scholarly journals Brief Communication: Does it matter exactly when the Arctic will become ice-free?

2016 ◽  
Author(s):  
J. K. Ridley ◽  
R. A. Wood ◽  
A. B. Keen ◽  
E. Blockley ◽  
J. A. Lowe
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Climate Change Mitigation ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
The Public ◽  
Arctic Sea ◽  
Definition Of ◽  
Dangerous Climate Change ◽  
Change Mitigation

Abstract. Following the 2015 UNFCCC Conference of Parties in Paris there is renewed interest in understanding and avoiding potentially dangerous climate change. The loss of Arctic sea ice is one of the most directly visible aspects of climate change and the question is frequently asked: when can we expect the Arctic to be ice-free in summer? We argue here that this question may not be the most useful one to inform decisions on climate change mitigation or adaptation in the Arctic. The development of a community-wide consensus on a robust definition of "ice-free", may reduce confusion in the community and amongst the public.

scholarly journals Arctic Sea Ice’s Amplification as a Complement to Anthropogenic Global Warming

2021 ◽  
Author(s):  
Marco Morando
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Future Climate Change ◽  
Number Count ◽  
Anthropogenic Global Warming ◽  
Arctic Sea ◽  
Scientific Subject

Abstract Climate Change is a widely debated scientific subject and Anthropogenic Global Warming is its main cause. Nevertheless, several authors have indicated solar activity and Atlantic Multi-decadal Oscillation variations may also influence Climate Change. This article considers the amplification of solar radiation’s and Atlantic Multi-decadal Oscillation’s variations, via sea ice cover albedo feedbacks in the Arctic regions, providing a conceptual advance in the application of Arctic Amplification for modelling historical climate change. A 1-dimensional physical model, using sunspot number count and Atlantic Multi-decadal Oscillation index as inputs, can simulate the average global temperature’s anomaly and the Arctic Sea Ice Extension for the past eight centuries. This model represents an innovative progress in understanding how existing studies on Arctic sea ice’s albedo feedbacks can help complementing the Anthropogenic Global Warming models, thus helping to define more precise models for future climate change.

Early Holocene history of the Zachariae Ice Stream, NE Greenland: Evidence from geochemistry, grain size and sedimentary parameters

2020 ◽  
Author(s):  
Joanna Davies ◽  
Anders Møller Mathiase ◽  
Christof Pearce ◽  
Marit-Solveig Seidenkrantz
Keyword(s):  
Climate Change ◽  
Grain Size ◽  
Sea Ice ◽  
Surface Waters ◽  
Arctic Sea Ice ◽  
Early Holocene ◽  
The Arctic ◽  
Cold Surface ◽  
Sea Ice Extent ◽  
Arctic Sea

<p>The Arctic region exhibits some of the most visible signs of climate change globally. Arctic sea ice extent and volume has been declining sharply in recent decades; observations indicate a mean annual decrease of 3.2% since 1980. However, no extensive network of sea ice observations extends back further than the mid-18<sup>th</sup> century and satellite data since the late 1970s; this limits perspectives of sea ice variability on longer time scales. Thus, to understand the processes governing sea-ice cover and variability, predict how sea ice and ocean conditions will respond to anthropogenic climate change and to understand if the shrinking of Arctic sea ice is a unique and irreversible process, longer records of sea ice variability and oceanic conditions are required.</p><p>A multi-proxy approach, involving grain size, geochemical, foraminifera and sedimentary analysis, was applied to a marine sediment core from North East Greenland to reconstruct changes in sea ice extent and palaeoceanographic conditions throughout the early Holocene (ca. 12,400-7,800 cal. yrs. BP). The study aimed to improve the understanding of the interaction between ocean circulation, sea ice and fluctuations of the Zachariae Isstrøm (ZI), one of the main glacier outlets of NE Greenland. Four distinct zones have been identified: Zone 1 (12,400-11,600 cal. yrs. BP) covering the transition from the Younger Dryas into the Holocene which evidences a gradually warming climate, resulting in a retreat of the ZI; Zone 2 (11,600 – 10,300 cal. yrs. BP) which encapsulates two distinct cooling events as a result of cooler surface waters, rapid release of freshwater and local feedback mechanisms. This coincides with sudden re-advances of the ZI followed by gradual retreats; 3) Zone 3 (10,300 – 8,600 cal. yrs. BP) shows warm and stable conditions, with warm surface waters that resulted in the retreat of the ZI; 4) Zone 4 (8,600 – 7,800 cal. yrs. BP) which shows a rapid return to cooler conditions, with cold surface waters and rapid freshwater outbursts resulting in the re-advance of the ZI, forced by decreasing solar insolation and cold surface waters. Our investigation thus indicated that changes in oceanic conditions at the NE Greenland shelf had a significant impact on the extent and melting rate of the ZI glacier.</p>

Linkage between Arctic Sea Ice Area and Atmospheric Blocking Probability over Europe using Logistic Regression Models

2021 ◽  
Author(s):  
Andy Richling ◽  
Uwe Ulbrich ◽  
Henning Rust ◽  
Johannes Riebold ◽  
Dörthe Handorf
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Regression Models ◽  
Arctic Sea Ice ◽  
Arctic Climate ◽  
The Arctic ◽  
Atmospheric Blocking ◽  
Logistic Regression Models ◽  
Arctic Sea ◽  
Arctic Climate Change

<p>Over the last decades the Arctic climate change has been observed with a much faster warming of the Arctic compared to the global average (Arctic amplification) and related sea-ice retreat. These changes in sea ice can affect the large-scale atmospheric circulation over the mid-latitudes, in particular atmospheric blocking, and thus the frequency and severity of extreme events. As a step towards a better understanding of changes in weather and climate extremes over Central Europe associated with Arctic climate change, we first analyze the linkage between recent Arctic sea ice loss and blocking variability using logistic regression models. ERA5 reanalysis data are used on a monthly and seasonal time scale, and specific regional sea ice variabilities are explored. First results indicate an increased occurrence-probability in terms of blocking frequency over Greenland in summer as well as over Scandinavia/Ural in winter during low sea ice conditions. </p>

Voices of the Sea Ice: engaging an Arctic community to communicate impacts of climate change

2020 ◽  
Author(s):  
David Lipson ◽  
Kim Reasor ◽  
Kååre Sikuaq Erickson
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Digital Version ◽  
Sea Ice Decline ◽  
Arctic Sea ◽  
The World ◽  
Impacts Of Climate Change

<p>The predominantly Inupiat people of Utqiaġvik, Alaska are among those who will be most impacted by<br>climate change and the loss of Arctic sea ice in the near future. Subsistence hunting of marine mammals<br>associated with sea ice is central to the Inupiat way of life. Furthermore, their coastal homes and<br>infrastructure are increasingly subject to damage from increased wave action on ice-free Beaufort and<br>Chukchi Seas. While the people of this region are among the most directly vulnerable to climate change,<br>the subject is not often discussed in the elementary school curriculum. Meanwhile, in many other parts<br>of the world, the impacts of climate change are viewed as abstract and remote. We worked with fifth<br>grade children in Utqiaġvik both to educate them, but also to engage them in helping us communicate<br>to rest of the world, in an emotionally resonant way, the direct impacts of climate change on families in<br>this Arctic region.<br>The team consisted of a scientist (Lipson), an artist (Reasor) and an outreach specialist (Erickson) of<br>Inupiat heritage from a village in Alaska. We worked with four 5th grade classes of about 25 students<br>each at Fred Ipalook Elementary in Utqiaġvik, AK. The scientist gave a short lecture about sea ice and<br>climate change in the Arctic, with emphasis on local impacts to hunting and infrastructure (with<br>interjections from the local outreach specialist). We then showed the students a large poster of<br>historical and projected sea ice decline, and asked the students to help us fill in the white space beneath<br>the lines. The artist led the children in making small art pieces that represent things that are important<br>to their lives in Utqiaġvik (they were encouraged to paint animals, but they were free to do whatever<br>they wanted). We returned to the class later that week and had each student briefly introduce<br>themselves and their painting, and place it to the large graph of sea ice decline, which included the dire<br>predictions of the RCP8.5 scenario. At the end we added the more hopeful RCP2.6 scenario to end on a<br>positive note. The artist then painted in the more hopeful green line by hand.<br>The result was a poster showing historical and projected Arctic sea ice cover, with 100 beautiful<br>paintings by children of things that are dear to them about their home being squeezed into a smaller<br>region as the sea ice cover diminishes. We scanned all the artwork to make a digital version of the<br>poster, and left the original with the school. These materials are being converted into an interactive<br>webpage where viewers can click on the individual painting for detail, and get selected recordings of the<br>children’s statements about their artwork. This project can serve as a nucleus for communicating to<br>other classes and adults about the real impacts of climate change in people’s lives.</p>

Deep learning for monthly Arctic sea ice concentration prediction

2020 ◽  
Author(s):  
Tom Andersson ◽  
Fruzsina Agocs ◽  
Scott Hosking ◽  
María Pérez-Ortiz ◽  
Brooks Paige ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Deep Learning ◽  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Prediction System ◽  
Sea Ice Concentration ◽  
Arctic Sea ◽  
Ice Concentration

<p>Over recent decades, the Arctic has warmed faster than any region on Earth. The rapid decline in Arctic sea ice extent (SIE) is often highlighted as a key indicator of anthropogenic climate change. Changes in sea ice disrupt Arctic wildlife and indigenous communities, and influence weather patterns as far as the mid-latitudes. Furthermore, melting sea ice attenuates the albedo effect by replacing the white, reflective ice with dark, heat-absorbing melt ponds and open sea, increasing the Sun’s radiative heat input to the Arctic and amplifying global warming through a positive feedback loop. Thus, the reliable prediction of sea ice under a changing climate is of both regional and global importance. However, Arctic sea ice presents severe modelling challenges due to its complex coupled interactions with the ocean and atmosphere, leading to high levels of uncertainty in numerical sea ice forecasts.</p><p>Deep learning (a subset of machine learning) is a family of algorithms that use multiple nonlinear processing layers to extract increasingly high-level features from raw input data. Recent advances in deep learning techniques have enabled widespread success in diverse areas where significant volumes of data are available, such as image recognition, genetics, and online recommendation systems. Despite this success, and the presence of large climate datasets, applications of deep learning in climate science have been scarce until recent years. For example, few studies have posed the prediction of Arctic sea ice in a deep learning framework. We investigate the potential of a fully data-driven, neural network sea ice prediction system based on satellite observations of the Arctic. In particular, we use inputs of monthly-averaged sea ice concentration (SIC) maps since 1979 from the National Snow and Ice Data Centre, as well as climatological variables (such as surface pressure and temperature) from the European Centre for Medium-Range Weather Forecasts reanalysis (ERA5) dataset. Past deep learning-based Arctic sea ice prediction systems tend to overestimate sea ice in recent years - we investigate the potential to learn the non-stationarity induced by climate change with the inclusion of multi-decade global warming indicators (such as average Arctic air temperature). We train the networks to predict SIC maps one month into the future, evaluating network prediction uncertainty by ensembling independent networks with different random weight initialisations. Our model accounts for seasonal variations in the drivers of sea ice by controlling for the month of the year being predicted. We benchmark our prediction system against persistence, linear extrapolation and autoregressive models, as well as September minimum SIE predictions from submissions to the Sea Ice Prediction Network's Sea Ice Outlook. Performance is evaluated quantitatively using the root mean square error and qualitatively by analysing maps of prediction error and uncertainty.</p>

scholarly journals Insignificant effect of climate change on winter haze pollution in Beijing

2018 ◽  
Vol 18 (23) ◽  
pp. 17489-17496 ◽  
Author(s):  
Lu Shen ◽  
Daniel J. Jacob ◽  
Loretta J. Mickley ◽  
Yuxuan Wang ◽  
Qiang Zhang
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
21St Century ◽  
Climate Models ◽  
Eastern China ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Projections ◽  
Haze Pollution ◽  
Arctic Sea

Abstract. Several recent studies have suggested that 21st century climate change will significantly worsen the meteorological conditions, leading to very high concentrations of fine particulate matter (PM2.5) in Beijing in winter (Beijing haze). We find that 81 % of the variance in observed monthly PM2.5 during 2010–2017 winters can be explained by a single meteorological mode, the first principal component (PC1) of the 850 hPa meridional wind velocity (V850) and relative humidity (RH). V850 and RH drive stagnation and chemical production of PM2.5, respectively, and thus have a clear causal link to Beijing haze. PC1 explains more of the variance in PM2.5 than either V850 or RH alone. Using additional meteorological variables does not explain more of the variance in PM2.5. Therefore PC1 can serve as a proxy for Beijing haze in the interpretation of long-term climate records and in future climate projections. Previous studies suggested that shrinking Arctic sea ice would worsen winter haze conditions in eastern China, but we show with the PC1 proxy that Beijing haze is correlated with a dipole structure in the Arctic sea ice rather than with the total amount of sea ice. Beijing haze is also correlated with dipole patterns in Pacific sea surface temperatures (SSTs). We find that these dipole patterns of Arctic sea ice and Pacific SSTs shift and change sign on interdecadal scales, so that they cannot be used reliably as future predictors for the haze. Future 21st century trends of the PC1 haze proxy computed from the CMIP5 ensemble of climate models are statistically insignificant. We conclude that climate change is unlikely to significantly offset current efforts to decrease Beijing haze through emission controls.

Changes in Lake Area in the Inner Mongolian Plateau under Climate Change: The Role of the Atlantic Multidecadal Oscillation and Arctic Sea Ice

2020 ◽  
Vol 33 (4) ◽  
pp. 1335-1349
Author(s):  
Yong Liu ◽  
Huopo Chen ◽  
Guoqing Zhang ◽  
Jianqi Sun ◽  
Hua Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Summer Precipitation ◽  
Atlantic Multidecadal Oscillation ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Lake Area ◽  
Mongolian Plateau ◽  
Arctic Sea

AbstractThe lake area in the Inner Mongolian Plateau (IMP) has experienced a rapid reduction in recent decades. Previous studies have highlighted the important role of intensive human activities in IMP lake shrinkage. However, this study found that climate change–induced summer precipitation variations can exert great influences on the IMP lake area variations. The results suggest that the decadal shift in the IMP summer precipitation may be the predominant contributor to lake shrinkage. Further analysis reveals that the Atlantic multidecadal oscillation (AMO) and Arctic sea ice concentration (SIC) play important roles in the IMP summer precipitation variations. The AMO seems to provide beneficial large-scale circulation fields for the decadal variations in the IMP summer precipitation, and the Arctic SIC decline is favorable for weakening the IMP summer precipitation intensity after the late 1990s. Evidence indicates that the vorticity advection related to the Arctic SIC decline can result in the generation of Rossby wave resources in the midlatitudes. Then, the strengthened wave resources become favorable for enhancing the stationary wave propagation across Eurasia and inducing cyclonic circulation over the Mongolia–Baikal regions, which might bring more rainfall northward and weaken the IMP summer precipitation intensity. Consequently, due to the decreased rainfall and gradual warming after the late 1990s, the lake area in the IMP has experienced a downward trend in recent years.

scholarly journals Atmospheric feedback explains disparate climate response to regional Arctic sea-ice loss

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Xavier J. Levine ◽  
Ivana Cvijanovic ◽  
Pablo Ortega ◽  
Markus G. Donat ◽  
Etienne Tourigny
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Sea Ice ◽  
Feedback Mechanism ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Response ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss ◽  
Atmospheric Feedback

AbstractArctic sea-ice loss is a consequence of anthropogenic global warming and can itself be a driver of climate change in the Arctic and at lower latitudes, with sea-ice minima likely favoring extreme events over Europe and North America. Yet the role that the sea-ice plays in ongoing climate change remains uncertain, partly due to a limited understanding of whether and how the exact geographical distribution of sea-ice loss impacts climate. Here we demonstrate that the climate response to sea-ice loss can vary widely depending on the pattern of sea-ice change, and show that this is due to the presence of an atmospheric feedback mechanism that amplifies the local and remote signals when broader scale sea-ice loss occurs. Our study thus highlights the need to better constrain the spatial pattern of future sea-ice when assessing its impacts on the climate in the Arctic and beyond.

scholarly journals Evolution of the Global Coupled Climate Response to Arctic Sea Ice Loss during 1990–2090 and Its Contribution to Climate Change

2018 ◽  
Vol 31 (19) ◽  
pp. 7823-7843 ◽  
Author(s):  
Lantao Sun ◽  
Michael Alexander ◽  
Clara Deser
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Sea Ice ◽  
Surface Temperature ◽  
Atmospheric Circulation ◽  
Arctic Sea Ice ◽  
Meridional Overturning Circulation ◽  
The Arctic ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

The role of transient Arctic sea ice loss in the projected greenhouse gas–induced late-twentieth- to late-twenty-first-century climate change is investigated using the Geophysical Fluid Dynamics Laboratory’s Coupled Model version 3. Two sets of simulations have been conducted, one with representative concentration pathway (RCP) 8.5 radiative forcing and the second with RCP forcing but with Arctic sea ice nudged to its 1990 state. The difference between the two five-member sets indicates the influence of decreasing Arctic sea ice on the climate system. Within the Arctic, sea ice loss is found to be a primary driver of the surface temperature and precipitation changes. Arctic sea ice depletion also plays a dominant role in projected Atlantic meridional overturning circulation weakening and changes in North Atlantic extratropical sea surface temperature and salinity, especially in the first half century. The effect of present-day Arctic sea ice loss on Northern Hemisphere (NH) extratropical atmospheric circulation is small relative to internal variability and the future sea ice loss effect on atmospheric circulation is distinct from the projected anthropogenic change. Arctic sea ice loss warms NH extratropical continents and is an important contributor to global warming not only over high latitudes but also in the eastern United States. Last, the Arctic sea ice loss displaces the Pacific intertropical convergence zone (ITCZ) equatorward and induces a “mini-global warming” in the tropical upper troposphere.

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