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As the Arctic and its rivers continue to warm, a better understanding of the possible future impacts on people would benefit from close partnership with Indigenous communities and scientists from diverse fields of study. We present efforts by the Arctic Rivers Project to conduct community‐engaged research to increase collective understanding of the historical and potential future impacts of climate change on rivers, fish, and Indigenous communities. Working in central to northern Alaska and the Yukon Territory in Canada, the project seeks to engage with Indigenous communities in ethical and equitable ways to produces science that is useful, useable, and used that may serve as an example for future research efforts. Toward this goal, we formed an Indigenous Advisory Council and together developed project‐specific knowledge co‐production protocols. This paper provides a novel model of design and implementation to co‐produce knowledge with communities across a large study domain. Plain Language Summary: The Arctic and rivers located in the Arctic and subarctic are warming due to climate change. To understand the impacts this warming will have on people, partnering with impacted Indigenous communities in the region is important. It is also important that these partnerships are ethical and equitable and produce science that is actionable. This paper discusses efforts undertaken by a specific project, the Arctic Rivers Project, to conduct ethical and equitable research with Indigenous communities and generate science that is useful to those communities. Through this research our goal is to better understand potential future impacts of climate change on rivers, fish, and Indigenous communities in central northern Alaska and the Yukon Territory in Canada. To achieve this goal, the project formed an Indigenous Advisory Council (IAC) and together developed guidelines for how we can work collaboratively with Indigenous communities. Our specific process of forming an IAC and guidelines is, to our knowledge, a new way to approach collaborative research when working across a large geographic area. We present our process here so that it may provide an example for other research efforts. Key Points: Arctic climate information can be made useful, useable, and used by equitably accounting for diverse community adaptation needs through knowledge co‐productionInstitutional and community capacity, including means and ability, is necessary for equitable knowledge co‐production to occurWe present an approach for co‐producing knowledge with Indigenous communities that can serve as an example for other scientific efforts [ABSTRACT FROM AUTHOR]

This article presents the results of a bifurcation analysis of a simple energy balance model (EBM) for the future climate of the Earth. The main focus is on the following question: can the nonlinear processes intrinsic to atmospheric physics, including natural positive feedback mechanisms, cause a mathematical bifurcation of the climate state, as a consequence of continued anthropogenic forcing by rising greenhouse gas emissions? Our analysis shows that such a bifurcation could cause an abrupt change to a drastically different climate state in the EBM, which is warmer and more equable than any climate existing on Earth since the Pliocene epoch. In previous papers, with this EBM adapted to paleoclimate conditions, it was shown to exhibit saddle-node and cusp bifurcations, as well as hysteresis. The EBM was validated by the agreement of its predicted bifurcations with the abrupt climate changes that are known to have occurred in the paleoclimate record, in the Antarctic at the Eocene–Oligocene transition (EOT) and in the Arctic at the Pliocene–Paleocene transition (PPT). In this paper, the EBM is adapted to fit Anthropocene climate conditions, with emphasis on the Arctic and Antarctic climates. The four Representative Concentration Pathways (RCP) considered by the IPCC (Intergovernmental Panel on Climate Change) are used to model future CO2 concentrations, corresponding to different scenarios of anthropogenic activity. In addition, the EBM investigates four naturally occurring nonlinear feedback processes which magnify the warming that would be caused by anthropogenic CO2 emissions alone. These four feedback mechanisms are ice–albedo feedback, water vapour feedback, ocean heat transport feedback, and atmospheric heat transport feedback. The EBM predicts that a bifurcation resulting in a catastrophic climate change, to a pre-Pliocene-like climate state, will occur in coming centuries for an RCP with unabated anthropogenic forcing, amplified by these positive feedbacks. However, the EBM also predicts that appropriate reductions in carbon emissions may limit climate change to a more tolerable continuation of what is observed today. The globally averaged version of this EBM has an equilibrium climate sensitivity (ECS) of 4.34 K, near the high end of the likely range reported by the IPCC. [ABSTRACT FROM AUTHOR]

A better understanding of the interannual variability in temperature and precipitation datasets used as forcing fields for hydrologic models will lead to a more complete description of hydrologic model uncertainty, in turn helping scientists study the larger goal of how the Arctic terrestrial systemis responding to global change. Accordingly, this paper investigates temporal and spatial variability in monthly mean (1992--2000) temperature and precipitation datasets over the Western Arctic Linkage Experiment (WALE) study region. The six temperature datasets include 1) the fifth-generation Pennsylvania State University--National Center for Atmospheric Research MesoscaleModel (MM5); 2) the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40); 3) the Advanced Polar Pathfinderall-sky temperatures (APP); 4) National Centers for Environmental Prediction--National Center for Atmospheric Research (NCEP--NCAR) reanalyses (NCEP1); 5) the Climatic Research Unit/University of East Anglia CRUTEM2v (CRU); and 6) the Matsuura and Wilmott 0.5° × 0.5° Global Surface Air Temperature and Precipitation (MW). Comparisons of monthly precipitation are examined for MM5, ERA-40, NCEP1, CRU, and MW. Results of the temporal analyses indicate significant differences between at least two datasets (for either temperature or precipitation) in almost every month. The largest number of significant differences for temperature occurs in October, when there are five separate groupings; for precipitation, there are four significantly different groupings from March through June, and again in December. Spatial analyses of June temperatures indicate that the greatest dissimilarity is concentrated in the central portion of the study region, with the NCEP1 and APP datasets showing the greatest differences. In comparison, the spatial analysis of June precipitation datasets suggests that the largest dissimilarity is concentrated in the eastern portion of the study region. These results indicate that the choice of forcing datasets likely will have a significant effecton the output from hydrologic models, and several different datasets should beused for a robust hydrologic assessment. [ABSTRACT FROM AUTHOR]

This paper examines search and rescue and backcountry medical response constraints in the Canadian Arctic and potential for unmanned aerial vehicles (UAV) to aid in response and preparedness. Semi-structured interviews (n = 18) were conducted with search and rescue responders, Elders, and emergency management officials to collect data on current emergency response and potential for UAV use. UAV test flights (n = 17) were undertaken with community members. We analyzed five years of weather data to examine UAV flight suitability. Numerous challenges face Arctic search and rescue and backcountry emergency response. Changing social and environmental conditions were described as increasing vulnerability to backcountry emergencies. Responders desired additional first aid and emergency training. Legal and weather restrictions were found to limit where, when and who could fly UAVs. UAVs were demonstrated to have potential benefits for hazard monitoring but not for SAR or medical response due to legal restrictions, weather margins, and local capacity. We find that communities are ill-prepared for ongoing SAR demands, let alone a larger disaster. There are numerous limitations to the use of consumer UAVs by Arctic communities. Prevention of backcountry medical emergencies, building resilience to disasters, and first responder training should be prioritized over introducing UAVs to the response system. [ABSTRACT FROM AUTHOR]

Accurate estimates of the spatial and temporal variation in terrestrial water and energy fluxes and mean states are important for simulating regional hydrology and biogeochemistry in high-latitude regions. Furthermore, it is necessary to develop high-resolution hydroclimatological datasets at finer spatial resolutions than are currently available from global analyses. This study uses a regional climate model (RCM) to develop a hydroclimatological dataset for hydrologic and ecological application in the Western Arctic. The fifth-generation Penn State–NCAR Mesoscale Model (MM5) forced by global reanalysis products at the boundaries is used to perform 12 yr of simulation (1990 through 2001) over the Western Arctic. An analysis that compares the RCM simulations with independent observationally derived data sources is conducted to evaluate the temporal and spatial distribution of the mean states, variability, and trends during the period of simulation. The RCM simulation of sea level pressure agrees well with the reanalysis in terms of mean states, seasonality, and interannual variability. The RCM also simulates major spatial patterns of the observed climatology of surface air temperature (SAT), but RCM SAT is generally colder in the summertime and warmer in the wintertime in comparison with other datasets. Although there are biases in the mean state of SAT, the RCM simulations of the seasonal and interannual variability of SAT are similar to variability in observationally derived datasets. The RCM also simulates general spatial patterns of observed rainfall, but the modeled mean state of precipitation is characterized by large biases relative to observationally derived datasets. In particular, the RCM tends to overestimate coastal region precipitation but underestimates precipitation in the interior of the Western Arctic. The Arctic terrestrial surface climate trends for the period of 1992 to 2001 of the RCM are similar to those derived from observations, with sea level pressure decreasing 0.15 hPa decade-1, SAT increasing 0.10°C decade-1, and precipitation decreasing slightly in the RCM simulations. In summary, the RCM dataset produced in this study represents an improvement over data currently available from large-scale global reanalysis and provides a consistent meteorological forcing dataset for hydrologic and ecological applications. [ABSTRACT FROM AUTHOR]

This paper addresses the specter of a September ice-free Arctic in the 21st century using newly available simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We find that large spread in the projected timing of the September ice-free Arctic in 30 CMIP5 models is associated at least as much with different atmospheric model components as with initial conditions. Here we reduce the spread in the timing of an ice-free state using two different approaches for the 30 CMIP5 models: (i) model selection based on the ability to reproduce the observed sea ice climatology and variability since 1979 and (ii) constrained estimation based on the strong and persistent relationship between present and future sea ice conditions. Results from the two approaches show good agreement. Under a high-emission scenario both approaches project that September ice extent will drop to ~ 1.7 million km2 in the mid 2040s and reach the ice-free state (defined as 1 million km2) in 2054-2058. Under a medium-mitigation scenario, both approaches project a decrease to ~1.7 million km2 in the early 2060s, followed by a leveling off in the ice extent. [ABSTRACT FROM AUTHOR]

Background: In 2007, the Intergovernmental Panel on Climate Change (IPCC) presented a report on global warming and the impact of human activities on global warming. Later the Lancet commission identified six ways human health could be affected. Among these were not environmental factors which are also believed to be important for human health. In this paper we therefore focus on environmental factors, climate change and the predicted effects on maternal and newborn health. Arctic issues are discussed specifically considering their exposure and sensitivity to long range transported contaminants. Methods: Considering that the different parts of pregnancy are particularly sensitive time periods for the effects of environmental exposure, this review focuses on the impacts on maternal and newborn health. Environmental stressors known to affects human health and how these will change with the predicted climate change are addressed. Air pollution and food security are crucial issues for the pregnant population in a changing climate, especially indoor climate and food security in Arctic areas. Results: The total number of environmental factors is today responsible for a large number of the global deaths, especially in young children. Climate change will most likely lead to an increase in this number. Exposure to the different environmental stressors especially air pollution will in most parts of the world increase with climate change, even though some areas might face lower exposure. Populations at risk today are believed to be most heavily affected. As for the persistent organic pollutants a warming climate leads to a remobilisation and a possible increase in food chain exposure in the Arctic and thus increased risk for Arctic populations. This is especially the case for mercury. The perspective for the next generations will be closely connected to the expected temperature changes; changes in housing conditions; changes in exposure patterns; predicted increased exposure to Mercury because of increased emissions and increased biological availability. Conclusions: A number of environmental stressors are predicted to increase with climate change and increasingly affecting human health. Efforts should be put on reducing risk for the next generation, thus global politics and research effort should focus on maternal and newborn health. [ABSTRACT FROM AUTHOR]

Abstract: This paper is concerned with the mathematical modelling of complex interactions between plant species in a harsh environment such as in the arctic. The aim of the paper is to consider whether interactions between the species change in character as environments change. For example, if the effect of climate change is to make harsh climates more benign, will this imply changes in the way species interact and affect biodiversity? We consider the interaction of two species of grass. Our model is constructed based on the notion of a summer season when the plants grow, followed by a winter season when there is no growth but when the plants are subject to the effects of events such as winter storms. Our aim is to investigate changes when the summer season is lengthened, when the climate becomes more benign, when the susceptibility of plants to damage as a result of storms is increased, and when the intensity (and number) of winter storms is varied. The models we consider provide new insights into the known behaviour of plant species interactions in such situations and a basis for further modelling and prediction. [Copyright &y& Elsevier]

The Arctic region has exhibited dramatic changes in recent times. Many of these are intimately tied up with synoptic activity, but little research has been undertaken on how the characteristics of Arctic cyclones have changed. This paper presents a comprehensive analysis of Arctic (here defined as the domain north of 70°N) cyclones diagnosed with the Melbourne University cyclone tracking scheme applied to the 40-yr ECMWF Re-Analysis (ERA-40) and the NCEP–NCAR (NCEP1) and NCEP–Department of Energy (DOE) Atmospheric Model Intercomparison Project (AMIP)-II (NCEP2) reanalysis sets (the last two extending to the end of 2006). A wide variety of cyclone characteristics is presented as befits these complex features. In winter the highest density of cyclones is found between Norway and Svalbard and to the east to the Barents and Kara Seas, and significant numbers are found in the central Arctic. In summer the greatest frequencies are found in the central Arctic. The total number of cyclones identified in the ERA-40 record exceeds those in the two NCEP compilations. The mean size of cyclones shows similar maxima in the central Arctic in both winter and summer. By contrast, the greatest mean system depth in winter (in excess of 8 hPa) is found to the southeast of Greenland, although average depths exceed 6 hPa over a considerable portion of the basin. In summer the deepest cyclones are found in the central portion of the Arctic. The analysis shows that the total number of cyclones in winter exceeds that in summer, a result in contrast to earlier studies. This difference comes about primarily due to the greater numbers of “open strong” systems in winter in all reanalyses. Cyclones in this category are associated with very active synoptic situations; it is of importance that they be included in cyclone counts but would not be considered in many cyclone identification schemes. Since 1979 neither the ERA-40 nor the NCEP2 sets show significant trends in any of the cyclone variables considered. However, over the entire record starting in 1958 the NCEP1 reanalysis exhibits a significant increase in summer cyclone frequency (due mainly to the increase in closed strong systems). Both NCEP1 and ERA-40 also reveal significant increases in the number of summer closed strong cyclones, as well as in their mean depth and intensity in that season. Interannual variations in Arctic cyclone numbers are closely related to the Arctic Oscillation (AO) index in the full reanalyses records. An even stronger relationship is found between the AO and the number of deep cyclones. These relationships have still held in the last decade when the AO has returned to more normal values but the summer and fall sea ice extent has continued to decrease. [ABSTRACT FROM AUTHOR]

Downwelling radiation in six regional models from the Arctic Regional Climate Model Intercomparison (ARCMIP) project is systematically biased negative in comparison with observations from the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment, although the correlations with observations are relatively good. In this paper, links between model errors and the representation of clouds in these models are investigated. Although some modeled cloud properties, such as the cloud water paths, are reasonable in a climatological sense, the temporal correlation of model cloud properties with observations is poor. The vertical distribution of cloud water is distinctly different among the different models; some common features also appear. Most models underestimate the presence of high clouds, and, although the observed preference for low clouds in the Arctic is present in most of the models, the modeled low clouds are too thin and are displaced downward. Practically all models show a preference to locate the lowest cloud base at the lowest model grid point. In some models this happens also to be where the observations show the highest occurrence of the lowest cloud base; it is not possible to determine if this result is just a coincidence. Different factors contribute to model surface radiation errors. For longwave radiation in summer, a negative bias is present both for cloudy and clear conditions, and intermodel differences are smaller when clouds are present. There is a clear relationship between errors in cloud-base temperature and radiation errors. In winter, in contrast, clear-sky cases are modeled reasonably well, but cloudy cases show a very large intermodel scatter with a significant bias in all models. This bias likely results from a complete failure in all of the models to retain liquid water in cold winter clouds. All models overestimate the cloud attenuation of summer solar radiation for thin and intermediate clouds, and some models maintain this behavior also for thick clouds. [ABSTRACT FROM AUTHOR]

Climate change is already occurring in the Arctic and the Arctic Climate Impact Assessment recently concluded that future climate change could be devastating for Inuit. This paper characterises vulnerability to climate change in two Inuit communities in the Canadian territory of Nunavut, focusing on the resource harvesting sector. In both communities, Inuit have demonstrated significant adaptability in the face of current changes in climatic conditions. This adaptability is facilitated by traditional Inuit knowledge, strong social networks, flexibility in resource use, and institutional support. Changing Inuit livelihoods, however, have undermined certain aspects of adaptive capacity and have resulted in emerging vulnerabilities. Global and regional climate projections indicate that climatic conditions which currently pose risks are expected to be negatively affected by future climate change. These projections are not without precedent and analysis of current vulnerability and identification of adaptation constraints by Inuit in the two communities indicate the continued importance of traditional coping mechanisms. The ability to draw on these coping mechanisms in light of future climate change, however, will be unequal and the research indicates that young Inuit and those without access to economic resources, in particular, are vulnerable. [ABSTRACT FROM AUTHOR]

The state-of-the-art AOGCM simulations have recently (late 2004–early 2005) been completed for the Intergovernmental Panel on Climate Change (IPCC) in order to provide input to the IPCC’s Fourth Assessment Report (AR4). The present paper synthesizes the new simulations of both the twentieth- and twenty-first-century arctic freshwater budget components for use in the IPCC AR4, and attempts to determine whether demonstrable progress has been achieved since the late 1990s. Precipitation and its difference with evapotranspiration are addressed over the Arctic Ocean and its terrestrial watersheds, including the basins of the four major rivers draining into the Arctic Ocean: the Ob, the Yenisey, the Lena, and the Mackenzie. Compared to the previous [IPCC Third Assessment Report (TAR)] generation of AOGCMs, there are some indications that the models as a class have improved in simulations of the Arctic precipitation. In spite of observational uncertainties, the models still appear to oversimulate area-averaged precipitation over the major river basins. The model-mean precipitation biases in the Arctic and sub-Arctic have retained their major geographical patterns, which are at least partly attributable to the insufficiently resolved local orography, as well as to biases in large-scale atmospheric circulation and sea ice distribution. The river discharge into the Arctic Ocean is also slightly oversimulated. The simulated annual cycle of precipitation over the Arctic Ocean is in qualitative agreement between the models as well as with observational and reanalysis data. This is also generally the case for the seasonality of precipitation over the Arctic Ocean’s terrestrial watersheds, with a few exceptions. Some agreement is demonstrated by the models in reproducing positive twentieth-century trends of precipitation in the Arctic, as well as positive area-averaged P–E late-twentieth-century trends over the entire terrestrial watershed of the Arctic Ocean. For the twenty-first century, three scenarios are considered: A2, A1B, and B1. Precipitation over the Arctic Ocean and its watersheds increases through the twenty-first century, showing much faster percentage increases than the global mean precipitation. The arctic precipitation changes have a pronounced seasonality, with the strongest relative increase in winter and fall, and the weakest in summer. The river discharge into the Arctic Ocean increases for all scenarios from all major river basins considered, and is generally about twice as large as the increase of freshwater from precipitation over the Arctic Ocean (70°–90°N) itself. The across-model scatter of the precipitation increase for each scenario is significant, but smaller than the scatter between the climates of the different models in the baseline period. [ABSTRACT FROM AUTHOR]

Summary Current predictions of the effects of climate change indicate that the Arctic may experience a larger than average increase in temperature with consequent changes to the length of the snow-free active summer period, winter snow depth and amount and frequency of summer precipitation being highly probable. This paper reports on measurements of carbon dioxide flux at a high arctic site at Ny-Ålesund (78° 56′ N, 11° 55′ E), Svalbard and the physical climate variables that largely control this flux. It is shown that during three important precipitation-free periods of the active summer period, namely post snowmelt, high summer, and early autumn, the net balance between CO2 flux from the soil (due to respiration of roots and soil organisms) and CO2 assimilation by the vegetation is controlled largely by soil temperature and solar radiation. A simple combined photosynthetic assimilation-soil respiration model is shown to be capable of simulating the net CO2 flux during mid-summer, but is less proficient in the post snowmelt period and in early autumn when the simple models’ inability to simulate the effects of emergent growth and ponding during the former and senescence, freezing temperatures and dew during the latter indicates the need for a more complex descriptive model. The net CO2 flux during the measurement periods progresses from a net CO2 source of 0.3 gC m-2 d-1 during late snowmelt to a mid summer net CO2 sink of -0.39 gC m-2 d-1, returning to a net CO2 source of 0.1 gC m-2 d-1 in the early autumn. Simple extrapolation of the data indicates that, during the active summer season in 1995, this site was a net sink of CO2 of approximately - 9 gC m-2. [ABSTRACT FROM AUTHOR]

Attribution of extreme events is a challenging science and one that is currently undergoing considerable evolution. In this paper are 19 analyses by 18 different research groups, often using quite different methodologies, of 12 extreme events that occurred in 2012. In addition to investigating the causes of these extreme events, the multiple analyses of four of the events, the high temperatures in the United States, the record low levels of Arctic sea ice, and the heavy rain in northern Europe and eastern Australia, provide an opportunity to compare and contrast the strengths and weaknesses of the various methodologies. The differences also provide insights into the structural uncertainty of event attribution, that is, the uncertainty that arises directly from the differences in analysis methodology. In these cases, there was considerable agreement between the different assessments of the same event. However, different events had very different causes. Approximately half the analyses found some evidence that anthropogenically caused climate change was a contributing factor to the extreme event examined, though the effects of natural fluctuations of weather and climate on the evolution of many of the extreme events played key roles as well. [ABSTRACT FROM AUTHOR]

Pithan and Mauritsen argue that the 2009 results of Boé et al. are not consistent with current understanding of the lapse-rate feedback in the Arctic. They also argue that these results arise to an important extent from self-correlation issues. In this response, the authors argue that their results are not inconsistent with current understanding of lapse-rate feedback and demonstrate that the conclusions remain unchanged when all possibilities of self-correlation are excluded. [ABSTRACT FROM AUTHOR]

Although snow depth on sea ice is a key parameter for sea ice thickness (SIT) retrieval, there currently does not exist reliable estimations. In the Arctic, nearly all SIT products use a snow depth climatology (the modified Warren-99 climatology, W99m) constructed from in situ data obtained prior to the first significant impacts of climate change. In the Antarctic, the lack of information on snow depth remains a major obstacle in the development of reliable SIT products. In this study, we present the latest version of the altimetric snow depth (ASD) product computed over both hemispheres from the difference of the radar penetration into the snow pack between the Ka-band frequency SARAL/Altika and the Ku-band frequency CryoSat-2. The ASD solution is compared against a wide range of snow depth products including model data (Pan-Arctic Ice-Ocean Modelling and Assimilation System (PIOMAS) or its equivalent in the Antarctic the Global Ice-Ocean Modeling and Assimilation System (GIOMAS), the MERCATOR model, and NASA's Eulerian Snow On Sea Ice Model (NESOSIM, only in the Arctic)), the Advanced Microwave Scanning Radiometer-2 (AMSR2) passive radiometer data, and the Dual-altimeter Snow Thickness (DuST) Ka–Ku product (only in the Arctic). The ASD product is further validated in the Arctic against the ice mass balance (IMB) buoys, the CryoSat Validation Experiment (CryoVEx) and Operation Ice Bridge's (OIB) airborne measurements. These comparisons demonstrate that ASD is a relevant snow depth solution, with spatiotemporal patterns consistent with those of the alternative Ka–Ku DuST product but with a mean bias of about 6.5 cm. We also demonstrate that ASD is consistent with the validation data: comparisons with OIB's airborne snow radar in the Arctic during the period of 2014–2018 show a correlation of 0.66 and a RMSE of about 6 cm. Furthermore, a first-guess monthly climatology has been constructed in the Arctic from the ASD product, which shows a good agreement with OIB during 2009–2012. This climatology is shown to provide a better solution than the W99m climatology when compared with validation data. Finally, we have characterised the SIT uncertainty due to the snow depth from an ensemble of SIT solutions computed for the Arctic by using the different snow depth products previously used in the comparison with the ASD product. During the period of 2013–2019, we found a spatially averaged SIT mean standard deviation of 20 cm. Deviations between SIT estimations due to snow depths can reach up to 77 cm. Using the ASD data instead of W99m to estimate SIT over this time period leads to a reduction in the average SIT of about 30 cm. [ABSTRACT FROM AUTHOR]

In a warming climate, permafrost is likely to be significantly reduced and eventually disappear from the sub-Arctic region. This will affect people at a range of scales, from locally by slumping of buildings and roads, to globally as melting of permafrost will most likely increase the emissions of the powerful greenhouse gas methane, which will further enhance global warming. In order to predict future changes in permafrost, it is crucial to understand what determines the presence or absence of permafrost under current climate conditions, to assess where permafrost is particularly vulnerable to climate change, and to identify where changes are already occurring. The Torneträsk region of northern sub-Arctic Sweden is one area where changes in permafrost have been recorded and where permafrost could be particularly vulnerable to any future climate changes. This paper therefore reviews the various physical, biological, and anthropogenic parameters that determine the presence or absence of permafrost in the Torneträsk region under current climate conditions, so that we can gain an understanding of its current vulnerability and potential future responses to climate change. A patchy permafrost distribution as found in the Torneträsk region is not random, but a consequence of site-specific factors that control the microclimate and hence the surface and subsurface temperature. It is also a product of past as well as current processes. In sub-Arctic areas such as northern Sweden, it is mainly the physical parameters, e.g., topography, soil type, and climate (in particular snow depth), that determine permafrost distribution. Even though humans have been present in the study area for centuries, their impacts on permafrost distribution can more or less be neglected at the catchment level. Because ongoing climate warming is projected to continue and lead to an increased snow cover, the permafrost in the region will most likely disappear within decades, at least at lower elevations. [ABSTRACT FROM AUTHOR]

Given uncertainty in the processes involved in polar amplification, elucidating the role of poleward heat and moisture transport is crucial. The Polar Amplification Model Intercomparison Project (PAMIP) permits robust separation of the effects of sea ice loss from sea surface warming under climate change. We utilize a moist isentropic circulation framework that accounts for moisture transport, condensation, and eddy transport, in order to analyze the circulation connecting the mid‐latitudes and the Arctic. In PAMIP's atmospheric general circulation model experiments, prescribed sea ice loss reduces poleward heat transport (PHT) by warming the returning moist isentropic circulation at high latitudes, while prescribed warming of the ocean surface increases PHT by strengthening the moist isentropic circulation. Inter‐model spread of PHT into the Arctic reflects the tug‐of‐war between sea‐ice and surface‐warming effects. Plain Language Summary: A major conundrum in current climate science is to understand what Arctic changes imply for the climate and environment in mid‐latitude regions. The Polar Amplification Model Intercomparison Project (PAMIP) designed a set of climate model experiments to specifically answer this question in a carefully designed, idealized framework. PAMIP's approach is to separate historic and projected climate change into parts associated with Arctic sea ice loss and ocean surface warming and investigate how these two contributions can influence the atmosphere. To isolate these effects, only models can be used, because, in reality, sea ice loss and ocean surface warming are strongly linked together. This letter focuses on what the PAMIP experiments imply for the transport and redistribution of heat and moisture in the atmosphere. In PAMIP, we learn that Arctic sea ice loss causes the atmosphere to reduce the transport of dry and cold air away from the Arctic while ocean warming causes more transport of moist warm air toward the Arctic. These two effects are in a tug‐of‐war, suggesting that climate change can cause a mix of competing impacts on the global energy transport from the tropics to the Arctic. Key Points: Sea ice loss exports static energy from the Arctic by warming the equatorward branch of the global mass circulationSea surface warming imports static energy into the Arctic by increasing the mid‐latitude mass transport, overwhelming the sea ice effectThere is more spread amongst models for the effect of sea‐surface warming than for sea ice loss [ABSTRACT FROM AUTHOR]

The most discernible and devastating impacts of climate change are caused by events with temporary extreme conditions (‘‘extreme events’’) or abrupt shifts to a new persistent climate state (‘‘tipping points’’). The rapidly growing amount of data from models and observations poses the challenge to reliably detect where, when, why, and how these events occur. This situation calls for data-mining approaches that can detect and diagnose events in an automatic and reproducible way. Here, we apply a new strategy to this task by generalizing the classical machine-vision problem of detecting edges in 2D images to many dimensions (including time). Our edge detector identifies abrupt or extreme climate events in spatio temporal data, quantifies their abruptness (or extremeness), and provides diagnostics that help one to understand the causes of these shifts. We also publish a comprehensive toolset of code that is documented and free to use. We document the performance of the new edge detector by analyzing several datasets of observations and models. In particular, we apply it to all monthly 2D variables of the RCP8.5 scenario of the Coupled Model Inter comparison Project (CMIP5). More than half of all simulations show abrupt shifts of more than 4 standard deviations on a time scale of 10 years. These shifts are mostly related to the loss of sea ice and permafrost in the Arctic. Our results demonstrate that the edge detector is particularly useful to scan large datasets in an efficient way, for example multi model or perturbed-physics ensembles. It can thus help to reveal hidden ‘‘climate surprises’’ and to assess the uncertainties of dangerous climate events. [ABSTRACT FROM AUTHOR]

Aerosols emitted from wildfires could significantly affect global climate through perturbing global radiation balance. In this study, the Community Earth System Model with prescribed daily fire aerosol emissions is used to investigate fire aerosols' impacts on global climate with emphasis on the role of climate feedbacks. The total global fire aerosol radiative effect (RE) is estimated to be −0.78 ± 0.29 W m−2, which is mostly from shortwave RE due to aerosol–cloud interactions (REaci; −0.70 ± 0.20 W m−2). The associated global annual-mean surface air temperature (SAT) change ∆T is −0.64 ± 0.16 K with the largest reduction in the Arctic regions where the shortwave REaci is strong. Associated with the cooling, the Arctic sea ice is increased, which acts to reamplify the Arctic cooling through a positive ice-albedo feedback. The fast response (irrelevant to ∆T) tends to decrease surface latent heat flux into atmosphere in the tropics to balance strong atmospheric fire black carbon absorption, which reduces the precipitation in the tropical land regions (southern Africa and South America). The climate feedback processes (associated with ∆T) lead to a significant surface latent heat flux reduction over global ocean areas, which could explain most (~80%) of the global precipitation reduction. The precipitation significantly decreases in deep tropical regions (5°N) but increases in the Southern Hemisphere tropical ocean, which is associated with the southward shift of the intertropical convergence zone and the weakening of Southern Hemisphere Hadley cell. Such changes could partly compensate the interhemispheric temperature asymmetry induced by boreal forest fire aerosol indirect effects, through intensifying the cross-equator atmospheric heat transport. [ABSTRACT FROM AUTHOR]

Climate change projections still suffer from a limited representation of the permafrost-carbon feedback. Predicting the response of permafrost temperature to climate change requires accurate simulations of Arctic snow and soil properties. This study assesses the capacity of the coupled land surface and snow models ISBA-Crocus and ISBA-ES to simulate snow and soil properties at Bylot Island, a high Arctic site. Field measurements complemented with ERA-Interim reanalyses were used to drive the models and to evaluate simulation outputs. Snow height, density, temperature, thermal conductivity and thermal insulance are examined to determine the critical variables involved in the soil and snow thermal regime. Simulated soil properties are compared to measurements of thermal conductivity, temperature and water content. The simulated snow density profiles are unrealistic, which is most likely caused by the lack of representation in snow models of the upward water vapor fluxes generated by the strong temperature gradients within the snowpack. The resulting vertical profiles of thermal conductivity are inverted compared to observations, with high simulated values at the bottom of the snowpack. Still, ISBA-Crocus manages to successfully simulate the soil temperature in winter. Results are satisfactory in summer, but the temperature of the top soil could be better reproduced by adequately representing surface organic layers, i.e., mosses and litter, and in particular their water retention capacity. Transition periods (soil freezing and thawing) are the least well reproduced because the high basal snow thermal conductivity induces an excessively rapid heat transfer between the soil and the snow in simulations. Hence, global climate models should carefully consider Arctic snow thermal properties, and especially the thermal conductivity of the basal snow layer, to perform accurate predictions of the permafrost evolution under climate change. [ABSTRACT FROM AUTHOR]

Recent climate change has been especially pronounced in the High Arctic, however, the responses of aquatic biota, such as diatoms, can be modified by site-specific environmental characteristics. To assess if climate-mediated ice cover changes affect the diatom response to climate, we used paleolimnological techniques to examine shifts in diatom assemblages from ten High Arctic lakes and ponds from Ellesmere Island and nearby Pim Island (Nunavut, Canada). The sites were divided a priori into four groups (“warm”, “cool”, “cold”, and “oasis”) based on local elevation and microclimatic differences that result in differing lengths of the ice-free season, as well as about three decades of personal observations. We characterized the species changes as a shift from Condition 1 (i.e. a generally low diversity, predominantly epipelic and epilithic diatom assemblage) to Condition 2 (i.e. a typically more diverse and ecologically complex assemblage with an increasing proportion of epiphytic species). This shift from Condition 1 to Condition 2 was a consistent pattern recorded across the sites that experienced a change in ice cover with warming. The “warm” sites are amongst the first to lose their ice covers in summer and recorded the earliest and highest magnitude changes. The “cool” sites also exhibited a shift from Condition 1 to Condition 2, but, as predicted, the timing of the response lagged the “warm” sites. Meanwhile some of the “cold” sites, which until recently still retained an ice raft in summer, only exhibited this shift in the upper-most sediments. The warmer “oasis” ponds likely supported aquatic vegetation throughout their records. Consequently, the diatoms of the “oasis” sites were characterized as high-diversity, Condition 2 assemblages throughout the record. Our results support the hypothesis that the length of the ice-free season is the principal driver of diatom assemblage responses to climate in the High Arctic, largely driven by the establishment of new aquatic habitats, resulting in increased diversity and the emergence of novel growth forms and epiphytic species. [ABSTRACT FROM AUTHOR]

Climate change is facilitating rapid changes in the composition and distribution of vegetation at northern latitudes, raising questions about the responses of wildlife that rely on arctic ecosystems. One widely observed change occurring in arctic tundra ecosystems is an increasing dominance of deciduous shrub vegetation. Our goals were to examine the tolerance of arctic-nesting bird species to existing gradients of vegetation along the boreal forest-tundra ecotone, to predict the abundance of species across different heights and densities of shrubs, and to identify species that will be most or least responsive to ongoing expansion of shrubs in tundra ecosystems. We conducted 1,208 point counts on 12 study blocks from 2012–2014 in northwestern Alaska, using repeated surveys to account for imperfect detection of birds. We considered the importance of shrub height, density of low and tall shrubs (i.e. shrubs >0.5 m tall), percent of ground cover attributed to shrubs (including dwarf shrubs <0.5 m tall), and percent of herbaceous plant cover in predicting bird abundance. Among 17 species considered, only gray-cheeked thrush (Catharus minimus) abundance was associated with the highest values of all shrub metrics in its top predictive model. All other species either declined in abundance in response to one or more shrub metrics or reached a threshold where further increases in shrubs did not contribute to greater abundance. In many instances the relationship between avian abundance and shrubs was nonlinear, with predicted abundance peaking at moderate values of the covariate, then declining at high values. In particular, a large number of species were responsive to increasing values of average shrub height with six species having highest abundance at near-zero values of shrub height and abundance of four other species decreasing once heights reached moderate values (≤ 33 cm). Our findings suggest that increases in shrub cover and density will negatively affect abundance of only a few bird species and may potentially be beneficial for many others. As shrub height increases further, however, a considerable number of tundra bird species will likely find habitat increasingly unsuitable. [ABSTRACT FROM AUTHOR]

It is one of the most robust projected responses of climate models to the increase of atmospheric CO2 concentration that the Arctic experiences a rapid warming with a magnitude larger than the rest of the world. While many processes are proposed as important, the relative contribution of individual processes to the Arctic warming is not often investigated systematically. Feedbacks are quantified in two different versions of an atmosphere-ocean GCM under idealized transient experiments based on an energy balance analysis that extends from the surface to the top of the atmosphere. The emphasis is placed on the largest warming from late autumn to early winter (October-December) and the difference from other seasons. It is confirmed that dominating processes vary with season. In autumn, the largest contribution to the Arctic surface warming is made by a reduction of ocean heat storage and cloud radiative feedback. In the annual mean, on the other hand, it is the albedo feedback that contributes the most, with increasing ocean heat uptake to the deeper layers working as a negative feedback. While the qualitative results are robust between the two models, they differ quantitatively, indicating the need for further constraint on each process. Ocean heat uptake, lower tropospheric stability, and low-level cloud response probably require special attention. [ABSTRACT FROM AUTHOR]

Climate change is occurring more rapidly in the Arctic than other places in the world, which is likely to alter the distribution and abundance of migratory birds breeding there. A warming climate can provide benefits to birds by decreasing spring snow cover, but increases in the frequency of summer rainstorms, another product of climate change, may reduce foraging opportunities for insectivorous birds. Cyclic lemming populations in the Arctic also influence bird abundance because Arctic foxes begin consuming bird eggs when lemmings decline. The complex interaction between summer temperature, precipitation, and the lemming cycle hinder our ability to predict how Arctic-breeding birds will respond to climate change. The main objective of this study was to investigate the relationship between annual variation in weather, spring snow cover, lemming abundance and spatiotemporal variation in the abundance of multiple avian guilds in a tundra ecosystem in central Nunavut, Canada: songbirds, shorebirds, gulls, loons, and geese. We spatially stratified our study area based on vegetation productivity, terrain ruggedness, and freshwater abundance, and conducted distance sampling to estimate strata-specific densities of each guild during the summers of 2010–2012. We also monitored temperature, rainfall, spring snow cover, and lemming abundance each year. Spatial variation in bird abundance matched what was expected based on previous ecological knowledge, but weather and lemming abundance also significantly influenced the abundance of some guilds. In particular, songbirds were less abundant during the cool, wet summer with moderate snow cover, and shorebirds and gulls declined with lemming abundance. The abundance of geese did not vary over time, possibly because benefits created by moderate spring snow cover were offset by increased fox predation when lemmings were scarce. Our study provides an example of a simple way to monitor the correlation between weather, spring snow cover, lemming abundance, and spatiotemporal variations in Arctic-breeding birds. [ABSTRACT FROM AUTHOR]

Most spatial modelling of climate change impacts on permafrost has been conducted at half-degree latitude/ longitude or coarser spatial resolution. At such coarse resolution, topographic effects on insolation cannot be considered accurately and the results are not suitable for landuse planning and ecological assessment. Here we mapped climate change impacts on permafrost from 1968 to 2100 at 10m resolution using a process-based model for Ivvavik National Park, an Arctic region with complex terrain in northern Yukon, Canada. Soil and drainage conditions were defined based on ecosystem types, which were mapped using SPOT imagery. Leaf area indices were mapped using Landsat imagery and the ecosystem map. Climate distribution was estimated based on elevation and station observations, and the effects of topography on insolation were calculated based on slope, aspect and viewshed. To reduce computation time, we clustered climate distribution and topographic effects on insolation into discrete types. The modelled active-layer thickness and permafrost distribution were comparable with field observations and other studies. The map portrayed large variations in active-layer thickness, with ecosystem types being the most important controlling variable, followed by climate, including topographic effects on insolation. The results show deepening in active-layer thickness and progressive degradation of permafrost, although permafrost will persist in most of the park during the 21st century. This study also shows that ground conditions and climate scenarios are the major sources of uncertainty for high-resolution permafrost mapping. [ABSTRACT FROM AUTHOR]

Clouds play a crucial role in the Arctic climate system. Therefore, it is essential to accurately and reliably quantify and understand cloud properties over the Arctic. It is also important to monitor and attribute changes in Arctic clouds. Here, we exploit the capability of the CALIPSO-CALIOP instrument and provide comprehensive statistics of tropospheric thin clouds, otherwise extremely difficult to monitor from passive satellite sensors. We use 4 yr of data (June 2006-May 2010) over the circumpolar Arctic, here defined as 67-82°N, and characterize probability density functions of cloud base and top heights, geometrical thickness and zonal distribution of such cloud layers, separately for water and ice phases, and discuss seasonal variability of these properties. When computed for the entire study area, probability density functions of cloud base and top heights and geometrical thickness peak at 200-400, 1000-2000 and 400-800 m, respectively, for thin water clouds, while for ice clouds they peak at 6-8, 7-9 and 400-1000 m, respectively. In general, liquid clouds were often identified below 2 km during all seasons, whereas ice clouds were sensed throughout the majority of the upper troposphere and also, but to a smaller extent, below 2 km for all seasons. [ABSTRACT FROM AUTHOR]

Climate development with possible anthropogenic effects occurs on a background of natural climatic variations, which may be considerable, and especially in the Arctic. Natural climate variations however remain poorly understood, although they remain important for discriminating between natural and anthropogenic influences on current climate change. Using the Svalbard (78?N) surface air temperature record 1912-2010 as an example, we here suggest a road ahead to identify and describe such natural climate variations. By means of Fourier and wavelet analysis the record is decomposed into time-frequency space, to extract information on periodic signals and their amplitude and variation over time. By this we identify several cyclic variations on the time scale investigated. These oscillations are present in the annual record, as well as in seasonal subsets of the record. Using only three oscillations it is possible to hindcast the Svalbard temperature record well. We suggest that such persistent oscillations may be used for forecasting the overall features of future temperature changes for a limited period, about 10-25% of the record length. Our main focus is on identifying the character of recurrent natural temperature variations, but we also comment briefly on possible physical explanations for some of the identified cyclic variations. [ABSTRACT FROM AUTHOR]

The large spread of the response to anthropogenic forcing simulated by state-of-the-art climate models in the Arctic is investigated. A feedback analysis framework specific to the Arctic is developed to address this issue. The feedback analysis shows that a large part of the spread of Arctic climate change is explained by the longwave feedback parameter. The large spread of the negative longwave feedback parameter is in turn mainly due to variations in temperature feedback. The vertical temperature structure of the atmosphere in the Arctic, characterized by a surface inversion during wintertime, exerts a strong control on the temperature feedback and consequently on simulated Arctic climate change. Most current climate models likely overestimate the climatological strength of the inversion, leading to excessive negative longwave feedback. The authors conclude that the models’ near-equilibrium response to anthropogenic forcing is generally too small. [ABSTRACT FROM AUTHOR]

The Arctic is extremely vulnerable to projected climate change, and global warming may result in major community reorganizations. The aim of this study was a thorough investigation of plant biomass production throughout an entire growing season in five different high arctic vegetation types: Cassiope, Dryas, and Salix heath, grassland, and fen. The main focus was on the gross ecosystem production (GEP), and the biotic and abiotic factors which may influence GEP. Photosynthesis, aboveground biomass, and carbon, nitrogen, and chlorophyll content were measured weekly during nine weeks. There were large differences in seasonal growth and production within and among vegetation types. Mosses contributed considerably to the total C and N pool in grassland, fen, and Salix heath. Fen, which had the highest pool of leaf N, leaf chlorophyll, and moss N, was the most productive vegetation type in terms of GEP, despite the lowest total biomass. Across vegetation types, leaf biomass, leaf N, and moss N pool size influenced GEP. Within most vegetation types GEP correlated with leaf N, in correspondence with the notion that N may limit plant production in many high arctic ecosystems. The timing of the peaks in C and N pools in leaves did not coincide with that in the mosses and in woody tissues. This emphasizes the importance of sampling throughout the growing season, when using field data from the Arctic to estimate plant biomasses and modeling C and N fluxes and pool sizes. [ABSTRACT FROM AUTHOR]

The article focuses on the history of arctic aerosols. Arctic is considered as the head of contemporary climate change which deeply modified by the distant emissions of the green gases. The first discovery of Arctic aerosol pollution happened between 1940 and 1950. The disturbance of aerosols from midlatitudes in the Arctic climate has been considered as the prevailing anthropogenic climate signature. The examination for the future development of aerosol contributions in the Arctic needs a long-term maintenance of network observation.

The article reflects on the climate lessons from the first International Polar Year (IPY). The section focuses on a unique glimpse of the Arctic from a period before the present era of climate warming is found in the records of the first IPY of 1882-83. The purpose of the study was to discover the fundamental laws governing global meteorological and geophysics phenomena. The study also aims to contribute significant information to the upcoming fourth IPY scheduled for 2007-08: to understand the climate changes currently unfolding in the Arctic/Antarctic within the context of the past.

Early conceptual models and global climate model (GCM) simulations both indicated the likelihood of an enhanced sensitivity to climate change in the polar regions, derived from the positive feedbacks brought about by snow and ice. As GCMs developed, however, the expected enhanced sensitivity has been more robust in the North Polar Region than the South Polar Region. Some recent increased-CO2 simulations, for instance, show little change in Southern Ocean sea ice extent and thickness and much less warming in the Southern Ocean region than in the sea ice regions of the Northern Hemisphere. Observations show a highly variable Southern Ocean ice cover that decreased significantly in the 1970s but, overall, has increased since the late 1970s. The increases are non-uniform, and in fact decreases occurred in the last three years of the 1979-2002 satellite record highlighted here. Regionally, the positive trends since the late 1970s are strongest in the Ross Sea, while the trends are negative in the Bellingshausen and Amundsen seas, a pattern that appears in greater spatial detail in maps of trends in the length of the sea ice season. These patterns correspond well with patterns of temperature trends, but there is a substantial way to go before they are understood (and can be modelled) in the full context of global change. [ABSTRACT FROM AUTHOR]