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To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the "warm Arctic, cold East Asia" (WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day (or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day (or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four (ten) times larger than the ice-induced East Asian cooling in the present-day (future) experiment; the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60% (80%) to the Arctic winter warming in the present-day (future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-loss-induced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling. [ABSTRACT FROM AUTHOR]

Birds maintain some of the highest body temperatures among endothermic animals. Often deemed a selective advantage for heat tolerance, high body temperatures also limits birds' thermal safety margin before reaching lethal levels. Recent modelling suggests that sustained effort in Arctic birds might be restricted at mild air temperatures, which may require reductions in activity to avoid overheating, with expected negative impacts on reproductive performance. We measured within-individual changes in body temperature in calm birds and then in response to an experimental increase in activity in an outdoor captive population of Arctic, cold-specialised snow buntings (Plectrophenax nivalis), exposed to naturally varying air temperatures (− 15 to 36 °C). Calm buntings exhibited a modal body temperature range from 39.9 to 42.6 °C. However, we detected a significant increase in body temperature within minutes of shifting calm birds to active flight, with strong evidence for a positive effect of air temperature on body temperature (slope = 0.04 °C/ °C). Importantly, by an ambient temperature of 9 °C, flying buntings were already generating body temperatures ≥ 45 °C, approaching the upper thermal limits of organismal performance (45–47 °C). With known limited evaporative heat dissipation capacities in these birds, our results support the recent prediction that free-living buntings operating at maximal sustainable rates will increasingly need to rely on behavioural thermoregulatory strategies to regulate body temperature, to the detriment of nestling growth and survival. [ABSTRACT FROM AUTHOR]

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

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

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

The new permanent seismic station SVZ started working in Arctic (Severnaya Zemlya archipelago, Bolshevik Island), we discuss the first results of the local seismicity study. We have processed 46 local seismic events for 2017–2022. Data processing using a single seismic sensor is difficult, but using waveforms and spectral-temporal analysis of P, S, and surface waves, it is possible to separate shallow earthquakes from glacial events. We distinguish two types of icequakes—glacier-related events and pulses. An increase in seismic background noise is related to processes of glacial nature in summertime. Data processing allows to obtain the main peculiarities of local seismicity, i.e., mutual connection of glacial processes and crustal seismicity. We show the presence of icequakes induced by local crustal events; their epicenters confined to the ice domes edges. Spatio-temporal sequence and the rate of events migration show that the glacial events are a result of the defusing deformations process in the glaciers caused by the impact of shallow tectonic earthquakes. Thousands of pulsed and high-frequency micro-oscillations associate with the sea ice sheet or lake ice. The temporal variation of events' number and energy per day correlates with air temperature temporal variations. Moreover, there is a sharp increase in the number of pulses with sharp temperature changes. The greatest activity of this pulsed events is in winter and especially in March, connected with ice surface destruction. In case a network deployment is not feasible, even a single seismic station allows to get a useful information about the glacial and seismic processes. [ABSTRACT FROM AUTHOR]

The results of numerical experiments with a chemistry–climate model of the lower and middle atmosphere are presented to study the sensitivity of the polar stratosphere of the Northern and Southern Hemispheres to sea surface temperature (SST) variability, both as a result of interannual variability associated with the Southern Oscillation, and because of long-term increases in SST under global warming. An analysis of the results of model experiments showed that for both scenarios of SST changes, the response of the polar stratosphere for the Northern and Southern Hemispheres is very different. In the Arctic, during the El Niño phase, conditions are created for the polar vortex to become less stable, and in the Antarctic, on the contrary, for it to become more stable, which is expressed in a weakening of the zonal wind in the winter in the Arctic and its increase in the Antarctic, followed by a spring decrease in temperature and concentration of ozone in the Antarctic and their increase in the Arctic. Global warming creates a tendency for the polar vortex to weaken in winter in the Arctic and strengthen it in the Antarctic. As a result, in the Antarctic, the concentration of ozone in the polar stratosphere decreases both in winter (June–August) and, especially, in spring (September–November). Global warming may hinder ozone recovery which is expected as a result of the reduced emissions of ozone-depleting substances. The model results demonstrate the dominant influence of Brewer–Dobson circulation variability on temperature and ozone in the polar stratosphere compared with changes in wave activity, both with changes in SST in the Southern Oscillation and with increases in SST due to global warming. [ABSTRACT FROM AUTHOR]

This study presents an unmanned aerial vehicle (UAV) platform used to resolve horizontal and vertical patterns of CO2 and CH4 mole fractions within the lower part of the atmospheric boundary layer. The obtained data contribute important information for upscaling fluxes from natural ecosystems over heterogeneous terrain, and for constraining hot spots of greenhouse gas (GHG) emissions. This observational tool, therefore, has the potential to complement existing stationary carbon monitoring networks for GHGs, such as eddy covariance towers and manual flux chambers. The UAV platform is equipped with two gas analyzers for CO2 and CH4 which are connected sequentially. In addition, a 2D anemometer is deployed above the rotor plane to measure environmental parameters including 2D wind speed, air temperature, humidity, and pressure. Laboratory and field tests demonstrate that the platform is capable of providing data with reliable accuracy, with good agreement between the UAV data and tower-based measurements of CO2 and CH4 , and wind speed. Using interpolated maps of GHG mole fractions, with this tool we assessed the signal variability over a target area, and identified potential hot spots. Our study shows that the UAV platform provides information about the spatial variability of the lowest part of the boundary layer, which up to this date remains poorly observed, especially in remote areas such as the Arctic. Furthermore, using the profile method, it is demonstrated that the GHG fluxes from a local source can be calculated. Although subject to large uncertainties over the area of interest, the comparison between the eddy covariance method and UAV-based calculations showed acceptable qualitative agreement. [ABSTRACT FROM AUTHOR]

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

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

The Barents Sea is experiencing large trends in sea ice decline and increasing surface temperatures while at the same time, it is a key region of weather variability in the Arctic and therefore predestined for the occurrence of surface weather extremes. In this study, we identify extreme winter seasons in the Barents Sea, based on a multivariate method, as winters with large seasonal-mean anomalies in one or several surface parameters encompassing surface temperature, precipitation, surface heat fluxes and surface net radiation. Using large-ensemble climate model data for historical (S2000) and end-of-century (S2100) projections following a RCP8.5 emission scenario, we find distinct clusters of extreme winters that are characterized by similar combinations of anomalies in these key surface weather parameters. In particular, we find that, during extreme winters, seasonal-mean anomalies in surface temperature are usually spatially extended with a maximum over sea ice in S2000 simulations, which shifts towards the continental land masses in a warmer climate, as the formation of a warm or cold air reservoir is being hampered by the increasing area of open ocean. Several extreme winters are selected for a detailed investigation of their substructure focusing on the relative importance of anomalies in the occurrence of synoptic-scale weather systems and anomalous surface boundary conditions for the formation of such seasons. Large combined anomalies in the key surface parameters result mainly from the accumulation of recurrent short-term events that are linked to distinct patterns of anomalous frequencies in cyclones, anticyclones and cold air outbreaks. While large seasonal-mean anomalies in surface air temperature can be linked to large-scale patterns facilitating the horizontal advection of relatively warmer (colder) air, which coincides with a lack (surplus) of cold air outbreaks, precipitation anomalies are characterized by local anomalies in cyclone and anticyclone frequency. Additionally, anomalous surface boundary conditions – that is sea ice concentration and sea surface temperatures – facilitate the formation of persistent anomalous surface conditions or further enhance atmospherically driven anomalies due to anomalous surface heat fluxes. In a warmer climate, we find extreme winters with similar substructures as in S2000. However, the increasing distance of the Barents Sea to the sea ice edge causes a decreasing magnitude in seasonal-mean anomalies of surface air temperatures and the atmospheric components of the surface energy balance. A decrease in the variability of both sea ice and sea surface temperatures indicates a decreasing importance in anomalous surface boundary conditions for the formation of future extreme winters in the Barents Sea, while the robust link shown for surface weather systems persists in a warmer climate. [ABSTRACT FROM AUTHOR]

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

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

Maintaining frozen ground stability in the Arctic and sub-Arctic is a continuing challenge, particularly with climate warming. One engineering solution to tackle this problem is the use of thermosyphons, an artificial ground cooling apparatus, to stabilize the frozen ground. Passive thermosyphons function when the above-ground condenser section is colder than the subsurface evaporator section. This occurs when the ambient air temperature is colder than the subsurface ground temperature. Passive thermosyphons absorb thermal energy from subsurface ground layers and reject it into the atmosphere. Therefore, this passive technology augments natural ground cooling during the cold winter months. Hybrid thermosyphons operate in passive and active (powered refrigeration) modes. For remote locations, the electrical requirements for active thermosyphons limit their application. However, solar power is a promising method to provide an electrical source to operate active and hybrid thermosyphons. This technical note presents the results from an experimental study that tested the use of a solar array system that powered a refrigeration unit, which provided active cooling to a hybrid thermosyphon. The energy that was generated from the solar array successfully operated the refrigeration unit, provided active cooling to the hybrid thermosyphon, and lowered soil temperatures. This study showed the potential for the future development and application of a more energy-efficient off-grid hybrid thermosyphon system. Maintaining frozen ground stability in the Arctic and sub-Arctic is a constant challenge, especially as the climate is warming. Engineering solutions, such as artificial ground freezing techniques to stabilize the frozen ground, are commonly used in cold climates. Freezing the ground with artificial freezing systems is achieved without power when air temperatures are below freezing. When air temperatures are above freezing, the passive system seizes; however, freezing could continue if linked to a mechanical refrigeration unit. The electrical requirements of this cooling technique, when temperatures are above freezing, severely restrict their use in remote areas. This technical note presents an experimental study where a solar array system was tested for powering a refrigeration unit connected to an artificial freezing system. Freezing was extended at warmer air temperatures (above freezing) with a refrigeration unit that was operated by solar array-generated energy. The refrigeration unit successfully operated, and soil temperatures decreased. Supplying this ground cooling technique with a solar powered system could be possible for future applications. [ABSTRACT FROM AUTHOR]

Local weather forecasts in the Arctic outside of settlements are challenging due to the dearth of ground-level observation stations and high computational costs. During winter, these forecasts are critical to help prepare for potentially hazardous weather conditions, while in spring, these forecasts may be used to determine flood risk during annual snow melt. To this end, a hybrid VMD-WT-InceptionTime model is proposed for multi-horizon multivariate forecasting of remote-region temperatures in Alaska over short-term horizons (the next seven days). First, the Spearman correlation coefficient is employed to analyze the relationship between each input variable and the forecast target temperature. The most output-correlated input sequences are decomposed using variational mode decomposition (VMD) and, ultimately, wavelet transform (WT) to extract time-frequency patterns intrinsic in the raw inputs. The resulting sequences are fed into a deep InceptionTime model for short-term forecasting. This hybrid technique has been developed and evaluated using 35+ years of data from three locations in Alaska. Different experiments and performance benchmarks are conducted using deep learning models (e.g., Time Series Transformers, LSTM, MiniRocket), and statistical and conventional machine learning baselines (e.g., GBDT, SVR, ARIMA). All forecasting performances are assessed using four metrics: the root mean squared error, the mean absolute percentage error, the coefficient of determination, and the mean directional accuracy. Superior forecasting performance is achieved consistently using the proposed hybrid technique. [ABSTRACT FROM AUTHOR]

Healthy Arctic marine ecosystems are essential to the food security and sovereignty, culture, and wellbeing of Indigenous Peoples in the Arctic. At the same time, Arctic marine ecosystems are highly susceptible to impacts of climate change and ocean acidification. While increasing ocean and air temperatures and melting sea ice act as direct stressors on the ecosystem, they also indirectly enhance ocean acidification, accelerating the associated changes in the inorganic carbon system. Yet, much is to be learned about the current state and variability of the inorganic carbon system in remote, high-latitude oceans. Here, we present time series (2016–2020) of pH and the partial pressure of carbon dioxide (p CO 2) from the northeast Chukchi Sea continental shelf. The Chukchi Ecosystem Observatory includes a suite of subsurface year-round moorings sited amid a biological hotspot that is characterized by high primary productivity and a rich benthic food web that in turn supports coastal Iñupiat, whales, ice seals, walrus (Odobenus rosmarus), and Arctic cod (Boreogadus saida). Our observations suggest that near-bottom waters (33 m depth, 13 m above the seafloor) are a high carbon dioxide and low pH and aragonite saturation state (Ωarag) environment in summer and fall, when organic material from the highly productive summer remineralizes. During this time, Ωarag can be as low as 0.4. In winter, when the site was covered by sea ice, pH was <8 and Ωarag remained undersaturated under the sea ice. There were only two short seasonal periods with relatively higher pH and Ωarag , which we term ocean acidification relaxation events. In spring, high primary production from sea ice algae and phytoplankton blooms led to spikes in pH (pH > 8) and aragonite oversaturation. In late fall, strong wind-driven mixing events that delivered low-CO 2 surface water to the shelf also led to events with elevated pH and Ωarag. Given the recent observations of high rates of ocean acidification and a sudden and dramatic shift of the physical, biogeochemical, and ecosystem conditions in the Chukchi Sea, it is possible that the observed extreme conditions at the Chukchi Ecosystem Observatory are deviating from the carbonate conditions to which many species are adapted. [ABSTRACT FROM AUTHOR]

The cloud type product 2B-CLDCLASS-LIDAR based on CloudSat and CALIPSO from June 2006 to May 2017 is used to examine the temporal and spatial distribution characteristics and interannual variability of eight cloud types (high cloud, altostratus, altocumulus, stratus, stratocumulus, cumulus, nimbostratus, and deep convection) and three phases (ice, mixed, and water) in the Arctic. Possible reasons for the observed interannual variability are also discussed. The main conclusions are as follows: (1) More water clouds occur on the Atlantic side, and more ice clouds occur over continents. (2) The average spatial and seasonal distributions of cloud types show three patterns: high clouds and most cumuliform clouds are concentrated in low-latitude locations and peak in summer; altostratus and nimbostratus are concentrated over and around continents and are less abundant in summer; stratocumulus and stratus are concentrated near the inner Arctic and peak during spring and autumn. (3) Regional averaged interannual frequencies of ice clouds and altostratus clouds significantly decrease, while those of water clouds, altocumulus, and cumulus clouds increase significantly. (4) Significant features of the linear trends of cloud frequencies are mainly located over ocean areas. (5) The monthly water cloud frequency anomalies are positively correlated with air temperature in most of the troposphere, while those for ice clouds are negatively correlated. (6) The decrease in altostratus clouds is associated with the weakening of the Arctic front due to Arctic warming, while increased water vapor transport into the Arctic and higher atmospheric instability lead to more cumulus and altocumulus clouds. [ABSTRACT FROM AUTHOR]

Scanning micro-X-ray fluorescence analysis with synchrotron radiation was applied to obtain the depth-variation profiles of element compositions of banded clays in Peyungda Lake (Krasnoyarsk krai, Evenkia) located 30 km southwest of the epicenter of the Tunguska event (1908). The age model was confirmed by a dated layer of anomalous thickness related to the fall and explosion of the Tunguska Cosmic Body (TCB). The variations in the element content in dated core layers were compared with the instrumental meteorological observation data over the last century. The regional average annual temperature and element compositions of the coeval bottom sediments (transfer function) were found to be interrelated. The approximation of the transfer function to the sampling depth of the sedimentary section made it possible to reconstruct the air temperature in the studied region over the past 1000 years. The average annual temperature reconstructions in the study area compared with the global temperature reconstructions in the Arctic region for the same period made it possible to reveal general trends and extreme values. [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]

Arctic birds and mammals are physiologically adapted to survive in cold environments but live in the fastest warming region on the planet. They should therefore be most threatened by climate change. We fitted a phylogenetic model of upper critical temperature (TUC) in 255 bird species and determined that TUC for dovekies (Alle alle; 22.4°C)—the most abundant seabird in the Arctic—is 8.8°C lower than predicted for a bird of its body mass (150 g) and habitat latitude. We combined our comparative analysis with in situ physiological measurements on 36 dovekies from East Greenland and forward-projections of dovekie energy and water expenditure under different climate scenarios. Based on our analyses, we demonstrate that cold adaptation in this small Arctic seabird does not handicap acute tolerance to air temperatures up to at least 15°C above their current maximum. We predict that climate warming will reduce the energetic costs of thermoregulation for dovekies, but their capacity to cope with rising temperatures will be constrained by water intake and salt balance. Dovekies evolved 15 million years ago, and their thermoregulatory physiology might also reflect adaptation to a wide range of palaeoclimates, both substantially warmer and colder than the present day. [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]

This article presents a comprehensive documentation and analysis of long-term observations of year-round groundwater occurrences in rivers and various types of taliks under continuous permafrost conditions on Svalbard. Previously thought to be nonexistent, the existence of these taliks has been confirmed through rigorous field observations, geotechnical investigations, and extensive data collection. This discovery holds pivotal implications for our current understanding of permafrost conditions in central Svalbard. The research reveals the presence of several year-round taliks in close proximity to the settlements in Longyearbyen, Pyramiden, and Ny-Ålesund. Importantly, these findings open up opportunities for using these taliks as groundwater reservoirs for extraction of drinking water, either in natural state or with appropriate engineering modifications. Furthermore, climate change may the possibilities in future by expanding the size of these talik reservoirs due to rising air temperatures and increased inflow of fresh water over prolonged summer. The results underscore the importance of including river taliks in continuous permafrost areas in water management strategies for Svalbard and similar Arctic regions. This research not only challenges prior assumptions but also offers valuable insights for sustainable water resource utilization in a changing climate context. [ABSTRACT FROM AUTHOR]

An enhanced Warm Arctic—Cold Eurasia (WACE) pattern has been a notable feature in recent winters of the Northern Hemisphere. However, divergent results between model and observational studies of the WACE still remain. This study evaluates the performance of 39 climate models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating the WACE pattern in winter of 1980–2014 and explores the key factors causing the differences in the simulation capability among the models. The results show that the multimodel ensemble (MME) can better simulate the spatial distribution of the WACE pattern than most single models. Models that can/cannot simulate both the climatology and the standard deviation of the Eurasian winter surface air temperature well, especially the latter, usually can/cannot simulate the WACE pattern well. This mainly results from the different abilities of the models to simulate the range and intensity of the warm anomaly in the Barents Sea—Kara seas (BKS) region. Further analysis shows that a good performance of the models in the BKS area is usually related to their ability to simulate location and persistence of Ural blocking (UB), which can transport heat to the BKS region, causing the warm Arctic, and strengthen the westerly trough downstream, cooling central Eurasia. Therefore, simulation of UB is key and significantly affects the model's performance in simulating the WACE. [ABSTRACT FROM AUTHOR]

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

An increase in warming in the Arctic relative to the rest of the Northern Hemisphere or the globe continues attracting attention, despite the large amount of research being conducted. Possible causes of the Arctic amplification have been considered and continue to be discussed in many articles and reviews. In this article, for the first time, a quantitative assessment of the role of atmospheric transports in the formation of variability and trends in the mean near-surface air temperature (SAT) in the Arctic and at adjacent latitudes of the Northern Hemisphere is carried out and an analytical description of amplification in high latitudes is proposed. For the study, data from NCEP and ERA5 reanalyses for 1989–2020 and a representation of the set of events of air exchange between latitudes in a simple hemispheric atmospheric model under constant conditions at the boundaries, on the basis of which analytical expressions are obtained for the standard deviation ratios (SDRs) and temperature trends in neighboring areas. The degree of closeness between the empirical and model ratios of SDR and trends is taken as a contribution measure of air exchange to the increase in SDR and trends during warming. It has been found that the exchange between the polar and adjacent regions reaches lower latitudes as the polar region expands from 70° N up to 60° N. The latitude to which the polar air propagates on average decreases with the trend taken into account in the SDR, which confirms the effect of warming on the increase in air mass exchange. The model value of the increase in the average air temperature trend in the polar region of an isolated homogeneous atmosphere above the hemisphere relative to the trend in the adjacent region is determined by the ratio of their areas multiplied by the ratio of the trend determination coefficients. An increase in the temperature trend in the polar region of the real atmosphere, according to the NCEP and ERA5 reanalyses for 1989–2020, was compared with the model value, thereby assessing the contribution of air mass exchange to the increase in the temperature trend in the polar region. It was found that the exchange explains 54% of the increase in the air temperature trend (Arctic amplification) in the region of 90–60° N on average per year and 66% in the cold year part relative to the rest of the Northern Hemisphere. If we take into account the established southern boundary of air mass exchange between the polar and adjacent regions, then the amplification of an air temperature trend in the area of 90–60° N relative to the trend in the adjacent area, with which the exchange of air masses occurs, will almost completely (by 93% on average per year) be the result of exchange and, in the area of 90°–70° N, it will mostly be the result of exchange (by 74% on average per year). [ABSTRACT FROM AUTHOR]

The modern unambiguous climate change reveals in a rapid increase of air temperature, which is more distinctly expressed in the Arctic than in any other part of the world, affecting people health and well-being. The main objective of the current research is to explore the inter- and intra-annual changes in thermal stress for people in the Arctic, specifically for two parts of Beringia: Alaska, USA, and Chukotka, Russia, using climatology of the universal thermal climate index (UTCI). Data for 39 locations are taken from the ERA5-HEAT reanalysis for the period 1979–2020. Climatologically, the study area is divided into four subregions in Alaska: North, Interior, West and South, and two in Chukotka: Interior and Coast. The extreme coldest UTCI categories (1 and 2) are most common in coastal locations of northern Alaska and Chukotka, where strong winds exacerbate the low temperatures during winter. The results show that the frequency of category 1 (UTCI<−40°C) varies spatially from a quarter of all hours annually in Alaska North to almost zero in Alaska South. On the other hand, the warmest categories are rarely reached almost everywhere in Alaska and Chukotka, and even categories 7 and 8 (UTCI between +26 and +38°C) are found occasionally only at interior locations. Category 6 with no thermal stress (UTCI between +9 and+26°C) has frequencies up to 3% and 25% in Alaska North and Interior, respectively. The extremely cold thermal stress frequencies have substantially decreased over the 1979–2020 period, especially in Alaska North and Chukotka Coast. At the same time, the number of hours with UTCI in the comfortable category of thermal perception has increased depending on subregion, from 25 to 203 h/year. Overall, a decrease in the UTCI categories of extremely cold stress is coupled with an increase in the comfortable range in both Alaska and Chukotka. The salient conclusion is that, from the point of view of comfort and safety, global warming has a positive impact on the climatology of thermal stress in the Arctic, providing advantages for the development of tourism and recreation. [ABSTRACT FROM AUTHOR]

Space observations (1979–2020) have shown that, over the past 40 years, years with a decrease in the area of summer ice and their thickness prevailed. Over 10 years, negative trends of anomalies in the area and thickness of the ice are –13 and –15%, respectively. A rapid reduction in the area of old ice (>4-year-old) is also noted, because in 1985 it was estimated at 2.7 million km2, while in March 2010 it was 0.34 million km2. The paper analyses paleo sea ice extent during the Holocene (the last 12 000 years) based on empirical IP25 biomarkers (a sea ice proxy with 25 carbon atoms synthesized by the specific Arctic sea ice diatoms Hasleaspp, which have been proven to be a suitable proxy for paleo-sea ice reconstructions) obtained from deep-sea cores from the North Atlantic. The data showed that, during the warm periods of the Early and Middle Holocene, the area of summer sea ice was reduced to a minimum. This confirms the conclusion made earlier in (Kinnard et al., 2011) that the current trend of reducing the area and thickness of ice is unprecedented over the past 1500 years. There is no complete analogue of the climate in the past corresponding to the current level of the CO2 concentration in the atmosphere. The period with CO2 concentrations in the atmosphere similar to the current level was the warm part of the Middle Pliocene between 3 and 4 million years ago with level of the CO2 concentration 450–500 ppm against approximately 420 ppm at present. Paleo-climate reconstructions for this period estimate the global temperature to be 3.0–3.5 ± 0.5°C higher than at the end of the 19th century. Summer air temperatures in the high latitudes of the Northern Hemisphere exceeded the current ones by 8–10°C, and the sea ice in the Arctic shelf seas was completely absent in the summer. Empirical data and model simulations have shown that presently the main driver of the reduction of the Arctic sea ice area is the increase in concentration of CO2 in the atmosphere. At the present time, old sea ice tends to be replaced by seasonal ice, demonstrating a natural shift from the predominance of permanent ice to an ice-free Arctic. In the case of a continuous increase in CO2 concentration in the atmosphere despite emission control measures, one of the scenarios that happened in the past may occur again. [ABSTRACT FROM AUTHOR]

To investigate patterns of horizontal atmospheric latent energy (LE) transport toward the Arctic, we applied the self-organizing maps (SOM) method to the daily vertically integrated horizontal LE flux from ERA5 in winter (January–March) during 1979–2021. A clear picture depicting the LE transport to the Arctic at a synoptic scale then emerged, with four primary transport pathways identified: the northern Europe, the Davis Strait, the Greenland Sea, and the Bering Strait pathways. The four primary pathways occurred at a comparable frequency, and noticeable interannual variability was observed in their time series of frequency during 1979–2021. Further analysis suggested that the northward LE transport through all these pathways is significantly modulated by cyclones, with the northern Europe and the Greenland Sea pathways being mostly affected. Generally, more frequent and stronger cyclones were observed near the entry regions of LE transport compared to other regions. Moreover, this study provides a comprehensive picture of how atmospheric LE transport is related to air temperature, moisture, surface heat flux, and sea ice anomalies over the Arctic Ocean in winter. Through a thermodynamic perspective, we argue that the deleterious impacts of poleward LE transport on Arctic sea ice are to a large extent attributable to the enhanced local atmosphere–ice interactions, which increase downward longwave radiation (DLR) plus turbulent fluxes, consequently warming the surface and promoting the loss of sea ice. According to the quantitative results, among the four primary pathways, LE transport through the Davis Strait and the Greenland Sea could cause the loss of Arctic sea ice most efficiently. [ABSTRACT FROM AUTHOR]

The Arctic is warming faster than anywhere on Earth, and with these warming temperatures, there is likely to be more precipitation falling as rain. This precipitation phase change will have profound impacts on the hydrologic cycle, energy balance, and snow and sea ice mass budgets. Here, we examine the number of rainfall days in the Arctic from three reanalyses, ERA-Interim, ERA5, and MERRA-2, over 1980–2016. We show that the number of rainfall days has increased over this period, predominantly in the autumn and in the North Atlantic and peripheral seas, and the length of the rain season has increased in all reanalyses. This is positively correlated to the number of days with above freezing air temperatures and a lengthening of the warm season. ERA-Interim produces significantly more rainfall days than other reanalyses and CloudSat observations, as well as significantly more rainfall when temperatures are below freezing. Investigation into the cloud microphysics schemes revealed that the scheme employed by ERA-Interim allowed for mixed-phase clouds to form rain at temperatures below freezing following a temperature-dependent phase partitioning function between 250 and 273 K. This simple diagnostic treatment erroneously overestimates rain at temperatures below 273 K and produces unrealistic rainfall compared to ERA5 and MERRA-2. This work highlights the importance of having accurate physics and improving microphysical schemes in models for simulating precipitation in the Arctic and the caution that is warranted for interpreting reanalysis trends. [ABSTRACT FROM AUTHOR]

Primary biological aerosol particles (PBAP) play an important role in the climate system, facilitating the formation of ice within clouds, consequently PBAP may be important in understanding the rapidly changing Arctic. Within this work, we use single-particle fluorescence spectroscopy to identify and quantify PBAP at an Arctic mountain site, with transmission electronic microscopy analysis supporting the presence of PBAP. We find that PBAP concentrations range between 10−3–10−1 L−1 and peak in summer. Evidences suggest that the terrestrial Arctic biosphere is an important regional source of PBAP, given the high correlation to air temperature, surface albedo, surface vegetation and PBAP tracers. PBAP clearly correlate with high-temperature ice nucleating particles (INP) (>-15 °C), of which a high a fraction (>90%) are proteinaceous in summer, implying biological origin. These findings will contribute to an improved understanding of sources and characteristics of Arctic PBAP and their links to INP. Primary bioaerosols, important for clouds and climate, were measured at an Arctic mountain site and traced to regional sources. Their seasonality was observed to peak in summer, where they significantly contribute to high-temperature ice nucleating particles. [ABSTRACT FROM AUTHOR]

The Tibet Plateau (TP) and the Arctic are typically cold regions with abundant snow cover, which plays a key role in land surface processes. Knowledge of variations in snow density is essential for understanding hydrology, ecology, and snow cover feedback. Here, we utilized extensive measurements recorded by 697 ground-based snow sites during 1950–2019 to identify the spatio-temporal characteristics of snow density in these two regions. We examined the spatial heterogeneity of snow density for different snow classes, which are from a global seasonal snow cover classification system, with each class determined from air temperature, precipitation, and wind speed climatologies. We also investigated possible mechanisms driving observed snow density differences. The long-term mean snow density in the Arctic was 1.6 times that of the TP. Slight differences were noted in the monthly TP snow densities, with values ranging from 122 ± 29 to 158 ± 52 kg/m3. In the Arctic, however, a clear increasing trend was shown from October to June, particularly with a rate of 30.3 kg/m3 per month from March to June. For the same snow class, the average snow density in the Arctic was higher than that in the TP. The Arctic was characterized mainly by a longer snowfall duration and deeper snow cover, with some areas showing perennial snow cover. In contrast, the TP was dominated by seasonal snow cover that was shallower and warmer, with less (more) snowfall in winter (spring). The results will be helpful for future simulations of snow cover changes and land interactions at high latitudes and altitudes. [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]

Healthy Arctic marine ecosystems are essential to the food security and sovereignty, culture and wellbeing of Indigenous Peoples in the Arctic. At the same time, Arctic marine ecosystems are highly susceptible to impacts of climate change and ocean acidification. While increasing ocean and air temperatures and melting sea ice act as direct stressors on the ecosystem, they also indirectly enhance ocean acidification, accelerating the associated changes in the inorganic carbon system. Yet, much is to be learned about the current state and variability of the inorganic carbon system in remote places. Here, we present pH and p CO2 time-series (2016–2020) from the Chukchi Ecosystem Observatory. The subsurface observatory is located in the midst of a biological hotspot with high primary productivity and a rich benthic food web that support coastal Iñupiat, whales, ice seals, walrus (Odobenus rosmarus), and Arctic cod (Boreogadus saida). Our observations suggest that near-bottom waters (33 m depth, 13 m above the seafloor) are a high carbon dioxide and low pH and aragonite saturation state environment in summer and fall, when organic material from the highly productive summer remineralizes. During this time, the aragonite saturation state can be as low as 0.4, triggering free CaCO3 dissolution. During the sea ice covered winter period, pH was < 8 and aragonite remained undersaturated under the sea ice. There are only two short seasonal periods with relatively higher pH and Ωarag, which we term ocean acidification relaxation events. In spring, high primary production from sea ice algae and phytoplankton blooms and ikaite dissolution lead to spikes in pH (pH > 8) and aragonite oversaturation. In late fall, strong wind driven mixing events that bring CO2 depleted surface water to the shelf also lead to events with elevated pH and Ωarag. Given the recent observations of high rates of ocean acidification, and sudden and dramatic shift of the physical, biogeochemical, and ecosystem conditions in the Chukchi Sea, it is possible that the observed extreme conditions at the Chukchi Ecosystem Observatory are significantly deviating from the carbonate conditions to which many species are adapted and may have negative impacts on the ecosystem. [ABSTRACT FROM AUTHOR]

Three-dimensional numerical modeling is used to assess the sensitivity of the sea ice state in the Arctic deep-water basin to changing the riverine heat influx. The change in the sea ice volume due to the heat coming with river waters relative to its annual average value is analyzed. Numerical experiment results demonstrate an increase in the riverine heat contribution to the Arctic sea ice decline at the end of the second decade of the present century. This process is most manifested in the deep-water part of the Eastern Hemisphere, which is determined by immediate proximity to the largest Siberia's rivers and the system of the circulation of shelf seas and deep-water basins under conditions of increasing air temperature and sea ice reduction in the Arctic. [ABSTRACT FROM AUTHOR]

A stochastic weather generator is proposed in the paper. The model is designed for the numerical simulation of joint time series of surface air temperature, wind speed, and relative air humidity with a three-hour resolution at weather stations located in the Russian Arctic. The proposed weather generator allows taking into account the non-Gaussian form of one-dimensional distributions of meteorological parameters and the diurnal variations inherent to real series. The results of verifying the proposed model are presented, and the prospects of its further application are briefly described. [ABSTRACT FROM AUTHOR]

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

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

Warming-driven lightning frequency increases may influence the burning rate within the circumpolar Arctic and influence vegetation productivity (GPP). We considered wildfire occurrence within the different Arctic sectors (Russian, North American, and Scandinavian). We used satellite-derived (MODIS) data to document changes in the occurrence and geographic extent of wildfires and vegetation productivity. Correlation analysis was used to determine environmental variables (lightning occurrence, air temperature, precipitation, soil and terrestrial moisture content) associated with a change in wildfires. Within the Arctic, the majority (>75%) of wildfires occurred in Russia (and ca. 65% in Eastern Siberia). We found that lightning occurrence increase and moisture are primary factors that meditate the fire frequency in the Arctic. Throughout the Arctic, warming-driven lightning influences fire occurrence observed mainly in Eastern Siberia (>40% of explained variance). Similar values (ca. 40%) at the scale of Eurasia and the entire Arctic are attributed to Eastern Siberia input. Driving by increased lightning and warming, the fires' occurrence boundary is shifting northward and already reached the Arctic Ocean coast in Eastern Siberia. The boundary's extreme shifts synchronized with air temperature extremes (heat waves). Despite the increased burning rate, vegetation productivity rapidly (5–10 y) recovered to pre-fire levels within burns. Together with increasing GPP trends throughout the Arctic, that may offset fires-caused carbon release and maintain the status of the Arctic as a carbon sink. [ABSTRACT FROM AUTHOR]

Hails observed at Ny Alesund, Svalbard in the Arctic during December–February 2018–19 is examined along with the atmospheric circulation patterns. When hail was noticed, surface warming and southwesterly—westerly winds were noticed. Atmospheric circulation pattern was characterised by high pressure anomaly over northwestern Europe. High clouds as well as excess liquid water were present when the high pressure systems were active over northwestern Europe. This is because winds blowing over ocean collect more moisture as well as transport nucleating particles to Svalbard. Also, hourly winds from ERA 5 reanalysis indicated vertical shear required for hail formation. When hails were observed, mixed precipitation types were recorded with the maximum intensities arising from the hails. The West Spitzbergen Current (WSC) induces a strong east west sea surface temperature (SST) gradient in the ocean west of Svalbard. A corresponding gradient in the atmospheric temperature is also maintained by the WSC in the west to east direction in the lower atmosphere. Moisture laden westerlies cross the SST gradient and induce strong frontal activity in the lower atmosphere resulting intense precipitation and hail. The upward vertical velocity noted in the lower troposphere supports the frontal activity. Human activities in the Arctic as elsewhere are bound to increase. Hence, there is a need to study the intense precipitation in the Arctic as well as its reasons as it can impact the Arctic environment and human activity. This calls for more continuous observations to clearly identify mechanisms and frequency of intense precipitation in the Arctic. [ABSTRACT FROM AUTHOR]

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

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

Since the 1980s, rapid Arctic sea ice loss has been observed, and its potential influences on the midlatitude weather and climate have been extensively examined, but strongly debated. This study instead investigates influences of Arctic sea ice loss on the Eastern Hemisphere westerly wind on the poleward side of the polar front jet (PFJ), which has significantly weakened in winter but strengthened in summer since 1980s. Observational analyses indicate that the Eastern Hemisphere PFJ anomalies in winter and summer are strongly correlated with Northern Hemisphere (NH) atmospheric circulation, surface air temperature and precipitation changes, and that the winter PFJ variability is significantly correlated to Barents-Kara sea ice anomalies from autumn and winter at interannual time scales. About 58% of the observed winter PFJ weakened trend during 1979–2014 is congruent with the autumn sea ice index over the Barents-Kara Seas. Atmospheric model ensemble simulations from four models show that Arctic sea ice loss contributes to Arctic warming in winter and reduces the northern Eurasia-pole temperature contrast, leading to an significant weakening winter PFJ. Ensemble mean effects of four models and each model due to Arctic sea ice loss explain about 10–20% of the observed winter PFJ weakening trend, because the model simulations underestimate observed impacts of sea ice reduction on Arctic troposphere warming. In summer, the strengthening PFJ is mostly controlled by increasing greenhouse gases and sea surface temperature changes outside the Arctic, but is little affected by Arctic sea ice loss. Our observational and numerical results consistently suggest that a dynamical pathway linking observed Arctic sea ice loss to northern Eurasian winter is through its weakening effect on the westerly wind on the poleward side of the PFJ. [ABSTRACT FROM AUTHOR]

In situ meteorological data are essential to better understand ongoing environmental changes in the Arctic. Here, we present a dataset of quality-controlled meteorological observations by two automatic weather stations in northwest Greenland from July 2012 to the end of August 2020. The stations were installed in an accumulation area on the Greenland Ice Sheet (SIGMA-A site, 1490 m a.s.l.) and near the equilibrium line of the Qaanaaq Ice Cap (SIGMA-B site, 944 m a.s.l.). We describe the two-step sequence of quality-control procedures that we used to create increasingly reliable datasets by masking erroneous data records. We analyzed the resulting 2012-2020 time series of air temperature, positive degree-days, snow height, surface albedo, and histograms of longwave radiation (a proxy of cloud formation frequency). We found that snow height increased and albedo remained steady at the SIGMA-A site, whereas high air temperatures and clear-sky conditions prevailed while snow height and albedo decreased in the summers of 2015, 2019, and 2020 at the SIGMA-B site. Therefore, it appears that these weather conditions led to notable snow height degradation at the SIGMA-B site but not at the SIGMA-A site. We anticipate that this quality-control method and these datasets will aid in climate studies of northwest Greenland as well as contribute to the advancement of broader polar climate studies. [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]

The Last Interglacial (LIG) period, which had higher summer solar insolation than today, has been suggested as the last time that Arctic summers were ice free. However, the latest suite of Coupled Modelling Intercomparison Project 6 Paleoclimate (CMIP6-PMIP4) simulations of the LIG produce a wide range of Arctic summer minimum sea ice area (SIA) results, with a 30 % to 96 % reduction from the pre-industrial (PI) period. Sea ice proxies are also currently neither abundant nor consistent enough to determine the most realistic state. Here we estimate LIG minimum SIA indirectly through the use of 21 proxy records for LIG summer surface air temperature (SSAT) and 11 CMIP6-PMIP4 models for the LIG. We use two approaches. First, we use two tests to determine how skilful models are at simulating reconstructed Δ SSAT from proxy records (where Δ refers to LIG-PI). This identifies a positive correlation between model skill and the magnitude of Δ SIA: the most reliable models simulate a larger sea ice reduction. Averaging the two most skilful models yields an average SIA of 1.3×106 km 2 for the LIG. This equates to a 4.5×106 km 2 or 79 % SIA reduction from the PI to the LIG. Second, across the 11 models, the averaged Δ SSAT at the 21 proxy locations and the pan-Arctic average Δ SSAT are inversely correlated with Δ SIA (r=-0.86 and -0.79 , respectively). In other words, the models show that a larger Arctic warming is associated with a greater sea ice reduction. Using the proxy-record-averaged Δ SSAT of 4.5±1.7 K and the relationship between Δ SSAT and Δ SIA suggests an estimated sea ice reduction of 4.2±1.4×106 km 2 or about 74 % less sea ice than the PI period. The mean proxy-location Δ SSAT is well correlated with the Arctic-wide Δ SSAT north of 60 ∘ N (r=0.97), and this relationship is used to show that the mean proxy record Δ SSAT is equivalent to an Arctic-wide warming of 3.7±1.5 K at the LIG compared to the PI period. Applying this Arctic-wide Δ SSAT and its modelled relationship to Δ SIA, results in a similar estimate of LIG sea ice reduction of 4.1±1.2×106 km 2. These LIG climatological minimum SIA of 1.3 to 1.5 ×106 km 2 are close to the definition of a summer ice-free Arctic, which is a maximum sea ice extent of less than 1 ×106 km 2. The results of this study thus suggest that the Arctic likely experienced a mixture of ice-free and near-ice-free summers during the LIG. [ABSTRACT FROM AUTHOR]

In recent decades, the interior regions of Eurasia and North America have experienced several unprecedentedly cold winters despite the global surface air temperature increases. One possible explanation of these increasing extreme cold winters comes from the so-called Warm Arctic Cold Continent (WACC) pattern, reflecting the effects of the amplified Arctic warming in driving the circulation change over surrounding continents. This study analyzed reanalysis data and model experiments forced by different levels of anthropogenic forcing. It is found that WACC exists on synoptic scales in observations, model's historical and even future runs. In the future, the analysis suggests a continued presence of WACC but with a slightly weakened cold extreme due to the overall warming. Warm Arctic events under the warmer climate will be associated with not only a colder continent in East Asia but also a warmer continent, depending on the teleconnection process that is also complicated by the warmer Arctic. Such an increasingly association suggests a reduction in potential predictability of the midlatitude winter anomalies. [ABSTRACT FROM AUTHOR]

In this study, a new technique is proposed to retrieve temperature and relative humidity profiles under clear sky conditions in the Arctic region based on the artificial neural network (ANN) algorithm using Fengyun-3D (FY-3D) vertical atmospheric sounder suit (VASS: HIRAS, MWTS-II, and MWHS-II) observations. This technology combines infrared (IR) and microwave (MW) observations to improve retrieval accuracy in the middle and low troposphere by reducing the sensitivity of the neural networks (NNs) to cloud coverage. The approach was compared against other methods available in the literature on retrieving profiles only from FY-3D/HIRAS data. Furthermore, its retrieval performance was tested by comparing the NNs' prediction accuracy versus the corresponding FY-3D/VASS and Aqua/AIRS L2 products. The results showed that: (1) NNs retrieval accuracy is higher during the warm season and over the ocean; (2) the retrieval accuracy of NNs has been significantly improved compared with satellite L2 products; (3) referring to radiosonde observations, the retrieval accuracy of NNs below 600 hPa is effectively improved by adding the information of the MW channel, especially on land where cloud clearing is more difficult. The root mean square error (RMSE) of temperature and relative humidity in the cold season were reduced by 0.3 K and 2%, respectively. The advanced NNs proposed herein offer a more stable retrieval performance compared with NNs built only by FY-3D/HIRAS data. The study results indicated the potential value in time and space domain of the NN algorithm in retrieving temperature and relative humidity profiles of the Arctic region from FY-3D/VASS observations under clear-sky conditions. All in all, this work enhances our knowledge towards improving operational use of FY-3D satellite data in the Arctic region. [ABSTRACT FROM AUTHOR]

A precise Arctic surface air temperature (SAT) dataset, that is regularly updated, has more complete spatial and temporal coverage, and is based on instrumental observations, is critically important for timely monitoring and improving understanding of the rapid change in the Arctic climate. In this study, a new monthly gridded Arctic SAT dataset dated back to 1979 was reconstructed with a deep learning method by combining surface air temperatures from multiple data sources. The source data include the observations from land station of GHCN (Global Historical Climatology Network), ICOADS (International Comprehensive Ocean-Atmosphere Data Set) over the oceans, drifting ice station of Russian NP (North Pole), and buoys of IABP (International Arctic Buoy Programme). The last two are crucial for improving the representation of the in-situ observed temperatures within the Arctic. The newly reconstructed dataset includes monthly Arctic SAT beginning in 1979 and daily Arctic SAT beginning in 2011. This dataset would represent a new improvement in developing observational temperature datasets and can be used for a variety of applications. [ABSTRACT FROM AUTHOR]

High-latitude low clouds in the Northern winter have been known to be closely related to the Arctic surface air temperature by controlling downward longwave radiation, but Earth system models often fail to accurately simulate this relationship. In this study, we conducted a series of model experiments to examine the role of winter high-latitude low-level clouds in determining the Arctic surface temperature. Our findings show that low-level clouds play a significant role in regulating the Arctic surface temperature. We used the NCAR CAM6 model and compared the results of an unforced simulation run with those of an experiment using an empirical low-level cloud scheme to alleviate the typical overestimation of the low cloud fraction of state-of-the-art general circulation models at high latitudes. The unforced simulation exhibited excessive downward longwave radiation in the Arctic, resulting in a significant warm bias compared to reanalysis data. On the other hand, the experiment using a modified scheme more closely resembled the reanalysis data in terms of low-level cloud simulation. Overall, our study underscores the importance of accurately representing low-level clouds in high-latitude regions to reduce surface temperature bias in the model. [ABSTRACT FROM AUTHOR]

The extensive global climate observing system (GCOS) reference upper-air network (GRUAN) datasets provide a chance to validate newly released Atmospheric Infrared Sounder (AIRS) version 7 (v7) products over the Arctic. This manuscript reports on the analysis performed to evaluate errors from AIRS version 6 (v6) and v7 temperature profiles and to characterize the derived low-level temperature inversion (LLI) representativeness in the Arctic region. The AIRS averaging kernel, representing the AIRS measurement sensitivity, is applied to reduce the vertical resolution of the radiosonde profiles for comparison. Due to improved retrieval algorithms, v7 produces smaller biases in the troposphere and suppresses the cold bias in v6. Nevertheless, the profile-averaged root mean square error (RMSE) increased by over 30% in v7, particularly in the winter half-year when v7 showed a larger RMSE below 800 hPa. The AIRS temperature retrieval accuracy is primarily sensitive to surface type and cloud fraction. Compared to v6, v7 has less bias over frozen land and sea ice in different cloud fraction conditions. However, the RMSEs of v7 are more sensitive to the effective cloud fraction (ECF) and are highly influenced by a more significant contribution from nonfrozen land samples. Compared to the kernel-averaged radiosonde profiles, more than 80% of the temperature profiles from v6 and v7 accurately detect LLIs. The discreteness of the AIRS's predefined pressure level results is consistent with the radiosondes only 65% of the time for LLI depth calculation. In contrast, the AIRS can obtain LLI intensity with a relatively high correlation (>0.9). With the AIRS temperature retrieval in the boundary layer further improved, it has the potential to be used as an independent LLI detector in the Arctic region. [ABSTRACT FROM AUTHOR]