analyses across regions indicated that THg trends in seals were mostly explained by age (7.3–21.7%), climate parameters (3.5–12.5%), and diet (up to 9%); climate indices (i.e., Arctic and North Atlantic Oscillations, Pacific/North American pattern) explained the majority of the climate portion. The THg levels had a positive relationship with Arctic Oscillation for multiple regions. Associations of THg with air temperature, total precipitation, and sea‐ice coverage, as well as with North Atlantic Oscillation and Pacific/North American pattern were found to vary with tissue type and geographical area. Environ Toxicol Chem 2020;39:2462–2474. © 2020 Her Majesty the Queen in Right of Canada. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Reproduced with the permission of the Minister of Fisheries and Oceans Canada. [ABSTRACT FROM AUTHOR]

Recent studies have used satellite data to estimate the response of top‐of‐atmosphere (TOA) radiative fluxes to surface temperature changes in the Arctic. The satellite‐observed radiative response is indicative of Arctic climate sensitivity that determines future Arctic warming. However, it remains ambiguous whether the satellite‐observed radiative response is invariable because the time period covered by satellite data reflects a rapidly changing transient Arctic climate state with considerable sea ice loss. Using NASA's Clouds and Earth's Radiant Energy System (CERES) observations from 2000 to 2018, this study evaluates the invariability of the radiative response by comparing the radiative response of the high sea ice concentration (SIC) period to that of the low SIC period. The results show that the net radiative response remains approximately unchanged regardless of the SIC (−0.19 ± 0.44 and 0.15 ± 0.16 W m−2 K−1 for high and low SIC periods, respectively). In addition, seven of the 11 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) demonstrated that the modeled radiative responses are stable. The ERA‐interim reanalysis estimates show that regionally confined changes in individual radiative feedbacks such as albedo, lapse rate, water vapor, and clouds do not vary considerably. Consequently, we infer that the radiative response in the Arctic may remain stable even under rapid Arctic climate change. Hence, the Arctic climate sensitivity can be quantified with present satellite observations. Key Points: Satellite‐observed radiative response to surface air temperature change remains unchanged under sea ice retreat over the Arctic regionRegionally confined changes in individual radiative feedbacks cannot considerably change the radiative response in the ArcticThe majority of the climate models demonstrated that the Arctic radiative response is insensitive to sea ice loss in the near future [ABSTRACT FROM AUTHOR]

Anthropogenic climate disruption, including temperature and precipitation regime shifts, has been linked to animal population declines since the mid‐20th century. However, some species, such as Arctic‐breeding geese, have thrived during this period. An increased understanding of how climate disruption might link to demographic rates in thriving species is an important perspective in quantifying the impact of anthropogenic climate disruption on the global state of nature. The Greenland barnacle goose (Branta leucopsis) population has increased tenfold in abundance since the mid‐20th century. A concurrent weather regime shift towards warmer, wetter conditions occurred throughout its range in Greenland (breeding), Ireland and Scotland (wintering) and Iceland (spring and autumn staging). The aim of this study was to determine the relationship between weather and demographic rates of Greenland barnacle geese to discern the role of climate shifts in the population trend. We quantified the relationship between temperature and precipitation and Greenland barnacle goose survival and productivity over a 50 year period from 1968 to 2018. We detected significant positive relationships between warmer, wetter conditions on the Icelandic spring staging grounds and survival. We also detected contrasting relationships between warmer, wetter conditions during autumn staging and survival and productivity, with warm, dry conditions being the most favourable for productivity. Survival increased in the latter part of the study period, supporting the possibility that spring weather regime shifts contributed to the increasing population trend. This may be related to improved forage resources, as warming air temperatures have been shown to improve survival rates in several other Arctic and northern terrestrial herbivorous species through indirect bottom‐up effects on forage availability. [ABSTRACT FROM AUTHOR]

The effect of future Arctic amplification (AA) on the extratropical atmospheric circulation remains unclear in modeling studies. Using a collection of coordinated atmospheric and coupled global climate model perturbation experiments, we find an emergent relationship between the high‐latitude 1,000–500 hPa thickness response and an enhancement of the Siberian High in winter. This wave number‐1‐like sea level pressure anomaly pattern is linked to an equatorward shift of the eddy‐driven jet and a dynamical cooling response in eastern Asia. Additional simulations, where AA is imposed directly into the model domain by nudging, demonstrate how the sea ice forcing is insufficient by itself to capture the vertical extent of the warming and by extension the amplitude of the response in the Siberian High. This study demonstrates the importance of the vertical extent of the tropospheric warming over the polar cap in revealing the "warm Arctic, cold Siberia" anomaly pattern in future projections. Plain Language Summary: Surface air temperature averaged within the Arctic Circle is rising more than twice as fast as the rate of the globally averaged temperature. This is known as "Arctic amplification" and is the result of numerous feedbacks in the Earth system. This warming is not restricted to the surface, as the temperature is also increasing at least to the middle troposphere in the Arctic. The effects of this warming on weather patterns in the midlatitudes remain uncertain in observations and model simulations. In this study, we conduct a series of climate model experiments to better understand how the vertical extent of warming in the Arctic atmosphere connects to a strengthening of the Siberian High in boreal winter. This high‐pressure response leads to colder air temperatures in eastern Asia through advection. We find that climate models prescribed with only Arctic sea ice loss do not fully capture the vertical extent of warming in the atmosphere, and thus underestimate the linkage between projected Arctic amplification and Eurasian climate. Key Points: Climate models forced only by sea ice anomalies do not capture the vertical extent of Arctic warming during winterIncrease in thickness of the winter 1,000–500 hPa layer is linked to a strengthening of the Siberian High and cold anomalies in eastern AsiaRole of the stratosphere is unclear due to large internal variability at future global warming of 2° C above preindustrial levels [ABSTRACT FROM AUTHOR]

Recent winters have been unique due to the rapid and extreme cooling of the subpolar North Atlantic. Here, we present a novel view on its causes and consequences. Combining in‐situ observations with remote sensing and atmospheric reanalysis data, we show that increased freshening of the subpolar region gives rise to a faster surface cooling in fall and winter. Large freshwater events, in particular, result in pronounced cold anomalies with sharp temperature gradients that promote an enhanced storminess. The storms reinforce the cooling by driving stronger heat losses and modulating the surface flow. Consistent with this mechanism, past freshwater events have been followed by cold anomalies in winter of approximately −2°C and increases in the North Atlantic Oscillation index of up to ∼0.6 within 3 years. We expect that future freshwater discharges into the North Atlantic will amplify the cold anomaly and trigger an enhanced wintertime storminess with far‐reaching climatic implications. Plain Language Summary: Recent winters have been unique due to a rapid and extreme cooling of the subpolar North Atlantic. Combining ocean and atmospheric data, we show that increased freshwater in this region leads to shallower surface layers that adjust faster to the lower air temperature in fall and winter. The faster surface cooling increases the south‐north temperature gradient, which promotes the development of storms. The storms, in turn, reinforce the cooling by modulating the surface flow. Accordingly, past freshwater events have been followed by an extremely cold ocean surface in the subpolar North Atlantic in winter and major changes in large‐scale weather patterns. We expect that future freshwater discharges from Greenland and the Arctic will amplify the cooling and trigger an enhanced wintertime storminess with far‐reaching implications for the climate. Key Points: Large freshwater events result in distinct cold anomalies with sharp temperature gradients in the subpolar North Atlantic in winterA strong, freshwater‐induced cold anomaly promotes an enhanced storminess, which reinforces the anomaly by modulating the surface flowConsistent with this mechanism, large freshwater events in the past have preceded positive North Atlantic Oscillation periods in winter [ABSTRACT FROM AUTHOR]

Over the past few decades the Arctic has warmed up more than the lower latitudes. Soil organic carbon (SOC) in the Arctic is vulnerable to climate change, and carbon dioxide (CO2) produced via SOC decomposition can amplify atmospheric temperature increase. Although SOC composition is relevant to decomposability, studies on its compositional changes with warming are scarce, particularly in the Arctic. Therefore, we investigated the responses of SOC and the bacterial community to climate manipulation under Cassiope and Salix heath vegetation communities in permafrost‐affected soil in Zackenberg, Greenland. After 8–9 years of experimental warming, we evaluated changes in SOC quantity and quality of three density fractions of soil: free light fraction (FLF), occluded light fraction (OLF) and heavy fraction (HF). The SOC content at 0–5‐cm depth was significantly reduced with warming under Cassiope, and it was accompanied by decreased FLF content, attributed to accelerated decomposition of the FLF by warming. However, SOC molecular composition and bacterial community composition were not affected by warming. By contrast, there was no warming effect on SOC under Salix, which could be partially due to smaller temperature increases caused by higher moisture levels associated with larger silt and clay contents, or to different responses of the dominant plant species to temperature. In both soils, more than 55% of SOC was associated with minerals, and its molecular composition indicated microbial decomposition. Our results suggested that long‐term warming in the high Arctic could induce the loss of SOC, particularly in the FLF; however, the response could vary with vegetation type and/or soil properties, that is, soil texture. Highlights: We show decreased SOC with long‐term (8‐year) warming of heath soils in the high ArcticParticularly, the free light fraction of SOC in topsoil decreased with warming in a Cassiope heath siteMineral‐associated SOC content was more than 55% and showed signs of microbial processingEffects of warming differed according to soil properties and/or plant community composition [ABSTRACT FROM AUTHOR]

We have investigated the effects of land use on past climate change by means of a new 15‐member ensemble of the HadGEM3‐A‐N216 model, usually used for event attribution studies. This ensemble runs from 1960 to 2013, and includes natural external climate forcings with the addition of human land use changes. It supports previously‐existing ensembles, either with only natural forcings, or with all forcings (both anthropogenic and natural, including land use changes), in determining the contribution to the change in risk of extreme events made by land use change. We found a significant difference in near‐surface air temperature trends over land, attributable to the effects of human land use. The main part of the signal derives from a relative cooling in Arctic regions which closely matches that of deforestation. This cooling appears to spread by polar amplification. A similar pattern of change is seen in latent heat flux trend, but significant rainfall change is almost entirely absent. [ABSTRACT FROM AUTHOR]

Globally, 2017 was one of the three warmest years on record at the surface of the Earth, despite neutral or weak La Niña conditions. Warmth was widespread in the climate system, with ocean heat and atmospheric temperatures also among the top three years. Arctic and Antarctic sea ice extents were below the long‐term average, and a number of months had record low extents. In the UK and Europe there were a number of unusual weather events, and high spring and summer temperatures affected areas of Europe, North Africa and the Middle East. We summarise aspects of global and regional climate in 2017. [ABSTRACT FROM AUTHOR]

The increased extremewarm and decreased extreme cold temperature events across the Arctic strongly influence the natural environment as well as the societal activities. This study investigates temporal and spatial variability of wintertime extreme high and low temperature events defined by the 95 and 5% percentiles across the Arctic and subarctic regions, respectively (north of 60°N) using data from 238 stations in the Global Summary of the Day for the period 1979-2016. Empirical orthogonal function analyses indicate that the first modes (which account for 30-35% of the total variance) are out-of-phase between northern Europe, western and central Russia, and northeastern North America, and that this appears to be related to the Arctic Oscillation (AO) and the Northern Atlantic Oscillation. The second modes explain about 8% of the total variance. During the positive phase of the first and second modes the anomalous northeasterly and northerly winds decrease Arctic extreme high and increase extreme low temperature occurrences; while the anomalous southerly and southwesterly winds have the opposite effect. Symmetric and asymmetric effects of the AO index on extreme temperature events refer to the difference and sum between the composite of its positive and negative phases. The symmetric components of the spatial patterns are similar to those of the first modes. The asymmetric components occur mainly over western and central Russia for extreme high and low temperatures, respectively. In addition the impacts of six other large-scale climate modes are also explored. [ABSTRACT FROM AUTHOR]

Since temperature extremes have a strong impact on environment and society, it is crucial to understand their underlying mechanisms. While their relationship to the large-scale atmospheric circulation has been comprehensively investigated, the role of physical processes in the formation of air masses with extreme temperatures is less well understood. This study presents a Lagrangian analysis of the 0.1% most extreme six-hourly hot and cold events in three European regions (UK, Central Europe, Balkans) for the time period 1989-2009. The results provide insight into typical transport patterns and physical processes (adiabatic compression, radiation, surface heat fluxes) occurring along the trajectories of extreme temperature air masses. Cold events in Europe are most frequently induced by advection of cold air masses from the Arctic and Russia. The transport to the target region is characterized by a temperature increase caused by adiabatic compression and, in the maritime setting of the UK, also by diabatic heating due to surface sensible heat fluxes. Despite the warming along the trajectories, the extremeness of the associated 2 m temperature increases, due to the dislocation of the air mass to regions with a milder climate. Hot events are generally associated with weaker horizontal transport, but strong adiabatic warming and local temperature increase caused by enhanced radiation and surface heat fluxes. This in situ warming is particularly strong in Central Europe. Evaluating the temperature evolution along the trajectories reveals that hot and cold extremes develop on a similar time-scale of 2-3 days. This time-scale is mostly set by physical processes for hot extremes and controlled by advective transport for cold extremes. The diagnostics applied in this study lead to an improved process understanding that can provide a basis for more accurate predictions of temperature extremes. [ABSTRACT FROM AUTHOR]

The article investigates the effects of pollution-derived sulfuric acid aerosols on the aerosol-cloud-radiation interaction over the Arctic on February 1990 as well as the possible effects of dehydration-greenhouse feedback on the Arctic climate during February 1990, using simulations from Arctic regional climate model for the said month. Findings reveal the significant effect of DGF on cloud, atmospheric dehydration and temperature over the coldest part of the Arctic, the Central and Eurasian Arctic. It was also found out that increased aerosol concentration, as a result of DGF, leads to stronger cloud lifetime over warmer areas.