scholarly journals Unnatural Trend Detection of Arctic Amplification

2021 ◽  
Author(s):  
Yu Wang ◽  
Pengcheng Yan ◽  
Taichen Feng ◽  
Fei Ji ◽  
Shankai Tang ◽  
...  
Keyword(s):  
Great Plains ◽  
Barents Sea ◽  
Surface Air Temperature ◽  
Arctic Region ◽  
Warming Trend ◽  
Kara Sea ◽  
Trend Detection ◽  
The Arctic ◽  
Driving Mechanism ◽  
Arctic Amplification

Abstract The driving mechanism of Arctic amplification (AA) is so complex that no consistent and definitive conclusion has been formed yet. In particular, the natural or unnatural cause of AA has not yet been investigated and distinguished in clarity and depth. Given that the Arctic is more sensitive than other regions to greenhouse gases and other unnatural forcing, especially human activity, we are focusing on separating unnatural trend (caused by unnatural forcing) from the Arctic surface air temperature (SAT) changes during 1979–2017 to quantify the contribution of unnatural forcing on AA, with converting detection and attribution to probability statistics model. Compared to earlier studies, we find that the Arctic coast of the Siberian Great Plains, from the Barents Sea to the Kara Sea and eastward to the Bering Strait, has been warming most significantly, which is mainly dominated by unnatural trends. From 1979 to 2017, the minimum unnatural warming in most parts of the Arctic Ocean reached above 1.5℃, especially in the Kara Sea area, where the unnatural warming was significant, reaching 4℃. The Kara Sea is sensitive to unnatural forcing. In addition, the minimum unnatural contributions exceed 60% in most parts of the Arctic Circle, and was more than 80% in (75–90°N, 150–180°W). In 140°W-140°E Arctic region, the unnatural trend is the most remarkable with 0.82℃ per decade, accounting for 84.5% of the measured warming trend. Meanwhile, the unnatural trend changes most rapidly for the temporal evolution in this area (0-140°W, 60–90°N).

scholarly journals Prediction of Arctic temperature and sea ice using a high-resolution coupled model

2021 ◽  
pp. 1-62
Author(s):  
Le Chang ◽  
Jing-Jia Luo ◽  
Jiaqing Xue ◽  
Haiming Xu ◽  
Nick Dunstone
Keyword(s):  
High Resolution ◽  
Sea Ice ◽  
Air Temperature ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Arctic Region ◽  
Warming Trend ◽  
Lower Atmosphere ◽  
The Arctic

AbstractUnder global warming, surface air temperature has risen rapidly and sea ice decreased markedly in the Arctic. These drastic climate changes have brought about various severe impacts on the vulnerable environment and ecosystem there. Thus, accurate prediction of Arctic climate becomes more important than before. Here we examine the seasonal to interannual predictive skills of 2-meter air temperature (2-m T) and sea ice cover (SIC) over the Arctic region (70°∼90°N) during 1980–2014 with a high-resolution global coupled model called the Met Office Decadal Prediction System version 3 (DePreSys3). The model captures well both the climatology and interannual variability of the Arctic 2-m T and SIC. Moreover, the anomaly correlation coefficient (ACC) of Arctic-averaged 2-m T and SIC shows statistically significant skills at lead times up to 16 months. This is mainly due to the contribution of strong decadal trends. In addition, it is found that the peak warming trend of Arctic 2-m T lags the maximum decrease trend of SIC by one month, in association with the heat flux forcing from the ocean surface to lower atmosphere. While the predictive skill is generally much lower for the detrended variations, we find a close relationship between the tropical Pacific El Niño–Southern Oscillation and the Arctic detrended 2-m T anomalies. This indicates potential seasonal to interannual predictability of the Arctic natural variations.

scholarly journals Surface Energy Balance Framework for Arctic Amplification of Climate Change

2012 ◽  
Vol 25 (23) ◽  
pp. 8277-8288 ◽  
Author(s):  
Glen Lesins ◽  
Thomas J. Duck ◽  
James R. Drummond
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
The Arctic ◽  
Arctic Amplification ◽  
Global Average ◽  
Inversion Strength

Abstract Using 22 Canadian radiosonde stations from 1971 to 2010, the annually averaged surface air temperature trend amplification ranged from 1.4 to 5.2 relative to the global average warming of 0.17°C decade−1. The amplification factors exhibit a strong latitudinal dependence varying from 2.6 to 5.2 as the latitude increases from 50° to 80°N. The warming trend has a strong seasonal dependence with the greatest warming taking place from September to April. The monthly variations in the warming trend are shown to be related to the surface-based temperature inversion strength and the mean monthly surface air temperatures. The surface energy balance (SEB) equation is used to relate the response of the surface temperature to changes in the surface energy fluxes. Based on the SEB analysis, there are four contributing factors to Arctic amplification: 1) a larger change in net downward radiation at the Arctic surface compared to the global average; 2) a larger snow and soil conductive heat flux change than the global average; 3) weaker sensible and latent heat flux responses that result in a larger surface temperature response in the Arctic; and 4) a colder skin temperature compared to the global average, which forces a larger surface warming to achieve the same increase in upward longwave radiation. The observed relationships between the Canadian station warming trends and both the surface-based inversion strength and the surface air temperature are shown to be consistent with the SEB analysis. Measurements of conductive flux were not available at these stations.

Bryozoans of the Kara Sea: estimation of species diversity and patterns of biogeographic composition

2021 ◽  
Vol 325 (2) ◽  
pp. 217-234
Author(s):  
N.V. Denisenko
Keyword(s):  
Barents Sea ◽  
Geographic Location ◽  
Environmental Parameters ◽  
Arctic Region ◽  
Kara Sea ◽  
The Arctic ◽  
Arctic Seas ◽  
Species List ◽  
Faunistic Complex ◽  
The Moment

Until now, information on the bryozoan fauna of the Kara Sea was as the most unordered in comparison to other Arctic seas of Russia. The information in literature is mainly based on the data collected more than 80 years ago. Collections carried out over the last 30 years made it possible to expand the understanding not only of the species richness of this group, but also to study its spatial variation within the sea. At the moment, the species list of bryozoans in the Kara Sea includes 230 names. Of these, 42 species were recorded for the first time in this area of the Arctic. The fauna richness varies with depth and geographic location of sampling sites. Comparison of the species composition of bryozoans within 6 sectors defined on the basis of differences in environmental parameters indicates the presence of a single faunistic complex. The biogeographic composition of the fauna is characterized by the predominance of the boreal-arctic species (67%) over the arctic (30%); the share of boreal species is only 3%. Comparison of bryozoans from the Kara Sea with faunas from other areas of the Arctic region indicates a closer similarity of its fauna with the fauna of the Barents Sea than with the fauna of bryozoans from the Laptev Sea.

scholarly journals Extreme Warming in the Kara Sea and Barents Sea during the Winter Period 2000–16

2017 ◽  
Vol 30 (22) ◽  
pp. 8913-8927 ◽  
Author(s):  
Svenja H. E. Kohnemann ◽  
Günther Heinemann ◽  
David H. Bromwich ◽  
Oliver Gutjahr
Keyword(s):  
Sea Ice ◽  
Air Temperature ◽  
Barents Sea ◽  
Kara Sea ◽  
The Arctic ◽  
Winter Period ◽  
Limited Area ◽  
Spatial And Temporal Variability ◽  
Large Variability ◽  
Air Temperatures

The regional climate model COSMO in Climate Limited-Area Mode (COSMO-CLM or CCLM) is used with a high resolution of 15 km for the entire Arctic for all winters 2002/03–2014/15. The simulations show a high spatial and temporal variability of the recent 2-m air temperature increase in the Arctic. The maximum warming occurs north of Novaya Zemlya in the Kara Sea and Barents Sea between March 2003 and 2012 and is responsible for up to a 20°C increase. Land-based observations confirm the increase but do not cover the maximum regions that are located over the ocean and sea ice. Also, the 30-km version of the Arctic System Reanalysis (ASR) is used to verify the CCLM for the overlapping time period 2002/03–2011/12. The differences between CCLM and ASR 2-m air temperatures vary slightly within 1°C for the ocean and sea ice area. Thus, ASR captures the extreme warming as well. The monthly 2-m air temperatures of observations and ERA-Interim data show a large variability for the winters 1979–2016. Nevertheless, the air temperature rise since the beginning of the twenty-first century is up to 8 times higher than in the decades before. The sea ice decrease is identified as the likely reason for the warming. The vertical temperature profiles show that the warming has a maximum near the surface, but a 0.5°C yr−1 increase is found up to 2 km. CCLM, ASR, and also the coarser resolved ERA-Interim data show that February and March are the months with the highest 2-m air temperature increases, averaged over the ocean and sea ice area north of 70°N; for CCLM the warming amounts to an average of almost 5°C for 2002/03–2011/12.

scholarly journals Mechanism of Seasonal Arctic Sea Ice Evolution and Arctic Amplification

2016 ◽  
Author(s):  
Kwang-Yul Kim ◽  
Benjamin D. Hamlington ◽  
Hanna Na ◽  
Jinju Kim
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Longwave Radiation ◽  
The Arctic ◽  
Turbulent Heat ◽  
Arctic Amplification ◽  
Ice Melting ◽  
Downward Longwave Radiation

Abstract. Sea ice melting is proposed as a primary reason for the Artic amplification, although physical mechanism of the Arctic amplification and its connection with sea ice melting is still in debate. In the present study, monthly ERA-interim reanalysis data are analyzed via cyclostationary empirical orthogonal function analysis to understand the seasonal mechanism of sea ice melting in the Arctic Ocean and the Arctic amplification. While sea ice melting is widespread over much of the perimeter of the Arctic Ocean in summer, sea ice remains to be thin in winter only in the Barents-Kara Seas. Excessive turbulent heat flux through the sea surface exposed to air due to sea ice melting warms the atmospheric column. Warmer air increases the downward longwave radiation and subsequently surface air temperature, which facilitates sea surface remains to be ice free. A 1 % reduction in sea ice concentration in winter leads to ~ 0.76 W m−2 increase in upward heat flux, ~ 0.07 K increase in 850 hPa air temperature, ~ 0.97 W m−2 increase in downward longwave radiation, and ~ 0.26 K increase in surface air temperature. This positive feedback mechanism is not clearly observed in the Laptev, East Siberian, Chukchi, and Beaufort Seas, since sea ice refreezes in late fall (November) before excessive turbulent heat flux is available for warming the atmospheric column in winter. A detailed seasonal heat budget is presented in order to understand specific differences between the Barents-Kara Seas and Laptev, East Siberian, Chukchi, and Beaufort Seas.

scholarly journals Frequency and distribution of winter melt events from passive microwave satellite data in the pan-Arctic, 1988–2013

2016 ◽  
Author(s):  
Libo Wang ◽  
Peter Toose ◽  
Ross Brown ◽  
Chris Derksen
Keyword(s):  
Snow Cover ◽  
Microwave Radiometer ◽  
Surface Air Temperature ◽  
Arctic Region ◽  
Temporal Variations ◽  
Passive Microwave ◽  
The Arctic ◽  
Winter Period ◽  
Strongly Correlated ◽  
Air Temperatures

Abstract. This study presents an algorithm for detecting winter melt events in seasonal snow cover based on temporal variations in the brightness temperature difference between 19 and 37 GHz from satellite passive microwave measurements. An advantage of the passive microwave approach is that it is based on the physical presence of liquid water in the snowpack, which may not be the case with melt events inferred from surface air temperature data. The algorithm is validated using in situ observations from weather stations, snowpit surveys, and a surface-based passive microwave radiometer. The results of running the algorithm over the pan-Arctic region (north of 50º N) for the 1988–2013 period show that winter melt days are relatively rare averaging less than 7 melt days per winter over most areas, with higher numbers of melt days (around two weeks per winter) occurring in more temperate regions of the Arctic (e.g. central Quebec and Labrador, southern Alaska, and Scandinavia). The observed spatial pattern was similar to winter melt events inferred with surface air temperatures from ERA-interim and MERRA reanalysis datasets. There was little evidence of trends in winter melt frequency except decreases over northern Europe attributed to a shortening of the duration of the winter period. The frequency of winter melt events is shown to be strongly correlated to the duration of winter period. This must be taken into account when analyzing trends to avoid generating false increasing trends from shifts in the timing of the snow cover season.

The Role of Horizontal Temperature Advection on Arctic Amplification

2021 ◽  
pp. 1-54
Author(s):  
Joseph P. Clark ◽  
Vivek Shenoy ◽  
Steven B. Feldstein ◽  
Sukyoung Lee ◽  
Michael Goss
Keyword(s):  
Chukchi Sea ◽  
Surface Air Temperature ◽  
Longwave Radiation ◽  
Warming Trend ◽  
Surface Energy Budget ◽  
Arctic Amplification ◽  
Self Organizing Maps ◽  
Temperature Advection ◽  
Downward Longwave Radiation ◽  
Barents And Kara Seas

AbstractThe wintertime (December – February) 1990 - 2016 Arctic surface air temperature (SAT) trend is examined using self-organizing maps (SOMs). The high dimensional SAT dataset is reduced into nine representative SOM patterns, with each pattern exhibiting a decorrelation time scale about 10 days and having about 85% of its variance coming from intraseasonal timescales. The trend in the frequency of occurrence of each SOM pattern is used to estimate the interdecadal Arctic winter warming trend associated with the SOM patterns. It is found that trends in the SOM patterns explain about one-half of the SAT trend in the Barents and Kara Seas, one-third of the SAT trend around Baffin Bay and two-thirds of the SAT trend in the Chukchi Sea. A composite calculation of each term in the thermodynamic energy equation for each SOM pattern shows that the SAT anomalies grow primarily through the advection of the climatological temperature by the anomalous wind. This implies that a substantial fraction of Arctic amplification is due to horizontal temperature advection that is driven by changes in the atmospheric circulation. An analysis of the surface energy budget indicates that the skin temperature anomalies as well as the trend, although very similar to that of the SAT, are produced primarily by downward longwave radiation.

Sustainable Development of Oil Production in the Arctic Shelf and Evolution of Fish Stock

2019 ◽  
pp. 451-469
Author(s):  
Yuri Yegorov
Keyword(s):  
Sustainable Development ◽  
Oil And Gas ◽  
Barents Sea ◽  
Arctic Region ◽  
Renewable Resource ◽  
Academic Community ◽  
The Arctic ◽  
Fish Stock ◽  
Common Pool ◽  
Arctic Fish

Arctic region is an important resource for hydrocarbons (oil and gas). Their exploitation is not immediate but will develop fast as soon as oil prices approach $100 per barrel again. In the Arctic, fish stock is an important renewable resource. Contrary to hydrocarbons, it is already overexploited. Future simultaneous exploitation of both resources poses several problems, including externalities and common pool. The academic community still has some time for theoretical investigation of those future problems and working out the corresponding policy measures that are consistent with sustainable development of the region. The Barents Sea is especially important because it has a common pool both in hydrocarbons and fish.

Salt composition and biogenic elements in modern pore waters of the Barents Sea (1997–2019)

2021 ◽  
pp. 370-398
Author(s):  
A.Yu. Lein ◽  
◽  
M.D. Kravchishina ◽  
G.A. Pavlova ◽  
A.L. Chultsova ◽  
...  
Keyword(s):  
Barents Sea ◽  
Arctic Region ◽  
The Arctic ◽  
Biogenic Elements ◽  
Pore Waters ◽  
Salt Composition ◽  
Surface Layers ◽  
Suspended Particulate ◽  
The Arctic Ocean ◽  
Maximum Warming

The data (Cl-, SO42-, Ca2+ Alk and biogenic elements) on the salt composition of pore water and the isotopic organic carbon composition of suspended particulate matter, fluffy layer and surface layers (0–30 cm) of bottom sediments in the Barents and Norwegian seas are discussed during the period of the supposed maximum warming in the Arctic region in the 21st century associated with the “atlantification” of the Arctic Ocean.

scholarly journals CMIP5 Projections of Arctic Amplification, of the North American/North Atlantic Circulation, and of Their Relationship

2015 ◽  
Vol 28 (13) ◽  
pp. 5254-5271 ◽  
Author(s):  
Elizabeth A. Barnes ◽  
Lorenzo M. Polvani
Keyword(s):  
North Atlantic ◽  
Climate Models ◽  
Coupled Model ◽  
Arctic Region ◽  
The Arctic ◽  
Cmip5 Models ◽  
Arctic Amplification ◽  
Arctic Warming ◽  
The North ◽  
Sequence Of Events

Abstract Recent studies have hypothesized that Arctic amplification, the enhanced warming of the Arctic region compared to the rest of the globe, will cause changes in midlatitude weather over the twenty-first century. This study exploits the recently completed phase 5 of the Coupled Model Intercomparison Project (CMIP5) and examines 27 state-of-the-art climate models to determine if their projected changes in the midlatitude circulation are consistent with the hypothesized impact of Arctic amplification over North America and the North Atlantic. Under the largest future greenhouse forcing (RCP8.5), it is found that every model, in every season, exhibits Arctic amplification by 2100. At the same time, the projected circulation responses are either opposite in sign to those hypothesized or too widely spread among the models to discern any robust change. However, in a few seasons and for some of the circulation metrics examined, correlations are found between the model spread in Arctic amplification and the model spread in the projected circulation changes. Therefore, while the CMIP5 models offer some evidence that future Arctic warming may be able to modulate some aspects of the midlatitude circulation response in some seasons, the analysis herein leads to the conclusion that the net circulation response in the future is unlikely to be determined solely—or even primarily—by Arctic warming according to the sequence of events recently hypothesized.

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