VIII.—Burning Cliffs of the Banks of the Mackenzie River, etc

1908 ◽  
Vol 5 (12) ◽  
pp. 562-563
Author(s):  
H. W.
Keyword(s):  
Spontaneous Combustion ◽  
The Arctic ◽  
Carbonaceous Matter ◽  
Geological Age ◽  
Arctic Sea ◽  
Rupert's Land ◽  
Mackenzie River

As bearing upon the phenomenon of the spontaneous combustion of bituminous beds of coaly or carbonaceous matter of any geological age (charged with pyrites) in sitû, the account given by Sir John Richardson, C.B., F.R.S., in his “Arctic Searching Expedition; a Journal of a Boat-voyage through Rupert's Land and the Arctic Sea,” 1851, vol. i, may not be without interest in this connection.

scholarly journals Inorganic carbon dynamics of melt pond-covered first year sea ice in the Canadian Arctic

2014 ◽  
Vol 11 (5) ◽  
pp. 7485-7519 ◽  
Author(s):  
N.-X. Geilfus ◽  
R. J. Galley ◽  
O. Crabeck ◽  
T. Papakyriakou ◽  
J. Landy ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
First Year ◽  
Ice Melt ◽  
Melt Pond ◽  
Melt Ponds ◽  
Arctic Sea ◽  
Melt Water

Abstract. Melt pond formation is a common feature of the spring and summer Arctic sea ice. However, the role of the melt ponds formation and the impact of the sea ice melt on both the direction and size of CO2 flux between air and sea is still unknown. Here we describe the CO2-carbonate chemistry of melting sea ice, melt ponds and the underlying seawater associated with measurement of CO2 fluxes across first year landfast sea ice in the Resolute Passage, Nunavut, in June 2012. Early in the melt season, the increase of the ice temperature and the subsequent decrease of the bulk ice salinity promote a strong decrease of the total alkalinity (TA), total dissolved inorganic carbon (TCO2) and partial pressure of CO2 (pCO2) within the bulk sea ice and the brine. Later on, melt pond formation affects both the bulk sea ice and the brine system. As melt ponds are formed from melted snow the in situ melt pond pCO2 is low (36 μatm). The percolation of this low pCO2 melt water into the sea ice matrix dilutes the brine resulting in a strong decrease of the in situ brine pCO2 (to 20 μatm). As melt ponds reach equilibrium with the atmosphere, their in situ pCO2 increase (up to 380 μatm) and the percolation of this high concentration pCO2 melt water increase the in situ brine pCO2 within the sea ice matrix. The low in situ pCO2 observed in brine and melt ponds results in CO2 fluxes of −0.04 to −5.4 mmol m–2 d–1. As melt ponds reach equilibrium with the atmosphere, the uptake becomes less significant. However, since melt ponds are continuously supplied by melt water their in situ pCO2 still remains low, promoting a continuous but moderate uptake of CO2 (~ −1mmol m–2 d–1). The potential uptake of atmospheric CO2 by melting sea ice during the Arctic summer has been estimated from 7 to 16 Tg of C ignoring the role of melt ponds. This additional uptake of CO2 associated to Arctic sea ice needs to be further explored and considered in the estimation of the Arctic Ocean's overall CO2 budget.

scholarly journals Inorganic carbon dynamics of melt-pond-covered first-year sea ice in the Canadian Arctic

2015 ◽  
Vol 12 (6) ◽  
pp. 2047-2061 ◽  
Author(s):  
N.-X. Geilfus ◽  
R. J. Galley ◽  
O. Crabeck ◽  
T. Papakyriakou ◽  
J. Landy ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
First Year ◽  
Co2 Fluxes ◽  
Ice Melt ◽  
Melt Pond ◽  
Melt Ponds ◽  
Arctic Sea

Abstract. Melt pond formation is a common feature of spring and summer Arctic sea ice, but the role and impact of sea ice melt and pond formation on both the direction and size of CO2 fluxes between air and sea is still unknown. Here we report on the CO2–carbonate chemistry of melting sea ice, melt ponds and the underlying seawater as well as CO2 fluxes at the surface of first-year landfast sea ice in the Resolute Passage, Nunavut, in June 2012. Early in the melt season, the increase in ice temperature and the subsequent decrease in bulk ice salinity promote a strong decrease of the total alkalinity (TA), total dissolved inorganic carbon (TCO2) and partial pressure of CO2 (pCO2) within the bulk sea ice and the brine. As sea ice melt progresses, melt ponds form, mainly from melted snow, leading to a low in situ melt pond pCO2 (36 μatm). The percolation of this low salinity and low pCO2 meltwater into the sea ice matrix decreased the brine salinity, TA and TCO2, and lowered the in situ brine pCO2 (to 20 μatm). This initial low in situ pCO2 observed in brine and melt ponds results in air–ice CO2 fluxes ranging between −0.04 and −5.4 mmol m−2 day−1 (negative sign for fluxes from the atmosphere into the ocean). As melt ponds strive to reach pCO2 equilibrium with the atmosphere, their in situ pCO2 increases (up to 380 μatm) with time and the percolation of this relatively high concentration pCO2 meltwater increases the in situ brine pCO2 within the sea ice matrix as the melt season progresses. As the melt pond pCO2 increases, the uptake of atmospheric CO2 becomes less significant. However, since melt ponds are continuously supplied by meltwater, their in situ pCO2 remains undersaturated with respect to the atmosphere, promoting a continuous but moderate uptake of CO2 (~ −1 mmol m−2 day−1) into the ocean. Considering the Arctic seasonal sea ice extent during the melt period (90 days), we estimate an uptake of atmospheric CO2 of −10.4 Tg of C yr−1. This represents an additional uptake of CO2 associated with Arctic sea ice that needs to be further explored and considered in the estimation of the Arctic Ocean's overall CO2 budget.

STORM ICE OIL WIND WAVE WATCH SYSTEM (SIOWS): WEB GIS APPLICATION FOR MONITORING THE ARCTIC

2017 ◽  
Author(s):  
Alexander Myasoedov ◽  
Alexander Myasoedov ◽  
Sergey Azarov ◽  
Sergey Azarov ◽  
Ekaterina Balashova ◽  
...  
Keyword(s):  
Satellite Data ◽  
Wind Wave ◽  
Arctic Region ◽  
Web Gis ◽  
The Arctic ◽  
Flexible Tool ◽  
In Situ Data ◽  
Current State ◽  
Watch System

Working with satellite data, has long been an issue for users which has often prevented from a wider use of these data because of Volume, Access, Format and Data Combination. The purpose of the Storm Ice Oil Wind Wave Watch System (SIOWS) developed at Satellite Oceanography Laboratory (SOLab) is to solve the main issues encountered with satellite data and to provide users with a fast and flexible tool to select and extract data within massive archives that match exactly its needs or interest improving the efficiency of the monitoring system of geophysical conditions in the Arctic. SIOWS - is a Web GIS, designed to display various satellite, model and in situ data, it uses developed at SOLab storing, processing and visualization technologies for operational and archived data. It allows synergistic analysis of both historical data and monitoring of the current state and dynamics of the "ocean-atmosphere-cryosphere" system in the Arctic region, as well as Arctic system forecasting based on thermodynamic models with satellite data assimilation.

Prévoir les variations saisonnières de la glace de mer arctique et leurs impacts sur le climat

2020 ◽  
pp. 024
Author(s):  
Rym Msadek ◽  
Gilles Garric ◽  
Sara Fleury ◽  
Florent Garnier ◽  
Lauriane Batté ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
Climate Impacts ◽  
The Arctic ◽  
Recent Effort ◽  
Sea Ice Thickness ◽  
Arctic Sea ◽  
Ice Conditions ◽  
Upper Level

L'Arctique est la région du globe qui s'est réchauffée le plus vite au cours des trente dernières années, avec une augmentation de la température de surface environ deux fois plus rapide que pour la moyenne globale. Le déclin de la banquise arctique observé depuis le début de l'ère satellitaire et attribué principalement à l'augmentation de la concentration des gaz à effet de serre aurait joué un rôle important dans cette amplification des températures au pôle. Cette fonte importante des glaces arctiques, qui devrait s'accélérer dans les décennies à venir, pourrait modifier les vents en haute altitude et potentiellement avoir un impact sur le climat des moyennes latitudes. L'étendue de la banquise arctique varie considérablement d'une saison à l'autre, d'une année à l'autre, d'une décennie à l'autre. Améliorer notre capacité à prévoir ces variations nécessite de comprendre, observer et modéliser les interactions entre la banquise et les autres composantes du système Terre, telles que l'océan, l'atmosphère ou la biosphère, à différentes échelles de temps. La réalisation de prévisions saisonnières de la banquise arctique est très récente comparée aux prévisions du temps ou aux prévisions saisonnières de paramètres météorologiques (température, précipitation). Les résultats ayant émergé au cours des dix dernières années mettent en évidence l'importance des observations de l'épaisseur de la glace de mer pour prévoir l'évolution de la banquise estivale plusieurs mois à l'avance. Surface temperatures over the Arctic region have been increasing twice as fast as global mean temperatures, a phenomenon known as arctic amplification. One main contributor to this polar warming is the large decline of Arctic sea ice observed since the beginning of satellite observations, which has been attributed to the increase of greenhouse gases. The acceleration of Arctic sea ice loss that is projected for the coming decades could modify the upper level atmospheric circulation yielding climate impacts up to the mid-latitudes. There is considerable variability in the spatial extent of ice cover on seasonal, interannual and decadal time scales. Better understanding, observing and modelling the interactions between sea ice and the other components of the climate system is key for improved predictions of Arctic sea ice in the future. Running operational-like seasonal predictions of Arctic sea ice is a quite recent effort compared to weather predictions or seasonal predictions of atmospheric fields like temperature or precipitation. Recent results stress the importance of sea ice thickness observations to improve seasonal predictions of Arctic sea ice conditions during summer.

scholarly journals Retrieval of Snow Depth over Arctic Sea Ice Using a Deep Neural Network

2019 ◽  
Vol 11 (23) ◽  
pp. 2864 ◽  
Author(s):  
Jiping Liu ◽  
Yuanyuan Zhang ◽  
Xiao Cheng ◽  
Yongyun Hu
Keyword(s):  
Neural Network ◽  
Sea Ice ◽  
Snow Depth ◽  
Deep Neural Network ◽  
Arctic Basin ◽  
Temporal Variations ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Thickness ◽  
Arctic Sea

The accurate knowledge of spatial and temporal variations of snow depth over sea ice in the Arctic basin is important for understanding the Arctic energy budget and retrieving sea ice thickness from satellite altimetry. In this study, we develop and validate a new method for retrieving snow depth over Arctic sea ice from brightness temperatures at different frequencies measured by passive microwave radiometers. We construct an ensemble-based deep neural network and use snow depth measured by sea ice mass balance buoys to train the network. First, the accuracy of the retrieved snow depth is validated with observations. The results show the derived snow depth is in good agreement with the observations, in terms of correlation, bias, root mean square error, and probability distribution. Our ensemble-based deep neural network can be used to extend the snow depth retrieval from first-year sea ice (FYI) to multi-year sea ice (MYI), as well as during the melting period. Second, the consistency and discrepancy of snow depth in the Arctic basin between our retrieval using the ensemble-based deep neural network and two other available retrievals using the empirical regression are examined. The results suggest that our snow depth retrieval outperforms these data sets.

scholarly journals Observation-based selection of climate models projects Arctic ice-free summers around 2035

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Arctic Sea ◽  
Area And Volume

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.

scholarly journals Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models

2021 ◽  
Vol 13 (5) ◽  
pp. 831
Author(s):  
Jorge Vazquez-Cuervo ◽  
Chelle Gentemann ◽  
Wenqing Tang ◽  
Dustin Carroll ◽  
Hong Zhang ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Future Research ◽  
Surface Salinity ◽  
Cold Temperatures ◽  
Yukon River ◽  
Arctic Sea ◽  
The Arctic Ocean

The Arctic Ocean is one of the most important and challenging regions to observe—it experiences the largest changes from climate warming, and at the same time is one of the most difficult to sample because of sea ice and extreme cold temperatures. Two NASA-sponsored deployments of the Saildrone vehicle provided a unique opportunity for validating sea-surface salinity (SSS) derived from three separate products that use data from the Soil Moisture Active Passive (SMAP) satellite. To examine possible issues in resolving mesoscale-to-submesoscale variability, comparisons were also made with two versions of the Estimating the Circulation and Climate of the Ocean (ECCO) model (Carroll, D; Menmenlis, D; Zhang, H.). The results indicate that the three SMAP products resolve the runoff signal associated with the Yukon River, with high correlation between SMAP products and Saildrone SSS. Spectral slopes, overall, replicate the −2.0 slopes associated with mesoscale-submesoscale variability. Statistically significant spatial coherences exist for all products, with peaks close to 100 km. Based on these encouraging results, future research should focus on improving derivations of satellite-derived SSS in the Arctic Ocean and integrating model results to complement remote sensing observations.

scholarly journals Polar cod in jeopardy under the retreating Arctic sea ice

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Mats Brockstedt Olsen Huserbråten ◽  
Elena Eriksen ◽  
Harald Gjøsæter ◽  
Frode Vikebø
Keyword(s):  
Sea Ice ◽  
Barents Sea ◽  
Keystone Species ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Biophysical Model ◽  
The Arctic ◽  
Polar Cod ◽  
Arctic Sea ◽  
Shelf Sea

Abstract The Arctic amplification of global warming is causing the Arctic-Atlantic ice edge to retreat at unprecedented rates. Here we show how variability and change in sea ice cover in the Barents Sea, the largest shelf sea of the Arctic, affect the population dynamics of a keystone species of the ice-associated food web, the polar cod (Boreogadus saida). The data-driven biophysical model of polar cod early life stages assembled here predicts a strong mechanistic link between survival and variation in ice cover and temperature, suggesting imminent recruitment collapse should the observed ice-reduction and heating continue. Backtracking of drifting eggs and larvae from observations also demonstrates a northward retreat of one of two clearly defined spawning assemblages, possibly in response to warming. With annual to decadal ice-predictions under development the mechanistic physical-biological links presented here represent a powerful tool for making long-term predictions for the propagation of polar cod stocks.

scholarly journals An exemplary case of a bromine explosion event linked to cyclone development in the Arctic

2016 ◽  
Vol 16 (3) ◽  
pp. 1773-1788 ◽  
Author(s):  
A.-M. Blechschmidt ◽  
A. Richter ◽  
J. P. Burrows ◽  
L. Kaleschke ◽  
K. Strong ◽  
...  
Keyword(s):  
Numerical Models ◽  
Weather Conditions ◽  
Conveyor Belt ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Blowing Snow ◽  
Air Stream ◽  
Combined Use ◽  
Arctic Sea ◽  
Development Duration

Abstract. Intense, cyclone-like shaped plumes of tropospheric bromine monoxide (BrO) are regularly observed by GOME-2 on board the MetOp-A satellite over Arctic sea ice in polar spring. These plumes are often transported by high-latitude cyclones, sometimes over several days despite the short atmospheric lifetime of BrO. However, only few studies have focused on the role of polar weather systems in the development, duration and transport of tropospheric BrO plumes during bromine explosion events. The latter are caused by an autocatalytic chemical chain reaction associated with tropospheric ozone depletion and initiated by the release of bromine from cold brine-covered ice or snow to the atmosphere. In this manuscript, a case study investigating a comma-shaped BrO plume which developed over the Beaufort Sea and was observed by GOME-2 for several days is presented. By making combined use of satellite data and numerical models, it is shown that the occurrence of the plume was closely linked to frontal lifting in a polar cyclone and that it most likely resided in the lowest 3 km of the troposphere. In contrast to previous case studies, we demonstrate that the dry conveyor belt, a potentially bromine-rich stratospheric air stream which can complicate interpretation of satellite retrieved tropospheric BrO, is spatially separated from the observed BrO plume. It is concluded that weather conditions associated with the polar cyclone favoured the bromine activation cycle and blowing snow production, which may have acted as a bromine source during the bromine explosion event.

Sign in / Sign up

Export Citation Format

Share Document