scholarly journals What Goes Up Must Come Down: The Influence of Climate on Caribou Populations

2021 ◽  
Vol 9 ◽  
Author(s):  
Kyle Joly
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
The Arctic ◽  
Climate Oscillations ◽  
Wildlife Populations ◽  
Very High ◽  
Number Of Births

Wildlife populations naturally go up and down. Oscillation is the term used for this pattern of highs (when there are many animals) and lows (when there are few). When the number of births is greater than the number of deaths, then populations grow. If deaths exceed births, populations decline. Caribou in the Arctic have dramatic population oscillations. The number of caribou can grow very high and also decrease to very few. Large-scale, long-lasting weather oscillations are one reason for this pattern. Knowledge of the connection between wildlife populations and climate oscillations is important to help conserve species like caribou and to better understand how climate change will impact wildlife.

scholarly journals Melt Pond Retrieval Based on the LinearPolar Algorithm Using Landsat Data

2021 ◽  
Vol 13 (22) ◽  
pp. 4674
Author(s):  
Yuqing Qin ◽  
Jie Su ◽  
Mingfeng Wang
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Relative Error ◽  
Large Scale ◽  
The Arctic ◽  
Landsat Data ◽  
Melt Pond ◽  
Melt Ponds ◽  
Very High ◽  
Sentinel 2

The formation and distribution of melt ponds have an important influence on the Arctic climate. Therefore, it is necessary to obtain more accurate information on melt ponds on Arctic sea ice by remote sensing. The present large-scale melt pond products, especially the melt pond fraction (MPF), still require verification, and using very high resolution optical satellite remote sensing data is a good way to verify the large-scale retrieval of MPF products. Unlike most MPF algorithms using very high resolution data, the LinearPolar algorithm using Sentinel-2 data considers the albedo of melt ponds unfixed. In this paper, by selecting the best band combination, we applied this algorithm to Landsat 8 (L8) data. Moreover, Sentinel-2 data, as well as support vector machine (SVM) and iterative self-organizing data analysis technique (ISODATA) algorithms, are used as the comparison and verification data. The results show that the recognition accuracy of the LinearPolar algorithm for melt ponds is higher than that of previous algorithms. The overall accuracy and kappa coefficient results achieved by using the LinearPolar algorithm with L8 and Sentinel-2A (S2), the SVM algorithm, and the ISODATA algorithm are 95.38% and 0.88, 94.73% and 0.86, and 92.40%and 0.80, respectively, which are much higher than those of principal component analysis (PCA) and Markus algorithms. The mean MPF (10.0%) obtained from 80 cases from L8 data based on the LinearPolar algorithm is much closer to Sentinel-2 (10.9%) than the Markus (5.0%) and PCA algorithms (4.2%), with a mean MPF difference of only 0.9%, and the correlation coefficients of the two MPFs are as high as 0.95. The overall relative error of the LinearPolar algorithm is 53.5% and 46.4% lower than that of the Markus and PCA algorithms, respectively, and the root mean square error (RMSE) is 30.9% and 27.4% lower than that of the Markus and PCA algorithms, respectively. In the cases without obvious melt ponds, the relative error is reduced more than that of those with obvious melt ponds because the LinearPolar algorithm can identify 100% of dark melt ponds and relatively small melt ponds, and the latter contributes more to the reduction in the relative error of MPF retrieval. With a wider range and longer time series, the MPF from Landsat data are more efficient than those from Sentinel-2 for verifying large-scale MPF products or obtaining long-term monitoring of a fixed area.

The Frontier Research System for Global Change—The International Arctic Research Center (Frontier-IARC): its Origin and Tentative Science Plan

1999 ◽  
Vol 33 (1) ◽  
pp. 81-84
Author(s):  
Jinro Ukila ◽  
Moloyoshi Ikeda
Keyword(s):  
Climate Change ◽  
Global Change ◽  
Global Climate Change ◽  
Large Scale ◽  
Global Climate ◽  
Research Effort ◽  
Arctic Region ◽  
Research Center ◽  
The Arctic ◽  
Research System

The Frontier Research System for Global Change—the International Arctic Research Center (Frontier-IARC) is a research program funded by the Frontier Research System for Global Change. The program is jointly run under a cooperative agreement between the Frontier Research System for Global Change and the University of Alaska Fairbanks. The aim of the program is to understand the role of the Arctic region in global climate change. The program concentrates its research effort initially on the areas of air-sea-ice interactions, bio-geochemical processes and the ecosystem. To understand the arctic climate system in the context of global climate change, we focus on mechanisms controlling arctic-subarctic interactions, and identify three key components: the freshwater balance, the energy balance, and the large-scale atmospheric processes. Knowledge of details of these components and their interactions will be gained through long-term monitoring, process studies, and modeling; our focus will be on the latter two categories.

scholarly journals Assessing the risks to United States and Canadian mammals caused by climate change using a trait-mediated model

2019 ◽  
Author(s):  
Christy M McCain
Keyword(s):  
Climate Change ◽  
United States ◽  
Large Scale ◽  
Human Impacts ◽  
Mammalian Species ◽  
Species Traits ◽  
The United States ◽  
Mammal Species ◽  
Climate Change Risk ◽  
Very High

Abstract A set of 182 populations of 76 mammal species in the United States and Canada, examined in natural conditions with minimized disturbances or management effects, shows that responses to climate change include negative responses, such as elevational range contractions, upward shifts and decreases in abundance, positive responses, such as range expansions, and no detectable responses. Responses vary among and within mammal species but many are correlated with species traits, particularly the responses linked to high extinction risks (= climate change risk: decreases in population sizes, range contractions, local extirpations). The traits showing the strongest links to differential responses to climate change are 1) body size—large mammals respond more often and most negatively to climate change, 2) activity times—few mammals with flexible active times respond to climate change, and 3) spatial distribution—high-latitude and high-elevation mammals responded more often to climate change. Using these traits and two approaches to trait weighting, I modeled the relative climate change risk for all 328 terrestrial, nonvolant mammal species in the United States and Canada across 10 levels of risk (low = 1–2, moderate = 3–4, moderate-high = 5–6, high = 7–8, very high = 9–10). The models predicted that 15% of these mammalian species are in the high- and very high-risk categories, including species from most orders. Many mammal populations and species listed as of conservation concern due to other human impacts by national or international agencies are also predicted by my models to be in the higher categories of climate change risk. My intention for these models is to clarify for managers and researchers which, where, and how mammals are responding to climate change relatively independent of other anthropogenic stressors (e.g., large-scale habitat change, overhunting) and to provide a preliminary assessment of species most in need of careful monitoring for climate change impacts.

7.  An Examination of the Use of Salix Arctica for Dendrochronological Studies in the Arctic

2017 ◽  
Author(s):  
Anthony Bassutti
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Annual Growth ◽  
The Arctic ◽  
Growth Rings ◽  
Proxy Records ◽  
Land Disturbance ◽  
Annual Growth Rings ◽  
Salix Arctica ◽  
Large Scale Land

Large scale land disturbances are occurring in sensitive Arctic regions as a result of climate change. These disturbances which are caused by permafrost melting and can damage fragile tundra ecosystems and have important impacts on downstream water quality. Determining the timeline of these disturbances will aid in the understanding of the effect of climate change in the Arctic. This can be performed through the analysis of environmental proxy records such as those found in the annual growth rings of trees, which express environmental stresses, such as those experienced during a land disturbance. Dendrochronology of the most northern occurring woody plant, Salix arctica (arctic willow) has been explored only a few times in the past, and its potential for paleoenvironmental studies in the Arctic have been largely over‐looked. We examined the thickness of annual growth rings from S. arctica from two areas of land disturbance on southern Melville Island, Nunavut. Common growth trends were found in both dead (snag) and living samples from the sites. Preliminary data show that a substantial disturbance in the growth of the samples is evident approximately 40 years ago and was likely due to land disturbance. These initial findings demonstrate the successful use of S. arctica as a paleoenvironmental indicator and provide useful tools to determine the timing of past permafrost disturbances and climate change in the Arctic. We are continuing to investigate additional samples from other sites to determine if the method can be used as a novel tool for understanding permafrost landscape dynamics.

scholarly journals Coherent responses of sulphate concentration in Norwegian lakes: relationships with sulphur deposition and climate indices

2003 ◽  
Vol 7 (4) ◽  
pp. 596-608 ◽  
Author(s):  
P. J. Dillon ◽  
B. L. Skjelkvåle ◽  
K. M. Somers ◽  
K. Tørseth
Keyword(s):  
Climate Change ◽  
Acid Deposition ◽  
Large Scale ◽  
Temporal Trends ◽  
The Arctic ◽  
Climate Indices ◽  
Strongly Correlated ◽  
Sulphur Deposition ◽  
Arctic Oscillation Index ◽  
S Deposition

Abstract. The coherence or synchrony in the trends in SO42– concentration in a set of 100 lakes in Norway that have a long-term chemical record was evaluated. Using a statistical technique that compares patterns or trends that are not uni-directional, the lakes were grouped into 18 subsets or clusters, each with between 2 and 11 lakes that had similar trends. These temporal trends were strongly correlated with several climate indices, notably the Arctic Oscillation Index (AOI) measured in the autumn, and the annual North Atlantic Oscillation Index (NAOI). Because these clusters of lakes were spatially dispersed, they could not be compared directly with trends in wet S deposition, because S deposition varied substantially between lakes within each cluster. However, the average trend in SO42– concentration was evaluated in each of 10 regions of Norway that were defined previously on the basis of pollution load, meteorological variables and biogeography. Although these regions did not match the statistically-selected clusters of lakes with equal trends very closely, there were similar, strong correlations between climate indices (the AOI and NAOI) and the 10 average SO42– trends, although there were even stronger relationships with average wet S deposition in the regions. When subsets of lakes with coherent SO42– trends were selected from within each of the 10 regions, both wet S deposition and the climate indices were strongly correlated with those SO42– trends. Hence, lakes in Norway respond to changes in wet S deposition and are influenced by large-scale, i.e. global, climate signals. Future evaluation of recovery of lakes affected by acid deposition must therefore consider the confounding effects of climate and potential climate change. Keywords: recovery, acid deposition, coherence, sulphate, climate change

scholarly journals CLIMATE CHANGE A REPERCUSSION OF HUMAN INDUCED SYSTEMS

2021 ◽  
Vol 9 (09) ◽  
pp. 449-452
Author(s):  
Shweta Chand ◽  
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Temperature Rise ◽  
Large Scale ◽  
Crop Yields ◽  
Heat Waves ◽  
Human Impacts ◽  
World Health ◽  
The Arctic ◽  
Weather Extremes

Climate change includes both the global warming driven by human emissions of greenhouse gases, and the resulting large-scale shifts in weather patterns. Though there have been previous periods of climatic change, since the mid-20th century, humans have had unprecedented impact on Earths climate system and caused change on a global scale.The largest driver of warming is the emission of greenhouse gases, of which more than 90% are carbon dioxide and methane. Fossil fuel burning (coal, oil, and gas) for energy consumption is the main source of these emissions, with additional contributions from agriculture, deforestation, and industrial processes. The human cause of climate change is not disputed by any scientific body of national or international standing. Temperature rise is accelerated or tempered by climate feedbacks, such as loss of sunlight-reflecting snow and ice cover, increased water vapour (a greenhouse gas itself), and changes to land and ocean carbon sinks.Temperature rise on land is about twice the global average increase, leading to desert expansion and more common heat waves and wildfires. Increasing rates of evaporation cause more intense storms and weather extremes. Temperature rise is amplified in the Arctic, where it has contributed to melting permafrost and the retreat of glaciers and sea ice. Additional warming also increases the risk of triggering critical thresholds called tipping points. Impacts on ecosystems include the relocation or extinction of many species as their environment changes, most immediately in coral reefs, mountains, and the Arctic. Human impacts include undernutrition and hunger from reduced crop yields, declining fish stocks, increases in vector-borne diseases, potentially severe economic impacts, increased global economic inequality, more people living in uninhabitable climate zones, and increased migration.Effects such as these have led the World Health Organization to declare climate change the greatest threat to global health in the 21st century. Even if efforts to minimize future warming are successful, some effects will continue for centuries, including rising sea levels, rising ocean temperatures, and ocean acidification.

Characterizing the atmospheric boundary layer over Disko Bay: local structure and links to global dynamics

2021 ◽  
Author(s):  
Arno Hammann ◽  
Kirsty Langley
Keyword(s):  
Climate Change ◽  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Large Scale ◽  
Climate Models ◽  
Current Knowledge ◽  
The Arctic ◽  
Global Dynamics ◽  
Ecosystem Monitoring ◽  
Reanalysis Dataset

<p>Surface air temperatures have been rising roughly twice as fast in the Arctic as in the global average (“Arctic amplification”). Not all responsible physical mechanisms are understood or known, and current climate models frequently underestimate the pace of Arctic warming. Knowledge is lacking specifically about processes involving moisture and the formation of clouds in the the atmospheric boundary layer (ABL). This reduces the reliability of Arctic and global climate change projections and short-term weather predictions.</p><p>We use a comprehensive multi-sensor observational dataset from the Greenland Ecosystem Monitoring (GEM, https://g-e-m.dk/) research site in Qeqertarsuaq, Greenland, in order to identify dominant structural and dynamic patterns of the ABL. Central to this dataset are the atmospheric column profiles of air temperature and water content acquired by a passive microwave radiometer, one of only three such instruments operating in Greenland. The in situ data is related to the large-scale circulation via an analysis of the global ERA5 reanalysis dataset, with a focus on moisture transport from humid latitudes.</p><p>The statistical analysis comprises both process-level relationships between observed variables (regressions) for individual events and pattern recognition techniques (clustering) for the identification of dominant patterns on the small and large scale, an approach particularly suited for the study of an unsteady, changing climate. Moisture enters the Arctic in narrow and infrequent atmospheric bands termed atmospheric rivers, and climate change may alter the frequency of such events, but also the thermodynamic reaction of the ABL to the moisture influx. The current knowledge of the cloudy polar ABL is insufficient to predict important aspects of its behavior, e.g. the lifetime of clouds and the strength of their radiative effect, as well as how large-scale atmospheric dynamics and the presence of elevated inversion layers interact with the structure of the ABL.</p>

Green Edge Outreach Project: A large-scale public and educational initiative

Polar Record ◽  
2019 ◽  
Vol 55 (4) ◽  
pp. 227-234 ◽  
Author(s):  
Julie Sansoulet ◽  
Jean-Jacques Pangrazi ◽  
Noé Sardet ◽  
Sharif Mirshak ◽  
Ghassan Fayad ◽  
...  
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
The Arctic ◽  
Human Populations ◽  
School Age ◽  
The Arctic Ocean ◽  
Scientific Project ◽  
Primary School Age ◽  
Diverse Groups ◽  
The Impact

AbstractA collective outreach approach is fundamental for a scientific project. The Green Edge Project studied the impact of climate change on the dynamics of phytoplankton and their role in the Arctic Ocean, including the impact on human populations. We involved scientists and target audiences to ensure that the communications strategy was in agreement with scientists and audience requirements. We developed websites (academic site and blogs and an educational platform). Then, we produced a 52-minute documentary, ‘Arctic Bloom’, and infographics were created to explain experiments on the ice. We also organised a photo exhibition and live videos that enabled primary school-age students to ask questions directly of scientists working on the research icebreaker. Finally, both students and professionals drew their own conception of Arctic science, and our social media sites reached diverse groups of people. The evaluation results showed a large number of education structures (approximately 8000 schools and 104 museums or educational organisations) engaged with our communications outputs and encouraging statistics about website visits (117 021 and 3739 visits on the blog and the YouTube channel, respectively). Selecting different, but intersecting techniques, to promote a better understanding of the science contributed to the success of the communication and outreach outputs of the 3-year project.

scholarly journals Arctic Petroleum and the 2°C Goal: a Case for Accountability for Fossil-Fuel Supply

Climate Law ◽  
2020 ◽  
Vol 10 (3-4) ◽  
pp. 282-307
Author(s):  
Daria Shapovalova
Keyword(s):  
Climate Change ◽  
Emission Reduction ◽  
Large Scale ◽  
Fossil Fuel ◽  
Oil And Gas ◽  
The Arctic ◽  
Supply Side ◽  
Oil And Gas Development ◽  
Fossil Fuel Consumption ◽  
National Practice

Abstract The Arctic is both a place disproportionately affected by climate change and a place that has been, and continues to be, subject to large-scale oil-and-gas development. Production and subsequent combustion of these resources would compromise the treaty-established target of keeping global warming ‘well below’ 2°C. The global regulatory efforts on climate change are centred on greenhouse gas emissions from fossil-fuel consumption, almost ignoring the supply side. In the absence of universal and strict emission-reduction targets, petroleum exports and carbon leakage jeopardize the effectiveness of the climate change regime. Through the examination of treaties and national practice, this paper argues for the establishment of accountability for the production of Arctic petroleum in light of climate change.

scholarly journals Relationship of the brightness temperature anomalies of the lower troposphere with the climate indices on the Southern Urals

2019 ◽  
pp. 14-28
Author(s):  
D. Yu. Vasil’ev ◽  
N. V. Velikanov ◽  
V. V. Vodopyanov ◽  
N. N. Krasnogorskaya ◽  
V. A. Semenov ◽  
...  
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climatic Variability ◽  
Lower Troposphere ◽  
Southern Urals ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Indices ◽  
The Southern Urals ◽  
Sea Ice Concentration

This paper presents an analysis of the average monthly temperature of the lower troposphere (TLT) according to satellite sensing data for the period 1979–2017 in the Southern Urals. In order to study the space-time structure of TLT, the method of decomposition of the temperature series into empirical orthogonal components (EOC) was used. A correlation analysis of the link between the identified EOC for winter and summer seasons and indices of large-scale modes of natural climate variability in the Northern hemisphere was carried out. The first leading EOC, which describes a negative temperature trend, makes the major contribution to the overall variability. For winter, the leading mode is associated with the North Atlantic oscillation. For summer, a significant contribution of the Atlantic multi-decadal oscillation and the index of the Arctic sea ice concentration anomalies is revealed, which can be used to improve the reliability of the future scenarios of the regional climate change. The results suggest a significant impact of natural climatic variability on the temperature regime and a possible difficulty in identifying the anthropogenic component of climate change in the studied region.

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