scholarly journals An energy budget approach to understand the Arctic warming during the Last Interglacial

2021 ◽  
Author(s):  
Marie Sicard ◽  
Masa Kageyama ◽  
Sylvie Charbit ◽  
Pascale Braconnot ◽  
Jean-Baptiste Madeleine
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Air Temperature ◽  
Energy Budget ◽  
Surface Air Temperature ◽  
The Arctic ◽  
Last Interglacial ◽  
Near Surface ◽  
Arctic Warming ◽  
The Arctic Ocean

Abstract. The Last Interglacial period (129–116 ka BP) is characterized by a strong orbital forcing which leads to a different seasonal and latitudinal distribution of insolation compared to the pre-industrial period. In particular, these changes amplify the seasonality of the insolation in the high latitudes of the northern hemisphere. Here, we investigate the Arctic climate response to this forcing by comparing the CMIP6 lig127k and pi-Control simulations performed with the IPSL-CM6A-LR model. Using an energy budget framework, we analyse the interactions between the atmosphere, ocean, sea ice and continents. In summer, the insolation anomaly reaches its maximum and causes a near-surface air temperature rise of 3.2 °C over the Arctic region. This warming is primarily due to a strong positive surface downwelling shortwave radiation anomaly over continental surfaces, followed by large heat transfers from the continents back to the atmosphere. The surface layers of the Arctic Ocean also receives more energy, but in smaller quantity than the continents due to a cloud negative feedback. Furthermore, while heat exchanges from the continental surfaces towards the atmosphere are strengthened, the ocean absorbs and stores the heat excess due to a decline in sea ice cover. However, the maximum near-surface air temperature anomaly does not peak in summer like insolation, but occurs in autumn with a temperature increase of 4.0 °C relative to the pre-industrial period. This strong warming is driven by a positive anomaly of longwave radiations over the Arctic ocean enhanced by a positive cloud feedback. It is also favoured by the summer and autumn Arctic sea ice retreat (−1.9 × 106 and −3.4 × 106 km2 respectively), which exposes the warm oceanic surface and allows heat stored by the ocean in summer and water vapour to be released. This study highlights the crucial role of the sea ice cover variations, the Arctic ocean, as well as changes in polar clouds optical properties on the Last Interglacial Arctic warming.

Importance of Human-Induced Nitrogen Flux Increases for Simulated Arctic Warming

2021 ◽  
Vol 34 (10) ◽  
pp. 3799-3819
Author(s):  
Hyung-Gyu Lim ◽  
Jong-Yeon Park ◽  
John P. Dunne ◽  
Charles A. Stock ◽  
Sung-Ho Kang ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
The Arctic ◽  
Biogeochemical Model ◽  
Biological Feedback ◽  
Arctic Warming ◽  
The Arctic Ocean ◽  
N Fluxes ◽  
The Impact ◽  
Chlorophyll Concentrations

AbstractHuman activities such as fossil fuel combustion, land-use change, nitrogen (N) fertilizer use, emission of livestock, and waste excretion accelerate the transformation of reactive N and its impact on the marine environment. This study elucidates that anthropogenic N fluxes (ANFs) from atmospheric and river deposition exacerbate Arctic warming and sea ice loss via physical–biological feedback. The impact of physical–biological feedback is quantified through a suite of experiments using a coupled climate–ocean–biogeochemical model (GFDL-CM2.1-TOPAZ) by prescribing the preindustrial and contemporary amounts of riverine and atmospheric N fluxes into the Arctic Ocean. The experiment forced by ANFs represents the increase in ocean N inventory and chlorophyll concentrations in present and projected future Arctic Ocean relative to the experiment forced by preindustrial N flux inputs. The enhanced chlorophyll concentrations by ANFs reinforce shortwave attenuation in the upper ocean, generating additional warming in the Arctic Ocean. The strongest responses are simulated in the Eurasian shelf seas (Kara, Barents, and Laptev Seas; 65°–90°N, 20°–160°E) due to increased N fluxes, where the annual mean surface temperature increase by 12% and the annual mean sea ice concentration decrease by 17% relative to the future projection, forced by preindustrial N inputs.

Sea Ice Enhancements to Polar WRF*

2015 ◽  
Vol 143 (6) ◽  
pp. 2363-2385 ◽  
Author(s):  
Keith M. Hines ◽  
David H. Bromwich ◽  
Lesheng Bai ◽  
Cecilia M. Bitz ◽  
Jordan G. Powers ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Snow Depth ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Surface Model ◽  
Sea Ice Thickness ◽  
Near Surface ◽  
The Arctic Ocean

Abstract The Polar Weather Research and Forecasting Model (Polar WRF), a polar-optimized version of the WRF Model, is developed and made available to the community by Ohio State University’s Polar Meteorology Group (PMG) as a code supplement to the WRF release from the National Center for Atmospheric Research (NCAR). While annual NCAR official releases contain polar modifications, the PMG provides very recent updates to users. PMG supplement versions up to WRF version 3.4 include modified Noah land surface model sea ice representation, allowing the specification of variable sea ice thickness and snow depth over sea ice rather than the default 3-m thickness and 0.05-m snow depth. Starting with WRF V3.5, these options are implemented by NCAR into the standard WRF release. Gridded distributions of Arctic ice thickness and snow depth over sea ice have recently become available. Their impacts are tested with PMG’s WRF V3.5-based Polar WRF in two case studies. First, 20-km-resolution model results for January 1998 are compared with observations during the Surface Heat Budget of the Arctic Ocean project. Polar WRF using analyzed thickness and snow depth fields appears to simulate January 1998 slightly better than WRF without polar settings selected. Sensitivity tests show that the simulated impacts of realistic variability in sea ice thickness and snow depth on near-surface temperature is several degrees. The 40-km resolution simulations of a second case study covering Europe and the Arctic Ocean demonstrate remote impacts of Arctic sea ice thickness on midlatitude synoptic meteorology that develop within 2 weeks during a winter 2012 blocking event.

scholarly journals Light-absorbing impurities in Arctic snow

2010 ◽  
Vol 10 (8) ◽  
pp. 18807-18878 ◽  
Author(s):  
S. J. Doherty ◽  
S. G. Warren ◽  
T. C. Grenfell ◽  
A. D. Clarke ◽  
R. E. Brandt
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Greenland Ice Sheet ◽  
Surface Energy Budget ◽  
The Arctic ◽  
Arctic Canada ◽  
Near Surface ◽  
Near Ultraviolet ◽  
The Arctic Ocean ◽  
Snow Samples

Abstract. Absorption of radiation by ice is extremely weak at visible and near-ultraviolet wavelengths, so small amounts of light-absorbing impurities in snow can dominate the absorption of solar radiation at these wavelengths, reducing the albedo relative to that of pure snow, contributing to the surface energy budget and leading to earlier snowmelt. In this study Arctic snow is surveyed for its content of light-absorbing impurities, expanding and updating the 1983–1984 survey of Clarke and Noone. Samples were collected in Alaska, Canada, Greenland, Svalbard, Norway, Russia, and the Arctic Ocean during 2005–2009, on tundra, glaciers, ice caps, sea ice, frozen lakes, and in boreal forests. Snow was collected mostly in spring, when the entire winter snowpack is accessible for sampling. Sampling was carried out in summer on the Greenland ice sheet and on the Arctic Ocean, of melting glacier snow and sea ice as well as cold snow. About 1200 snow samples have been analyzed for this study. The snow is melted and filtered; the filters are analyzed in a specially designed spectrophotometer system to infer the concentration of black carbon (BC), the fraction of absorption due to non-BC light-absorbing constituents and the absorption Ångstrom exponent of all particles. The reduction of snow albedo is primarily due to BC, but other impurities, principally brown (organic) carbon, are typically responsible for ~40% of the visible and ultraviolet absorption. The meltwater from selected snow samples was saved for chemical analysis to identify sources of the impurities. Median BC amounts in surface snow are as follows (nanograms of carbon per gram of snow): Greenland 3, Arctic Ocean snow 7, melting sea ice 8, Arctic Canada 8, Subarctic Canada 14, Svalbard 13, Northern Norway 21, Western Arctic Russia 26, Northeastern Siberia 17. Concentrations are more variable in the European Arctic than in Arctic Canada or the Arctic Ocean, probably because of the proximity to BC sources. Individual samples of falling snow were collected on Svalbard, documenting the springtime decline of BC from March through May. Absorption Ångstrom exponents are 1.5–1.7 in Norway, Svalbard, and Western Russia, 2.1–2.3 elsewhere in the Arctic, and 2.5 in Greenland. Correspondingly, the estimated contribution to absorption by non-BC constituents in these regions is ~25%, 40%, and 50%, respectively. It has been hypothesized that when the snow surface layer melts some of the BC is left at the top of the snowpack rather than being carried away in meltwater. This process was observed in a few locations and would cause a positive feedback on snowmelt. The BC content of the Arctic atmosphere has declined markedly since 1989, according to the continuous measurements of near-surface air at Alert (Canada), Barrow (Alaska), and Ny-Ålesund (Svalbard). Correspondingly, the new BC concentrations for Arctic snow are somewhat lower than those reported by Clarke and Noone for 1983–1984, but because of methodological differences it is not clear that the differences are significant.

A multi-model CMIP6 study of Arctic sea ice at 127 ka: Sea ice data compilation and model differences

2020 ◽  
Author(s):  
Louise Sime ◽  
Masa Kageyama ◽  
Marie Sicard ◽  
Maria-Vittoria Guarino ◽  
Anne de Vernal ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Modelling ◽  
Last Interglacial ◽  
Nordic Seas ◽  
Arctic Sea ◽  
The Arctic Ocean ◽  
Intercomparison Project

<p>The Last interglacial (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models’ representation of climate reconstructions is one of the objectives set up by the Paleoclimate Modelling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 12 climate models in terms of Arctic sea ice. The mean pre-industrial to LIG reduction in minimum sea ice area (SIA) reaches 59% (multi-model mean LIG area is 2.21 mill. km2, compared to 5.85 mill. km2 for the PI), and the range of model results for LIG minimum sea ice area (from 0.02 to 5.65 mill. km2) is larger than for PI (from 4.10 to 8.30 mill. km2). On the other hand there is little change for the maximum sea ice area (which is 12 mill. km2 for both the PI and the LIG, with a standard deviation of 1.04 mill. km2 for PI and 1.21 mill. km2 for LIG). To evaluate the model results we synthesize LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. South of 78<sup>o</sup>N, in the Atlantic and Nordic seas, the LIG was seasonally ice-free. North of 78<sup>o</sup>N there are some discrepancies between sea ice reconstructions based on dinocysts/foraminifers/ostracods and IP25: some sites have both seasonal and perennial interpretations based on the same core, but different indicators. Because of the conflicting interpretations it is not possible for any one model to match every data point in our data synthesis, or say whether the Arctic was seasonally ice-free. Drivers for the inter-model differences are: different phasing of the up and down short-wave anomalies over the Arctic ocean, associated with differences in model albedo; possible cloud property differences, in terms of optical depth; LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally we note that inter-comparisons between the LIG simulations, and simulations with moderate CO2 increase (during the transition to high CO2 levels), may yield insight into likely 21C Arctic sea ice changes using these LIG simulations.</p>

scholarly journals “Atlantification” as a Possible Cause for Reducing of the Sea-Ice Cover in the Nansen Basin in winter

2018 ◽  
Vol 64 (1) ◽  
pp. 42-54 ◽  
Author(s):  
P. V. Aksenov ◽  
V. V. Ivanov
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Thermal Convection ◽  
Salt Content ◽  
Hydrological Regime ◽  
The Arctic ◽  
Time Interval ◽  
Ocean Reanalysis ◽  
Near Surface ◽  
The Arctic Ocean

The paper presents arguments in favor of an explanation of the reduction of the ice-covered area in the Nansen basin of the Arctic Ocean (AO) in winter by the so-called “atlantification “ — the strengthening of the influence of waters of Atlantic origin on the hydrological regime of the Arctic Ocean. We hypothesize that the main agent of “atlantification” in theWesternNansenBasinis winter thermal convection, which delivers heat from the deep to the upper mixed layer, thus melting sea ice and warming the near-surface air. To check up this hypothesis we used ocean reanalysis MERCATOR data for time interval 2007–2017. The quantitative criterion of thermal convection, based on the type of vertical thermohaline structure in the upper ocean layer, was applied to access the change of convection depth between climatic values in 1950–1990 and the present time. The main conclusion of the paper can be summarized as the following. Due to a gradual reduction of sea ice in the 1990s, the vertical stratification of waters in theWesternNansenBasinhas changed. As a result, the potential for penetration of vertical thermal convection into the warm and saline Atlantic layer and the consumption of heat and salt content of this layer for warming and salinification of the overlying waters increased, thus leading to additional loss of sea ice in winter.

scholarly journals Rotas marítimas no Ártico / Arctic sea routes

2017 ◽  
Vol 27 (51) ◽  
pp. 748
Author(s):  
Enoil De Souza Júnior ◽  
Kátia Kellem Da Rosa ◽  
Jefferson Cardia Simões
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Climatic Conditions ◽  
The Arctic ◽  
Arctic Warming ◽  
Northwest Passage ◽  
Arctic Sea ◽  
The World ◽  
The Arctic Ocean ◽  
Long Time

<p>Desde o período das Grandes Navegações, mais precisamente nos séculos XV e XVI, procura-se uma maneira mais rápida de ligar a Europa, Ásia e América. Nessa procura muitos exploradores se aventuraram no Ártico, porém naquela época, as condições climáticas eram diferentes das atuais, sendo que o gelo marinho cobria quase toda extensão do Oceano Ártico mesmo no verão.  Assim, as rotas marítimas árticas não puderam ser exploradas por muito tempo. Entretanto, com o atual aquecimento no Ártico e a consequente retração do gelo marinho, o que era um sonho passa a ser realidade: as rotas que outrora foram abandonadas por serem de difícil acesso, passam a ligar o mundo de maneira mais rápida e barata. Neste artigo examina a procura por essas rotas em artigos científicos e em livros que relatam registros históricos e qual é a expectativa para o século XXI.</p><p><strong>Palavras–chave:</strong> Rota Nordeste, Rota Noroeste, Ártico.</p><p><strong>Abstract </strong></p><p>Since the Great Navigations period, 15th and 16th centuries, there has been a search for faster sea-lanes to connect Europe, Asia and America. In this search many explorers ventured in the Arctic, however, at that time the climatic conditions were different from the current ones, sea ice covered almost the entire length of the Arctic Ocean even in high summer, so for a long time the Arctic sea routes could not be explored. Presently, the Arctic warming and the consequent decline of sea ice cover area, make such routes a reality and could potentially connect the world more quickly and cheaply. This paper examines the search for these routes in papers and books that reports historical events and what could be expected for the 21th century.</p><p><strong>Keywords</strong>: Northeast Passage, Northwest Passage, Arctic.</p>

Interannual Variations of Arctic Cloud Types in Relation to Sea Ice

2010 ◽  
Vol 23 (15) ◽  
pp. 4216-4232 ◽  
Author(s):  
Ryan Eastman ◽  
Stephen G. Warren
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Cloud Cover ◽  
Surface Air Temperature ◽  
The Arctic ◽  
Interannual Variations ◽  
Total Cloud Cover ◽  
Sea Ice Extent ◽  
The Arctic Ocean ◽  
Precipitating Clouds

Abstract Sea ice extent and thickness may be affected by cloud changes, and sea ice changes may in turn impart changes to cloud cover. Different types of clouds have different effects on sea ice. Visual cloud reports from land and ocean regions of the Arctic are analyzed here for interannual variations of total cloud cover and nine cloud types, and their relation to sea ice. Over the high Arctic, cloud cover shows a distinct seasonal cycle dominated by low stratiform clouds, which are much more common in summer than winter. Interannual variations of cloud amounts over the Arctic Ocean show significant correlations with surface air temperature, total sea ice extent, and the Arctic Oscillation. Low ice extent in September is generally preceded by a summer with decreased middle and precipitating clouds. Following a low-ice September there is enhanced low cloud cover in autumn. Total cloud cover appears to be greater throughout the year during low-ice years. Multidecadal trends from surface observations over the Arctic Ocean show increasing cloud cover, which may promote ice loss by longwave radiative forcing. Trends are positive in all seasons, but are most significant during spring and autumn, when cloud cover is positively correlated with surface air temperature. The coverage of summertime precipitating clouds has been decreasing over the Arctic Ocean, which may promote ice loss.

scholarly journals Atmospheric Trends Over the Arctic Ocean in Simulations from the Coordinated Regional Downscaling Experiment (CORDEX) and Their Driving GCMs

2021 ◽  
Author(s):  
Cathy Reader ◽  
Nadja Steiner
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
General Circulation ◽  
Climate Models ◽  
Circulation Model ◽  
The Arctic ◽  
Atlantic Sector ◽  
Near Surface ◽  
The Arctic Ocean ◽  
Regional Downscaling

Abstract The Arctic Coordinated Regional Downscaling Experiment (Arctic-CORDEX) uses regional climate models (RCMs) to downscale selected Fifth Coupled Model Intercomparison Project (CMIP5) simulations, allowing trend validation and projection on subregional scales. For 1986-2015, the CORDEX seasonal-average near-surface temperature (tas), wind speed (sfcWind), precipitation (pr) and snowfall (prsn) trends are consistent with the ERA5 analysis for the Arctic Ocean regions considered. The projected Representative Concentration Pathway 8.5 (RCP8.5) 2016-2100 subregional annual tas trends range from 0.03 to 0.18 K/year. Projected annual pr and prsn trends have a large inter-model spread centered around approximately 5.0x10−8 mm/s/year and -5.0x10−8 mm/s/year, respectively, while projected sfcWind summer and winter trends range between 0.0 and 0.4 m/s/year. For all variables except prsn, and sometimes total precipitation, the driving general circulation model (GCM) dominates the trends, however there is a tendency for the GCMs to underestimate the sfcWind trends compared to the downscaled simulations. Subtracting the Arctic-Ocean mean from subregional trends reveals a consistent, qualitative anomaly pattern in several variables and seasons characterized by greater-than or average trends in the central and Siberian Arctic Ocean and lesser or average trends in the Atlantic Sector and the Bering Sea, related to summer sea-ice trends. In particular, a strong proportional relationship exists between the summer sea-ice concentration and fall tas and sfcWind trend anomalies. The RCP4.5 annual, multi-model mean trends are 35-55% of the corresponding RCP8.5 trends for most variables and subregions.

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