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Global climate models account for sea ice thickness by summing thermodynamic processes that affect thickness through phase change and dynamic processes that affect thicknesses through relative motion. Comparison of these individual processes with observations is essential for model interpretation and development. We utilized observational estimates of basal thermodynamic growth, overall thickness changes and their residual difference (including dynamics) to evaluate these processes in the National Center for Atmospheric Research (NCAR) Community Earth System Model 2 (CESM2) submission to the World Climate Research Program (WCRP) Ocean Model Comparison Project Phase 2 (OMIP2) and Pan‐Arctic Ice–Ocean Modeling and Assimilation System (PIOMAS). Both models exhibit a similar pattern of higher basal thermodynamic growth and lower residual effects and wintertime thickness in the central Arctic than observational estimates for 2010–2018, and vice versa in the peripheral seas. Correcting residual effect biases would ameliorate the biases in both mean thickness and basal thermodynamic growth. Plain Language Summary: Sea ice models include two types of processes. Those causing phase change, called thermodynamic processes and those causing thickness changes through relative motion of ice parcels, called dynamic processes. We compare the effects of these processes in two models to observational estimates to aid the interpretation of ice thickness in these models and drive development. We find that the biases in the dynamic effects drive biases in mean thickness and thermodynamic processes, which could in turn be reduced if dynamic components biases were to be improved. Key Points: Sea ice models exhibit higher (lower) basal thermodynamic growth in the central Arctic (peripheral seas) compared to observational estimatesWhen summed, all other sea ice model effects are lower (higher) in the central Arctic (peripheral seas) compared to observational estimatesAdjustment of dynamic effects closer to observational estimates would correct biases in mean thickness and basal thermodynamic growth [ABSTRACT FROM AUTHOR]

The MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition was the largest Arctic field campaign ever conducted. MOSAiC offered the unique opportunity to monitor and characterize aerosols and clouds with high vertical resolution up to 30 km height at latitudes from 80 to 90 ∘ N over an entire year (October 2019 to September 2020). Without a clear knowledge of the complex aerosol layering, vertical structures, and dominant aerosol types and their impact on cloud formation, a full understanding of the meteorological processes in the Arctic, and thus advanced climate change research, is impossible. Widespread ground-based in situ observations in the Arctic are insufficient to provide these required aerosol and cloud data. In this article, a summary of our MOSAiC observations of tropospheric aerosol profiles with a state-of-the-art multiwavelength polarization Raman lidar aboard the icebreaker Polarstern is presented. Particle optical properties, i.e., light-extinction profiles and aerosol optical thickness (AOT), and estimates of cloud-relevant aerosol properties such as the number concentration of cloud condensation nuclei (CCN) and ice-nucleating particles (INPs) are discussed, separately for the lowest part of the troposphere (atmospheric boundary layer, ABL), within the lower free troposphere (around 2000 m height), and at the cirrus level close to the tropopause. In situ observations of the particle number concentration and INPs aboard Polarstern are included in the study. A strong decrease in the aerosol amount with height in winter and moderate vertical variations in summer were observed in terms of the particle extinction coefficient. The 532 nm light-extinction values dropped from >50 Mm -1 close to the surface to <5 Mm -1 at 4–6 km height in the winter months. Lofted, aged wildfire smoke layers caused a re-increase in the aerosol concentration towards the tropopause. In summer (June to August 2020), much lower particle extinction coefficients, frequently as low as 1–5 Mm -1 , were observed in the ABL. Aerosol removal, controlled by in-cloud and below-cloud scavenging processes (widely suppressed in winter and very efficient in summer) in the lowermost 1–2 km of the atmosphere, seems to be the main reason for the strong differences between winter and summer aerosol conditions. A complete annual cycle of the AOT in the central Arctic could be measured. This is a valuable addition to the summertime observations with the sun photometers of the Arctic Aerosol Robotic Network (AERONET). In line with the pronounced annual cycle in the aerosol optical properties, typical CCN number concentrations (0.2 % supersaturation level) ranged from 50–500 cm -3 in winter to 10–100 cm -3 in summer in the ABL. In the lower free troposphere (at 2000 m), however, the CCN level was roughly constant throughout the year, with values mostly from 30 to 100 cm -3. A strong contrast between winter and summer was also given in terms of ABL INPs which control ice production in low-level clouds. While soil dust (from surrounding continents) is probably the main INP type during the autumn, winter, and spring months, local sea spray aerosol (with a biogenic aerosol component) seems to dominate the ice nucleation in the ABL during the summer months (June–August). The strong winter vs. summer contrast in the INP number concentration by roughly 2–3 orders of magnitude in the lower troposphere is, however, mainly caused by the strong cloud temperature contrast. A unique event of the MOSAiC expedition was the occurrence of a long-lasting wildfire smoke layer in the upper troposphere and lower stratosphere. Our observations suggest that the smoke particles frequently triggered cirrus formation close to the tropopause from October 2019 to May 2020. [ABSTRACT FROM AUTHOR]

Estimating long-term trends and short-term amplitudes requires reliable temperature (Temp) observations in the pre-industrial period when few in situ observations existed in the Arctic. Tree-ring materials are most available and used to reconstruct past Arctic Temp variations. However, most previous studies incorporated materials that are insensitive to local Temp variabilities. The derived reconstruction qualities are low (indicated by low calibration R2), and the uncertainties inherent in the various detrending methodologies are unknown. To reconstruct Arctic (N60°–N90°) summer (June–August) Temp in 1850–1900 and variations over the past centuries, we screened 1116 tree-ring width and tree-ring density records and applied four detrending functions (sf-RCS, RCS, MOD, and spline). In total, 338–396 records show significant correlations (p < 0.05) with the Climate Research Unit (CRU) Temp of the corresponding grid point. These records were selected and combined into a proxy record. The achieved Arctic summer Temp reconstruction explained 45–57% of the instrumental summer Temp variance since 1950. The 2012–2021 summer Arctic warming amplitudes (1.42–1.74 °C) estimated by Temp anomaly datasets extending back to 1850 are within the range derived from our reconstructions, despite using various detrending methods. These findings could suggest the Berkeley and HadCRU5 datasets interpolating Temp from a few (6–73) meteorological stations could still represent the mean Arctic Temp variation in 1850–1900, and the updated reconstruction can be used as a reliable reference for 1550–2007 Arctic summer Temp history. [ABSTRACT FROM AUTHOR]

Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project was established in 2016 (www.ac3-tr.de/). It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, shipborne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data. For example, a distinct atmospheric moistening, an increase of regional storm activities, an amplified winter warming in the Svalbard and North Pole regions, and a decrease of sea ice thickness in the Fram Strait and of snow depth on sea ice have been identified. A positive trend of tropospheric bromine monoxide (BrO) column densities during polar spring was verified. Local marine/biogenic sources for cloud condensation nuclei and ice nucleating particles were found. Atmospheric–ocean and radiative transfer models were advanced by applying new parameterizations of surface albedo, cloud droplet activation, convective plumes and related processes over leads, and turbulent transfer coefficients for stable surface layers. Four modes of the surface radiative energy budget were explored and reproduced by simulations. To advance the future synthesis of the results, cross-cutting activities are being developed aiming to answer key questions in four focus areas: lapse rate feedback, surface processes, Arctic mixed-phase clouds, and airmass transport and transformation. [ABSTRACT FROM AUTHOR]

The radiation budget in polar regions plays an important role in global climate change study. This study investigates the performance of downward longwave radiation (DLR) of three satellite radiation products in polar regions, including GEWEX-SRB, ISCCP-FD, and CERES-SYN. The RMSEs are 35.8, 40.5, and 26.9 W/m2 at all polar sites for GEWEX-SRB, ISCCP-FD, and CERES-SYN. The results in the Arctic are much better than those in the Antarctic, RMSEs of the three products are 34.7 W/m2, 36.0 W/m2, and 26.2 W/m2 in the Arctic and are 38.8 W/m2 and 54.8 W/m2, and 28.6 W/m2 in the Antarctic. Both GEWEX-SRB and CERES-SYN underestimate DLRs at most sites, while ISCCP-FD overestimates DLRs at most sites. CERES-SYN and GEWEX-SRB DLR products can capture most of the DLR seasonal variation in both the Antarctic and Arctic. Though CERES-SYN has the best results that RMSE within 30 W/m2 in most polar sites, the accuracy of satellite products in polar regions still cannot meet the requirement of climate research. The improvement of satellite DLR products in polar regions mainly depends on the quality of improving input atmospheric parameters, the accuracy of improving cloud detection over the snow and ice surface and cloud parameters, and better consideration of spatial resolution and heterogeneity. [ABSTRACT FROM AUTHOR]

The indirect effect of winter Arctic Oscillation (AO) events on the following summer Arctic sea ice extent suggests an inherent winter-to-summer mechanism for sea ice predictability. On the other hand, operational regional summer sea ice forecasts in a large number of coupled climate models show a considerable drop in predictive skill for forecasts initialised prior to the date of melt onset in spring, suggesting that some drivers of sea ice variability on longer timescales may not be well represented in these models. To this end, we introduce an unsupervised learning approach based on cluster analysis and complex networks to establish how well the latest generation of coupled climate models participating in phase 6 of the World Climate Research Programme Coupled Model Intercomparison Project (CMIP6) are able to reflect the spatio-temporal patterns of variability in Northern Hemisphere winter sea-level pressure and Arctic summer sea ice concentration over the period 1979–2020, relative to ERA5 atmospheric reanalysis and satellite-derived sea ice observations, respectively. Two specific global metrics are introduced as ways to compare patterns of variability between models and observations/reanalysis: the adjusted Rand index – a method for comparing spatial patterns of variability – and a network distance metric – a method for comparing the degree of connectivity between two geographic regions. We find that CMIP6 models generally reflect the spatial pattern of variability in the AO relatively well, although they overestimate the magnitude of sea-level pressure variability over the north-western Pacific Ocean and underestimate the variability over northern Africa and southern Europe. They also underestimate the importance of regions such as the Beaufort, East Siberian, and Laptev seas in explaining pan-Arctic summer sea ice area variability, which we hypothesise is due to regional biases in sea ice thickness. Finally, observations show that historically, winter AO events (negatively) covary strongly with summer sea ice concentration in the eastern Pacific sector of the Arctic, although now under a thinning ice regime, both the eastern and western Pacific sectors exhibit similar behaviour. CMIP6 models however do not show this transition on average, which may hinder their ability to make skilful seasonal to inter-annual predictions of summer sea ice. [ABSTRACT FROM AUTHOR]

This article addresses the broader question of the special issue by reflecting on the coloniality of knowledge production in a context of global climate governance. Drawing on the rationale of the special issue, we highlight key dynamics in which knowledge shape climate policies and propose a decolonial approach at the nexus of academic knowledge production and policy formation by accounting for diverse ways of knowing climate justice. To this end, the article asks how to develop a decolonial approach to researching climate justice in order to identify the meaning-in-use of climate justice by affected people in what we describe as sensitive regions of the Arctic and the Mediterranean. To this end, the article develops a research design that accounts for diverse ways of knowing. The article proceeds as follows: first, we will discuss how diverse ways of knowing are related to global climate governance and climate justice; second, we outline our practice-based research framework that addresses research ethics, decolonial approaches and norm contestation; and third, we discuss how our approach can inform not only the co-production of research in climate governance, but also current debates on climate justice. [ABSTRACT FROM AUTHOR]

Improving the quality of weather forecasts and the reliability of climate research requires increasing the reliability of measurements. This paper presents results for optical sensors attached to radiosondes. These sensors can measure cloud-top height (CTH) with high accuracy and determine the presence of precipitation particles in clouds and the height of the boundary between the tropospheric and stratospheric air masses. These research findings are especially important in the Arctic, where the reliability of cloud data is poor, especially during polar nights. With the help of a visible range optical sensor, during the daytime, it is possible to measure CTH with an accuracy of 50 m. Using data from an IR sensor it is possible to measure CTH both day and night. The paper also discusses the possibility of using optical sensors in an observational network. The results from this study could be useful for both weather forecasting and climate research. Significance Statement: Remote satellite methods allow us to get information quickly from all over Earth. One of the important variables is the presence of clouds and the cloud-top height because they determines the flow of solar energy to Earth's surface. We suggest equipping a standard radiosonde with an optical sensor to detect cloud cover and measure cloud-top height. In addition, the optical sensor allows us to measure the height of the boundary between the troposphere and the stratosphere. [ABSTRACT FROM AUTHOR]

Sea levels of different atmosphere–ocean general circulation models (AOGCMs) respond to climate change forcing in different ways, representing a crucial uncertainty in climate change research. We isolate the role of the ocean dynamics in setting the spatial pattern of dynamic sea-level (ζ) change by forcing several AOGCMs with prescribed identical heat, momentum (wind) and freshwater flux perturbations. This method produces a ζ projection spread comparable in magnitude to the spread that results from greenhouse gas forcing, indicating that the differences in ocean model formulation are the cause, rather than diversity in surface flux change. The heat flux change drives most of the global pattern of ζ change, while the momentum and water flux changes cause locally confined features. North Atlantic heat uptake causes large temperature and salinity driven density changes, altering local ocean transport and ζ. The spread between AOGCMs here is caused largely by differences in their regional transport adjustment, which redistributes heat that was already in the ocean prior to perturbation. The geographic details of the ζ change in the North Atlantic are diverse across models, but the underlying dynamic change is similar. In contrast, the heat absorbed by the Southern Ocean does not strongly alter the vertically coherent circulation. The Arctic ζ change is dissimilar across models, owing to differences in passive heat uptake and circulation change. Only the Arctic is strongly affected by nonlinear interactions between the three air-sea flux changes, and these are model specific. [ABSTRACT FROM AUTHOR]

This ethnographic study at the US National Snow and Ice Data Center (NSIDC) follows a group of scientists and communications specialists as they compose visualizations and analyses of near-real-time Arctic sea ice data. Research participants collectively make scientific judgments about near-real-time data in a highly visible public venue with 'relational agility'. They balance multiple phenomena including knowledge of how sceptics attack climate science, reflexivity about the conventions through which sea ice data is gathered, the needs of journalists working in a news cycle paced by Twitter, and the liveliness and vitality of sea ice itself. Relational agility, understood as a way of coordinating the social in relation to this plurality of contingent practices and processes, provides insight into the science and politics of nonlinear climate change. [ABSTRACT FROM AUTHOR]

In this study, we compared four net radiation products: the fifth generation of European Centre for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate (ERA5), National Centers for Environmental Prediction (NCEP), Clouds and the Earth's Radiant Energy System Energy Balanced and Filled (EBAF), and Global Energy and Water Exchanges (GEWEX), based on ground observation data and intercomparison data. ERA5 showed the highest accuracy, followed by EBAF, GEWEX, and NCEP. When analyzing the validation grid, ERA5 showed the most similar data distribution to ground observation data. Different characteristics were observed between the reanalysis data and satellite data. In the case of satellite-based data, the net radiation value tended to increase at high latitudes. Compared with the reanalysis data, Greenland and the central Arctic appeared to be overestimated. All data were highly correlated, with a difference of 6–21 W/m2 among the products examined in this study. Error was attributed mainly to difficulties in predicting long-term climate change and having to combine net radiation data from several sources. This study highlights criteria that may be helpful in selecting data for future climate research models of this region. [ABSTRACT FROM AUTHOR]

The Lofoten Basin in the eastern Nordic Seas plays a central role in modifying the warm Atlantic Water inflow toward the Arctic Ocean. Here, the Atlantic Water experiences increased residence times, cooling, and substantial transformation. In this study, we investigate the Atlantic Water inflow pathways to the Lofoten Basin and their vertical and seasonal variations using 2‐D and 3‐D Lagrangian simulations forced by a high‐resolution ocean model. Atlantic Water enters the basin from all directions, but we find two main inflow pathways at all vertical levels, one close to the Lofoten Escarpment in the southeast, associated with the Slope Current, and another close to the Helgeland Ridge in the southwest, associated with the Front Current. The surface inflow exhibits a stronger seasonal forcing than the inflow at depth as well as a stronger heat loss that is dominated by water masses entering the basin from the south. At deeper levels, the warm inflow from the east cools, while the relatively colder inflow from the west warms. The 2‐D and 3‐D synthetic trajectories show similar pathways. However, they are affected differently by the seasonal signal, giving different heat exchange patterns. Our results have implications for how results from Lagrangian observations in the region should be interpreted. Plain Language Summary: The Lofoten Basin in the Nordic Seas is of fundamental importance for the modification of the warm northward flowing Atlantic Water. Much of the ocean heat is lost to the atmosphere in this region. This is maintained by warm water inflows from regions around. Here, we study these inflows, their vertical structure, seasonal variability, and contribution to the heat budget in the basin. We apply an ocean model to advect purposefully released particles in the Nordic Seas seeded at 15‐, 200‐, and 500‐m depth and study their pathways and fates. We analyze both a horizontal 2‐D (particles are fixed at depth) and a full 3‐D (particles can move in the vertical) simulation and compare the two. We find that the water masses mainly enter the Lofoten Basin in two regions, one in the southeast and one in the southwest. However, the vertical structure reveals that water that is cooled enter the basin via different routes at the surface than at deeper levels. The seasonal variations are also larger at surface than at depth. The 2‐D and 3‐D simulations show overall similar patterns, but the 3‐D simulation reveals larger seasonal variations than the 2‐D simulation. Key Points: The Atlantic Water inflow to the Lofoten Basin is concentrated in two main regions, the Lofoten Slope Inflow and the Helgeland InflowThree‐dimensional Lagrangian simulations are crucial to detect seasonal variations in the vertical structure and temperature changes of the inflowsWater masses that are cooled in the Lofoten Basin mainly enter from the south at the surface and from the continental slope at depth [ABSTRACT FROM AUTHOR]

As poster child for the climate crisis and symbol of the circumpolar North, the polar bear has received considerable public and scholarly attention in recent years. A review of academic research on polar bear politics shows that many texts share a positive frame of polar bear conservation as a successful example of Arctic science diplomacy. Despite making such substantive claims, authors fail by and large to explain their reasoning or provide evidence of this success, aside from references to the 1973 Agreement on the Conservation of Polar Bears. This article hence evaluates the claim that polar bear conservation constitutes a successful case of Arctic science diplomacy. To do so, the paper establishes a set of success criteria for Arctic science diplomacy. Based on an analysis of policy, governmental, and scientific documents and interviews on polar bear management and conservation, the paper identifies two periods of polar bear science diplomacy, evaluating each based on the success criteria developed in this paper. The first period (1960–90s) is defined by traditional threats to polar bears that are addressed through successful Arctic science diplomacy. Though the second period (1990s-present) also features elements of successful science diplomacy, Arctic scientists and diplomats are unable to effectively address the now dominant threat of climate change, shifting authority away from the Arctic and towards the international realm of climate change research and politics. As the climate crisis continues to outrank and amplify traditional threats to ecosystems around the globe, the article argues that this shift in epistemic and diplomatic authority may be indicative of a fate awaiting other specialized science diplomacy communities worldwide. [Display omitted] [ABSTRACT FROM AUTHOR]

The article describes the Arctic Observation and Reanalysis Integrated System (ArORIS), which combines various state-of-the-art satellite, reanalysis, and in situ datasets from peer-reviewed products. It provides an overview of the ArORIS dataset. It also demonstrates a few applications that indicate the value of ArORIS for validation, science, and assessment studies of the surface energy budget in the changing Arctic climate

Over the past decade, the diminishing Arctic sea ice has impacted the wave field which is principally dependent on the ice-free area and wind. This study characterizes the wave climate in the Arctic using detailed sea state information from a wave hindcast and merged altimeter dataset spanning 1992-2014. The wave model uses winds from the Climate Forecast System Reanalysis and ice concentrations derived from satellites as input. The ice concentrations have a grid spacing of 12.5 km, which is sufficiently able to resolve important features in the marginal ice zone. The model performs well, verified by the altimeters and is relatively consistent for climate studies. The wave seasonality and extremes are linked to the ice coverage, wind strength, and wind direction. This creates distinct features in the wind-seas and swells. The increase in wave heights is caused by the loss of sea ice and not the wind verified by the altimeters and model. However, trends are convoluted by inter-annual climate oscillations like the North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation. The Nordic-Greenland Sea is the only region with negative trends in wind speed and wave height and is related to the NAO. Swells are becoming more prevalent and wind-sea steepness is declining which make the impact on sea ice uncertain. It is inconclusive how important wave-ice processes are within the climate system, but selected events suggest the importance of waves within the marginal ice zone. [ABSTRACT FROM AUTHOR]

Permafrost-related processes drive regional landscape dynamics in the Arctic terrestrial system. A better understanding of past periods indicative of permafrost degradation and aggradation is important for predicting the future response of Arctic landscapes to climate change. Here, we used a multi-proxy approach to analyse a ~ 4 m long sediment core from a drained thermokarst lake basin on the northern Seward Peninsula in western Arctic Alaska (USA). Sedimentological, biogeochemical, geochronological, micropalaeontological (ostracoda, testate amoebae) and tephra analyses were used to determine the long-term environmental Early-Wisconsin to Holocene history preserved in our core for central Beringia. Yedoma accumulation dominated throughout the Early to Late-Wisconsin but was interrupted by wetland formation from 44.5 to 41.5 ka BP. The latter was terminated by the deposition of 1 m of volcanic tephra, most likely originating from the South Killeak Maar eruption at about 42 ka BP. Yedoma deposition continued until 22.5 ka BP and was followed by a depositional hiatus in the sediment core between 22.5 and 0.23 ka BP. We interpret this hiatus as due to intense thermokarst activity in the areas surrounding the site, which served as a sediment source during the Late-Wisconsin to Holocene climate transition. The lake forming the modern basin on the upland initiated around 0.23 ka BP and drained catastrophically in spring 2005. The present study emphasises that Arctic lake systems and periglacial landscapes are highly dynamic and that permafrost formation as well as degradation in central Beringia was controlled by regional to global climate patterns as well as by local disturbances. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This article seeks to analyze the parallels and transformations between Arctic visual narratives in America during the Cold War of the 1950s and those in the era of climate change in the twenty-first century. The work will explore how the American narrative of the Arctic has retooled Cold War aesthetic codes for the challenges of climate change. The research will focus on case studies of Arctic photography and videography in two discrete 15-year periods, from 1945–1960 and 2000–2015 for the Cold War and climate change, respectively. Through these comparative snapshots or samples, it will contend that two major, persistent themes – the Arctic as a distant early warning system and Arctic inhabitants as important holders of local knowledge – have been borrowed and refitted from America's Cold War polar visualization to inform climate narratives today. [ABSTRACT FROM PUBLISHER]

The surface warming in recent decades has been most rapid in the Arctic, especially during the winter. Here, by utilizing global reanalysis and satellite datasets, it is shown that the northward flux of moisture into the Arctic during the winter strengthens the downward infrared radiation (IR) by 30-40 W m−2 over 1-2 weeks. This is followed by a decline of up to 10% in sea ice concentration over the Greenland, Barents, and Kara Seas. A climate model simulation indicates that the wind-induced sea ice drift leads the decline of sea ice thickness during the early stage of the strong downward IR events, but that within one week the cumulative downward IR effect appears to be dominant. Further analysis indicates that strong downward IR events are preceded several days earlier by enhanced convection over the tropical Indian and western Pacific Oceans. This finding suggests that sea ice predictions can benefit from an improved understanding of tropical convection and ensuing planetary wave dynamics. [ABSTRACT FROM AUTHOR]

Understanding recent Arctic climate change requires detailed information on past changes, in particular on a regional scale. The extension of the depth-age relation of the Akademii Nauk (AN) ice core from Severnaya Zemlya (SZ) to the last 1100 yr provides new perspectives on past climate fluctuations in the Barents and Kara seas region. Here, we present the easternmost high-resolution ice-core climate proxy records (d18O and sodium) from the Arctic. Multiannual AN d18O data as near-surface air-temperature proxies reveal major temperature changes over the last millennium, including the absolute minimum around 1800 and the unprecedented warming to a double-peak maximum in the early 20th century. The long-term cooling trend in d18O is related to a decline in summer insolation but also to the growth of the AN ice cap as indicated by decreasing sodium concentrations. Neither a pronounced Medieval Climate Anomaly nor a Little Ice Age are detectable in the AN d18O record. In contrast, there is evidence of several abrupt warming and cooling events, such as in the 15th and 16th centuries, partly accompanied by corresponding changes in sodium concentrations. These abrupt changes are assumed to be related to sea-ice cover variability in the Barents and Kara seas region, which might be caused by shifts in atmospheric circulation patterns. Our results indicate a significant impact of internal climate variability on Arctic climate change in the last millennium. [ABSTRACT FROM AUTHOR]

The perennial ice area was drastically reduced to 38%% of its climatological average in 2007 but recovered slightly in 2008, 2009, and 2010 with the areas being 10%%, 24%%, and 11%% higher than in 2007, respectively. However, trends in extent and area remained strongly negative at −12.2%% and −13.5%% decade−1, respectively. The thick component of the perennial ice, called multiyear ice, as detected by satellite data during the winters of 1979-2011 was studied, and results reveal that the multiyear ice extent and area are declining at an even more rapid rate of −15.1%% and −17.2%% decade−1, respectively, with a record low value in 2008 followed by higher values in 2009, 2010, and 2011. Such a high rate in the decline of the thick component of the Arctic ice cover means a reduction in the average ice thickness and an even more vulnerable perennial ice cover. The decline of the multiyear ice area from 2007 to 2008 was not as strong as that of the perennial ice area from 2006 to 2007, suggesting a strong role of second-year ice melt in the latter. The sea ice cover is shown to be strongly correlated with surface temperature, which is increasing at about 3 times the global average in the Arctic but appears weakly correlated with the Arctic Oscillation (AO), which controls the atmospheric circulation in the region. An 8-9-yr cycle is apparent in the multiyear ice record, which could explain, in part, the slight recovery in the last 3 yr. [ABSTRACT FROM AUTHOR]

Land water and snow mass anomalies versus time were computed from the inversion of 50 Gravity Recovery and Climate Experiment (GRACE) geoids (August 2002 to February 2007) from the RL04 GeoForschungZentrum (GFZ) release and used to characterize the hydrology of the Arctic drainage system. GRACE-based time series have been compared to snow water equivalent and snow depth climatologies, and snowfall for validation purpose. Time series of regional averages of water volume were estimated for the 11 largest Peri-Arctic basins. Strong correlations were found between the snow estimates and river discharges in the Arctic basins (0.49-0.8). Then changes in land water storage were compared to precipitation minus evapotranspiration fluxes to determine which flux of the hydrological budget controls the Arctic hydrology. Results are very contrasted according to the basin. Trends of snow and land water masses were also computed over the 2003-2006 period. Eurasian basins lose snow mass whereas North American basins are gaining mass. [ABSTRACT FROM AUTHOR]

The article presents a study which examined the thermal conditions in the Arctic from 1801 to 1920. Collection of data from various land and marine expeditions was preformed, as well as gathering of 118 temperature series. Results indicate that the study period was cold, although the average yearly temperature was only around 0.8°C lower than the 1961-1990 value. The study concludes that it is possible to improve the knowledge on Arctic climate in the 19th and the start of 20th centuries.

Abstract: Arctic temperature is analyzed in view of its extremes based on climate indices derived from daily mean, maximum, and minimum temperature. This analysis is done for the pan Arctic domain and region-specific for the eastern and western Russian Arctic. The variability of temperature-related indices over the last four decades is presented, in which the spatial distribution and regional differences as well as its temporal trends are discussed. The analysis is based on ERA40 data and station data in the Russian Arctic. Station-based results for 1958–2008 show a significant decrease of frost days (−0.8days/decade) over the eastern Russian Arctic in spring. The trends in warm (cold) spell days are not statistically significant; except in western Russian Arctic in summer for cold spell days (−2days/decade). The inter-annual variability of the indices is large and shows pronounced decadal variations. ERA40 data generally reproduce well the inter-annual variability in the climate indices as seen in observations, but they show some deficiencies in the magnitudes and trends of the indices. [Copyright &y& Elsevier]

Distributed glacier surface melt models are often forced using air temperature fields that are either downscaled from climate models or reanalysis, or extrapolated from station measurements. Typically, the downscaling and/or extrapolation are performed using a constant temperature lapse rate, which is often taken to be the free-air moist adiabatic lapse rate (MALR: 6°–7°C km-1). To explore the validity of this approach, the authors examined altitudinal gradients in daily mean air temperature along six transects across four glaciers in the Canadian high Arctic. The dataset includes over 58 000 daily averaged temperature measurements from 69 sensors covering the period 1988–2007. Temperature lapse rates near glacier surfaces vary on both daily and seasonal time scales, are consistently lower than the MALR (ablation season mean: 4.9°C km-1), and exhibit strong regional covariance. A significant fraction of the daily variability in lapse rates is associated with changes in free-atmospheric temperatures (higher temperatures = lower lapse rates). The temperature fields generated by downscaling point location summit elevation temperatures to the glacier surface using temporally variable lapse rates are a substantial improvement over those generated using the static MALR. These findings suggest that lower near-surface temperature lapse rates can be expected under a warming climate and that the air temperature near the glacier surface is less sensitive to changes in the temperature of the free atmosphere than is generally assumed. [ABSTRACT FROM AUTHOR]

Satellite-retrieved data of total water vapor (TWV) over the Arctic are patchy, with large areas of missing data because of various limitations of the retrieval algorithms. To overcome these observational difficulties, a new retrieval algorithm has been developed that allows for monitoring the TWV over the Arctic during most of the year. This method retrieves TWV from satellite microwave radiometer data [the Advanced Microwave Sounding Unit B (AMSU-B)]. These new data have been made available for 4 yr (2000–03) and have been used to evaluate high-resolution simulations with the Arctic regional atmospheric climate model HIRHAM at daily, monthly, and seasonal time scales. The strong dynamic TWV variability on the daily time scale, linked with moisture transport by weather systems, is discussed for selected case studies. Both the simulated climatological seasonal mean patterns and the variability on interannual and decadal time scales are in agreement with those of the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) data. Trends in Arctic TWV for 1958–2001, broken down by season, are presented. Although an increase in the TWV is obvious in all seasons, there are also regions where a decreasing trend appears. Significant maximum positive trends are calculated over the western Arctic in summer (up to 0.06 kg m-2 yr-1), and a significant small negative trend is calculated over the East Siberian Sea in winter. [ABSTRACT FROM AUTHOR]

The article discusses the implementation of the new processing environment for Advanced Very High Resolution Radiometer (AVHRR)-based climate monitoring products by the EUMETSAT's Satellite Application Facility on Climate Monitoring (CM-SAF) in Europe and the Arctic. The utilization of NOAA-17, NOAA-18 and MetOp-A for AVRR measurements on cloud parameters includes cloud fraction and cloud phase. The study aims to monitor the processes that may affect the Arctic sea ice changes.

Surface air temperatures (SAT) from three Alaskan weather stations in a north-south section (Barrow, Nome, and St. Paul) show that on a decadal scale, the correlation among the stations changed during the past century. Before the 1960s, Barrow and Nome were dominated by Arctic air masses and St. Paul was dominated by North Pacific maritime air masses. After the 1960s, the SAT correlation in winter between Barrow and St. Paul increased from 0.2 to 0.7 and between Nome and St. Paul from 0.4 to 0.8, implying greater north-south penetration of both air masses. The correlation change in the winter of the Barrow-St. Paul pair is significant at a 95% confidence level. The Nome-St. Paul pair in spring also shows some of this characteristic change in correlation. Relatively stable, high correlations are found among the stations in the fall; correlations are low in the summer. Our study shows a change in the climatological structure of the Bering Sea in the late twentieth century, at present of unknown origin and occurring earlier than the well-known 1976/1977 shift. These climatological results further support the concept that the southeast Bering Sea ecosystem may have been dominated by Arctic species for most of the century, with a gradual replacement by sub-Arctic species in the last 30 years. Copyright © 2005 Royal Meteorological Society. [ABSTRACT FROM AUTHOR]

Hydrological models require accurate precipitation and air temperature inputs in order to adequately depict water fluxes and storages across Arctic regions. Biases such as gauge undercatch, as well as uncertainties in numerical weather prediction reanalysis data that propagate through water budget models, limit the ability to accurately model the terrestrial arctic watercycle. A hydrological model forced with three climate datasets and three methods of estimating potential evapotranspiration (PET) was used to better understand the impact of these processes on simulated water fluxes across the WesternArctic Linkage Experiment (WALE) domain. Climate data were drawn from the NCEP--NCAR reanalysis (NNR) (NCEP1), a modified version of the NNR (NCEP2), and the Willmott--Matsuura (WM) dataset. PET methods applied in the model were Hamon, Penman--Monteith, and Penman--Monteith using adjusted vapor pressure data.High vapor pressures in the NNR lead to low simulated evapotranspiration(ET) in model runs using the Penman--Monteith PET method, resulting in increased runoff. Annual ET derived from simulations using Penman--Monteith PET was half the magnitude of ET simulated when the Hamon method wasused. Adjustments made to the reanalysis vapor pressure data increased the simulated ET flux, reducing simulated runoff. Using the NCEP2 or WM climatedata, along with the Penman--Monteith PET function, results in agreement to within 7% between the simulated and observed runoff across the Yukon River basin. The results reveal the high degree of uncertainty present in climate data and the range of water fluxes generated from common model drivers. This suggests the need for thorough evaluations of model requirements and potential biases in forcing data, as well as corroborations with observed data, in all efforts to simulate arctic water balances. [ABSTRACT FROM AUTHOR]

The article provides information on Arctic and high mountain climates, and their effects on the carbohydrate content of oxyria digyna. It was noted that the Arctic and high mountains in temperate regions are the habitats with common characteristics of short growing season and a low mean temperature. However, their diurnal patterns contrast sharply. Furthermore, a comparison was made on the carbohydrate content of mature leaves of oxyria digyna in the two localities, growing at the altitude of 12,500 feet in the Karakoram-Himalaya and at sea-level on Jan Mayen in the Arctic. The result shows that the ratio of reducing sugar to total sugar and the diurnal variation range are similar with regards to the total carbohydrate content.

Polar sea ice affects atmospheric and ocean circulation and plays an important role in global climate change. Long time series sea ice concentrations (SIC) are an important parameter for climate research. This study presents an SIC retrieval algorithm based on brightness temperature (Tb) data from the FY3C Microwave Radiation Imager (MWRI) over the polar region. With the Tb data of Special Sensor Microwave Imager/Sounder (SSMIS) as a reference, monthly calibration models were established based on time–space matching and linear regression. After calibration, the correlation between the Tb of F17/SSMIS and FY3C/MWRI at different channels was improved. Then, SIC products over the Arctic and Antarctic in 2016–2019 were retrieved with the NASA team (NT) method. Atmospheric effects were reduced using two weather filters and a sea ice mask. A minimum ice concentration array used in the procedure reduced the land-to-ocean spillover effect. Compared with the SIC product of National Snow and Ice Data Center (NSIDC), the average relative difference of sea ice extent of the Arctic and Antarctic was found to be acceptable, with values of −0.27 ± 1.85 and 0.53 ± 1.50, respectively. To decrease the SIC error with fixed tie points (FTPs), the SIC was retrieved by the NT method with dynamic tie points (DTPs) based on the original Tb of FY3C/MWRI. The different SIC products were evaluated with ship observation data, synthetic aperture radar (SAR) sea ice cover products, and the Round Robin Data Package (RRDP). In comparison with the ship observation data, the SIC bias of FY3C with DTP is 4% and is much better than that of FY3C with FTP (9%). Evaluation results with SAR SIC data and closed ice data from RRDP show a similar trend between FY3C SIC with FTPs and FY3C SIC with DTPs. Using DTPs to present the Tb seasonal change of different types of sea ice improved the SIC accuracy, especially for the sea ice melting season. This study lays a foundation for the release of long time series operational SIC products with Chinese FY3 series satellites. [ABSTRACT FROM AUTHOR]

Sea ice concentration (SIC) plays a significant role in climate change research and ship's navigation in polar regions. Satellite-based SIC products have become increasingly abundant in recent years; however, the uncertainty of these products still exists and needs to be further investigated. To comprehensively evaluate the consistency of the SIC derived from different SIC algorithms in long time series and the whole polar regions, we compared four passive microwave (PM) satellite SIC products with the ERA-Interim sea ice fraction dataset during the period of 2015–2018. The PM SIC products include the SSMIS/ASI, AMSR2/BT, the Chinese FY3B/NT2, and FY3C/NT2. The results show that the remotely sensed SIC products derived from different SIC algorithms are generally in good consistency. The spatial and temporal distribution of discrepancy among satellite SIC products for both Arctic and Antarctic regions are also observed. The most noticeable difference for all the four SIC products mostly occurs in summer and at the marginal ice zone, indicating that large uncertainties exist in satellite SIC products in such period and areas. The SSMIS/ASI and AMSR2/BT show relatively better consistency with ERA-Interim in the Arctic and Antarctic, respectively, but they exhibit opposite bias (dry/wet) relative to the ERA-Interim data. The sea ice extent (SIE) and sea ice area (SIA) derived from PM and ERA-Interim SIC were also compared. It is found that the difference of PM SIE and SIA varies seasonally, which is in line with that of PM SIC, and the discrepancy between PM and ERA-Interim data is larger in Arctic than in Antarctic. We also noticed that different algorithms have different performances in different regions and periods; therefore, the hybrid of multiple algorithms is a promising way to improve the accuracy of SIC retrievals. It is expected that our findings can contribute to improving the satellite SIC algorithms and thus promote the application of these useful products in global climate change studies. [ABSTRACT FROM AUTHOR]

Under global warming due to anthropogenic increases in atmospheric carbon dioxide concentration, the surface air temperature in the Arctic is increasing with a speed that is more than double the global average, called "Arctic amplification (AA)." To grasp these changes in the Arctic, to understand the mechanism, to know the global influences, and to contribute to future climate projection, we conducted the Green Network of Excellence Program (GRENE) Arctic Climate Change Research Project "Rapid Change of the Arctic Climate System and its Global Influences" for five years between 2011 and 2016 (hereafter "GRENE Arctic"). To tackle four strategic targets presented, members from seven research themes, modeling, terrestrial ecosystem, atmosphere, cryosphere, greenhouse gases, marine ecosystem, and sea ice groups, worked together and reached to the outcomes. Here, the significant outcomes of the GRENE Arctic, presented in more than 100 research articles were compiled, reviewed, and synthesized. Among them, the notable key findings were highlighted in the final chapter. The GRENE Arctic was epoch-making as the first all-Japan comprehensive project incorporating multidisciplinary studies and collaboration between observation and modeling. The original synthetic report has been open at the GRENE home page (http://www.nipr.ac.jp/grene/). [ABSTRACT FROM AUTHOR]

The author discusses research on the implication of changes in the seasons pattern in the Arctic. He accounts the emphasis of the study on factors increasing vegetation productivity, specifically on the strong association between vegetation seasonality and temperature. They point out the significance of observational approaches in understanding climate change.

The article discusses the production of the Arctic Climate Impact Assessment publication, requested by the Arctic Council through the International Arctic Science Committee. The publication aims to provide an evaluation of the arctic climate change and its effects. It was produced by 300 scientists and published in 2004 by Cambridge University Press. The report's conclusion states that the Arctic is an extremely fragile environment that is warming faster. Scientists observed an almost 20% reduction of sea ice in the northern part.