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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]

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

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

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]

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

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