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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]

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]

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]

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]

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]

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]

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]