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

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

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

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]

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

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

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]

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]

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]

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]

Active layer probing in northern Sweden, northeast Greenland, and central Svalbard indicates active layer thickening has occurred at Circumpolar Active Layer Monitoring (CALM) sites with long‐term, continuous observations, since the sites were established at these locations in 1978, 1996, and 2000, respectively. The study areas exhibit a reverse latitudinal gradient in average active layer thickness (ALT), which is explained by site geomorphology and climate. Specifically, Svalbard has a more maritime climate and thus the thickest active layer of the study areas (average ALT = 99 cm, 2000–2018). The active layer is thinnest at the northern Sweden sites because it is primarily confined to superficial peat. Interannual variability in ALT is not synchronous across this Nordic Arctic region, but study sites in the same area respond similarly to local meteorology. ALT correlates positively with thawing degree days in Sweden and Greenland, as has been observed in other Arctic regions. However, ALT in Svalbard correlates with freezing degree days, where the maritime Arctic climate results in relatively high and variable winter air temperatures. The difference in annual ALT at adjacent sites is attributed to differences in snow cover and geomorphology. From 2000 to 2018, the average rate of active layer thickening at the Nordic Arctic CALM probing sites was 0.5 cm/yr. The average rate was 1 cm/yr for Nordic Arctic CALM database sites with significant trends, which includes a borehole in addition to probing sites. This range is in line with the circum‐Arctic average of 0.8 cm/yr from 2000 to 2018. [ABSTRACT FROM AUTHOR]

The predicted increase of ground temperatures in the Arctic results in the deepening of the active layer and intensification of geochemical processes. Determining the responses of riparian soil systems to surrounding hydrological flows is important for understanding seasonal changes in hydrological processes. In this study, one soil core from a polygon rim (close to the Taz River, TA) and two soil cores from a riverine terrace (close to the Syoyakha River, SY and Murtyyakha River, MU) in Western Siberia, Russia, and their suprapermafrost water, adjacent surface flows, and river water were sampled for analysis of geochemical elements. Results showed that most elements above their respective detection limits began accumulating in the underlying gleyed layer during September‐October in response to the deepest thaw in the active layer. This study focused on the highly mobile elements in the deepest layer; and found that the transport of organic matter in the upper layer carried these elements to both surface water ponds/flows and suprapermafrost water, and further, to the rivers. The efflux of released elements from surface soil to surrounding surface water appeared to be low. The best linear correlation for both surface flows and river water was with Mn; therefore, Mn may be a proxy for predicting the processes occurring within the active layer during the annual summer‐autumn thaw. Moreover, landscapes with different ice contents may experience changes in the elements transported to surface waters. A general conceptual model for the response of elements to the thawing‐freezing process of the active layer is established. Plain Language Summary: The rapidly increasing atmospheric temperature in the Arctic has led to the feedback of permafrost thawing, which increases the depth of the active layer and accelerates chemical weathering. These processes may cause a further release of chemical substances to adjacent aquatic landscapes. Here, we investigated the horizontal and vertical transport of geochemical elements through surface flow and suprapermafrost water to river water from three cryogenic soil cores in the Arctic tundra. The results showed that most elements accumulated in the gleyed layer, which was deepest in the active layer during the thawing season. Mn, Ca, Mg, Al, and Ti showed the highest mobility from soil to suprapermafrost water to the surface flows/rivers, while Mn was the only element that could migrate from topsoil and suprapermafrost water to surface water and river water, indicating that Mn may be a proxy for predicting the processes occurring in the active layer during summer‐autumn thawing. Key Points: Locate geochemical tracer to identify active layers during summer permafrost meltAssessed mobility of releasing geochemical elements to surrounding water bodiesIdentified permafrost active layer using geochemical elements' concentrations [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]