scholarly journals Effects of Arctic sea ice in autumn on extreme cold events over the Tibetan Plateau in the following winter: possible mechanisms

2021 ◽  
Author(s):  
Miao Bi ◽  
Qingquan Li ◽  
Song Yang ◽  
Dong Guo ◽  
Xinyong Shen ◽  
...  
Keyword(s):  
Sea Ice ◽  
Wave Train ◽  
Beaufort Sea ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
The Tibetan Plateau ◽  
The North ◽  
Arctic Sea ◽  
Cold Events ◽  
Extreme Cold

AbstractExtreme cold events (ECEs) on the Tibetan Plateau (TP) exert serious impacts on agriculture and animal husbandry and are important drivers of ecological and environmental changes. We investigate the temporal and spatial characteristics of the ECEs on the TP and the possible effects of Arctic sea ice. The daily observed minimum air temperature at 73 meteorological stations on the TP during 1980–2018 and the BCC_AGCM3_MR model are used. Our results show that the main mode of winter ECEs over the TP exhibits the same spatial variation and interannual variability across the whole region and is affected by two wave trains originating from the Arctic. The southern wave train is controlled by the sea ice in the Beaufort Sea. It initiates in the Norwegian Sea, and then passes through the North Atlantic Ocean, the Arabian Sea, and the Bay of Bengal along the subtropical westerly jet stream. It enters the TP from the south and brings warm, humid air from the oceans. By contrast, the northern wave train is controlled by the sea ice in the Laptev Sea. It originates from the Barents and Kara seas, passes through Lake Baikal, and enters the TP from the north, bringing dry and cold air. A decrease in the sea ice in the Beaufort Sea causes positive potential height anomalies in the Arctic. This change enhances the pressure gradient between the Artic and the mid-latitudes, leading to westerly winds in the northern TP, which block the intrusion of cold air into the south. By contrast, a decrease in the sea ice in the Laptev Sea causes negative potential height anomalies in the Artic. This change reduces the pressure gradient between the Artic and the mid-latitudes, leading to easterly winds to the north of the TP, which favors the southward intrusion of cold polar air. A continuous decrease in the amount of sea ice in the Beaufort Sea would reduce the frequency of ECEs over the TP and further aggravate TP warming in winter.

scholarly journals The Predictability of Ocean Environments that Contributed to the 2020/21 Extreme Cold Events in China: 2020/21 La Niña and 2020 Arctic Sea Ice Loss

2022 ◽  
Author(s):  
Fei Zheng ◽  
Ji-Ping Liu ◽  
Xiang-Hui Fang ◽  
Mi-Rong Song ◽  
Chao-Yuan Yang ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Arctic Sea Ice ◽  
La Niña ◽  
The Arctic ◽  
La Nina ◽  
Arctic Sea ◽  
Cold Events ◽  
Extreme Cold ◽  
Arctic Sea Ice Loss

AbstractSeveral consecutive extreme cold events impacted China during the first half of winter 2020/21, breaking the low-temperature records in many cities. How to make accurate climate predictions of extreme cold events is still an urgent issue. The synergistic effect of the warm Arctic and cold tropical Pacific has been demonstrated to intensify the intrusions of cold air from polar regions into middle-high latitudes, further influencing the cold conditions in China. However, climate models failed to predict these two ocean environments at expected lead times. Most seasonal climate forecasts only predicted the 2020/21 La Niña after the signal had already become apparent and significantly underestimated the observed Arctic sea ice loss in autumn 2020 with a 1–2 month advancement. In this work, the corresponding physical factors that may help improve the accuracy of seasonal climate predictions are further explored. For the 2020/21 La Niña prediction, through sensitivity experiments involving different atmospheric-oceanic initial conditions, the predominant southeasterly wind anomalies over the equatorial Pacific in spring of 2020 are diagnosed to play an irreplaceable role in triggering this cold event. A reasonable inclusion of atmospheric surface winds into the initialization will help the model predict La Niña development from the early spring of 2020. For predicting the Arctic sea ice loss in autumn 2020, an anomalously cyclonic circulation from the central Arctic Ocean predicted by the model, which swept abnormally hot air over Siberia into the Arctic Ocean, is recognized as an important contributor to successfully predicting the minimum Arctic sea ice extent.

Gridded Arctic sea ice concentration reconstruction for the first half of the 20th century based on different proxy data

2021 ◽  
Author(s):  
Vladimir Semenov ◽  
Tatiana Matveeva
Keyword(s):  
Sea Ice ◽  
20Th Century ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
The North ◽  
Arctic Sea ◽  
Ice Concentration

<p>Global warming in the recent decades has been accompanied by a rapid recline of the Arctic sea ice area most pronounced in summer (10% per decade). To understand the relative contribution of external forcing and natural variability to the modern and future sea ice area changes, it is necessary to evaluate a range of long-term variations of the Arctic sea ice area in the period before a significant increase in anthropogenic emissions of greenhouse gases into the atmosphere. Available observational data on the spatiotemporal dynamics of Arctic sea ice until 1950s are characterized by significant gaps and uncertainties. In the recent years, there have appeared several reconstructions of the early 20<sup>th</sup> century Arctic sea ice area that filled the gaps by analogue methods or utilized combined empirical data and climate model’s output. All of them resulted in a stronger that earlier believed negative sea ice area anomaly in the 1940s concurrent with the early 20<sup>th</sup> century warming (ETCW) peak. In this study, we reconstruct the monthly average gridded sea ice concentration (SIC) in the first half of the 20th century using the relationship between the spatiotemporal features of SIC variability, surface air temperature over the Northern Hemisphere extratropical continents, sea surface temperature in the North Atlantic and North Pacific, and sea level pressure. In agreement with a few previous results, our reconstructed data also show a significant negative anomaly of the Arctic sea ice area in the middle of the 20th century, however with some 15% to 30% stronger amplitude, about 1.5 million km<sup>2</sup> in September and 0.7 million km<sup>2</sup> in March. The reconstruction demonstrates a good agreement with regional Arctic sea ice area data when available and suggests that ETWC in the Arctic has been accompanied by a concurrent sea ice area decline of a magnitude that have been exceeded only in the beginning of the 21<sup>st</sup> century.</p>

scholarly journals The sensitivity of the Arctic sea ice to orbitally induced insolation changes: a study of the mid-Holocene Paleoclimate Modelling Intercomparison Project 2 and 3 simulations

2013 ◽  
Vol 9 (2) ◽  
pp. 969-982 ◽  
Author(s):  
M. Berger ◽  
J. Brandefelt ◽  
J. Nilsson
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Eastern Coast ◽  
Sea Ice Extent ◽  
The North ◽  
Arctic Sea ◽  
North Eastern ◽  
Intercomparison Project ◽  
Insolation Change

Abstract. In the present work the Arctic sea ice in the mid-Holocene and the pre-industrial climates are analysed and compared on the basis of climate-model results from the Paleoclimate Modelling Intercomparison Project phase 2 (PMIP2) and phase 3 (PMIP3). The PMIP3 models generally simulate smaller and thinner sea-ice extents than the PMIP2 models both for the pre-industrial and the mid-Holocene climate. Further, the PMIP2 and PMIP3 models all simulate a smaller and thinner Arctic summer sea-ice cover in the mid-Holocene than in the pre-industrial control climate. The PMIP3 models also simulate thinner winter sea ice than the PMIP2 models. The winter sea-ice extent response, i.e. the difference between the mid-Holocene and the pre-industrial climate, varies among both PMIP2 and PMIP3 models. Approximately one half of the models simulate a decrease in winter sea-ice extent and one half simulates an increase. The model-mean summer sea-ice extent is 11 % (21 %) smaller in the mid-Holocene than in the pre-industrial climate simulations in the PMIP2 (PMIP3). In accordance with the simple model of Thorndike (1992), the sea-ice thickness response to the insolation change from the pre-industrial to the mid-Holocene is stronger in models with thicker ice in the pre-industrial climate simulation. Further, the analyses show that climate models for which the Arctic sea-ice responses to increasing atmospheric CO2 concentrations are similar may simulate rather different sea-ice responses to the change in solar forcing between the mid-Holocene and the pre-industrial. For two specific models, which are analysed in detail, this difference is found to be associated with differences in the simulated cloud fractions in the summer Arctic; in the model with a larger cloud fraction the effect of insolation change is muted. A sub-set of the mid-Holocene simulations in the PMIP ensemble exhibit open water off the north-eastern coast of Greenland in summer, which can provide a fetch for surface waves. This is in broad agreement with recent analyses of sea-ice proxies, indicating that beach-ridges formed on the north-eastern coast of Greenland during the early- to mid-Holocene.

scholarly journals Internal Variability in Projections of Twenty-First-Century Arctic Sea Ice Loss: Role of the Large-Scale Atmospheric Circulation

2014 ◽  
Vol 27 (2) ◽  
pp. 527-550 ◽  
Author(s):  
Justin J. Wettstein ◽  
Clara Deser
Keyword(s):  
Sea Ice ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Wave Train ◽  
Internal Variability ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Arctic Sea ◽  
Rossby Wave Train ◽  
Arctic Sea Ice Loss

Abstract Internal variability in twenty-first-century summer Arctic sea ice loss and its relationship to the large-scale atmospheric circulation is investigated in a 39-member Community Climate System Model, version 3 (CCSM3) ensemble for the period 2000–61. Each member is subject to an identical greenhouse gas emissions scenario and differs only in the atmospheric model component's initial condition. September Arctic sea ice extent trends during 2020–59 range from −2.0 × 106 to −5.7 × 106 km2 across the 39 ensemble members, indicating a substantial role for internal variability in future Arctic sea ice loss projections. A similar nearly threefold range (from −7.0 × 103 to −19 × 103 km3) is found for summer sea ice volume trends. Higher rates of summer Arctic sea ice loss in CCSM3 are associated with enhanced transpolar drift and Fram Strait ice export driven by surface wind and sea level pressure patterns. Over the Arctic, the covarying atmospheric circulation patterns resemble the so-called Arctic dipole, with maximum amplitude between April and July. Outside the Arctic, an atmospheric Rossby wave train over the Pacific sector is associated with internal ice loss variability. Interannual covariability patterns between sea ice and atmospheric circulation are similar to those based on trends, suggesting that similar processes govern internal variability over a broad range of time scales. Interannual patterns of CCSM3 ice–atmosphere covariability compare well with those in nature and in the newer CCSM4 version of the model, lending confidence to the results. Atmospheric teleconnection patterns in CCSM3 suggest that the tropical Pacific modulates Arctic sea ice variability via the aforementioned Rossby wave train. Large ensembles with other coupled models are needed to corroborate these CCSM3-based findings.

scholarly journals Impact of a Reduced Arctic Sea Ice Cover on Ocean and Atmospheric Properties

2012 ◽  
Vol 25 (1) ◽  
pp. 307-319 ◽  
Author(s):  
Jan Sedláček ◽  
Reto Knutti ◽  
Olivia Martius ◽  
Urs Beyerle
Keyword(s):  
Sea Ice ◽  
North Atlantic ◽  
Arctic Basin ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Storm Tracks ◽  
The Arctic ◽  
The North ◽  
Arctic Sea ◽  
The North Atlantic

Abstract The Arctic sea ice cover declined over the last few decades and reached a record minimum in 2007, with a slight recovery thereafter. Inspired by this the authors investigate the response of atmospheric and oceanic properties to a 1-yr period of reduced sea ice cover. Two ensembles of equilibrium and transient simulations are produced with the Community Climate System Model. A sea ice change is induced through an albedo change of 1 yr. The sea ice area and thickness recover in both ensembles after 3 and 5 yr, respectively. The sea ice anomaly leads to changes in ocean temperature and salinity to a depth of about 200 m in the Arctic Basin. Further, the salinity and temperature changes in the surface layer trigger a “Great Salinity Anomaly” in the North Atlantic that takes roughly 8 yr to travel across the North Atlantic back to high latitudes. In the atmosphere the changes induced by the sea ice anomaly do not last as long as in the ocean. The response in the transient and equilibrium simulations, while similar overall, differs in specific regional and temporal details. The surface air temperature increases over the Arctic Basin and the anomaly extends through the whole atmospheric column, changing the geopotential height fields and thus the storm tracks. The patterns of warming and thus the position of the geopotential height changes vary in the two ensembles. While the equilibrium simulation shifts the storm tracks to the south over the eastern North Atlantic and Europe, the transient simulation shifts the storm tracks south over the western North Atlantic and North America. The authors propose that the overall reduction in sea ice cover is important for producing ocean anomalies; however, for atmospheric anomalies the regional location of the sea ice anomalies is more important. While observed trends in Arctic sea ice are large and exceed those simulated by comprehensive climate models, there is little evidence based on this particular model that the seasonal loss of sea ice (e.g., as occurred in 2007) would constitute a threshold after which the Arctic would exhibit nonlinear, irreversible, or strongly accelerated sea ice loss. Caution should be exerted when extrapolating short-term trends to future sea ice behavior.

scholarly journals Two leading modes of wintertime atmospheric circulation drive the recent warm Arctic-cold Eurasia temperature pattern

2020 ◽  
Author(s):  
kunhui Ye ◽  
Gabriele Messori
Keyword(s):  
Sea Ice ◽  
Atmospheric Circulation ◽  
North Atlantic ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
The North ◽  
Downward Longwave Radiation ◽  
North Asia ◽  
Arctic Sea ◽  
The North Atlantic

<p>The wintertime warm Arctic-cold Eurasia (WACE) temperature trend during 1990-2010 was characterized by accelerating warming in the Arctic region, cooling in Eurasia and accelerating autumn/winter Arctic sea ice loss. We identify two atmospheric circulation modes over the North Atlantic-Northern Eurasian sector which displayed strong upward trends over the same period and can explain a large part of the observed decadal WACE pattern. Both modes bear a close resemblance to well-known teleconnection patterns and are relatively independent from anomalies in Arctic sea-ice cover. The first mode (PC1) captures the recent negative trends in the North Atlantic Oscillation and increased Greenland blocking frequency while the second mode (PC2) is reminiscent of a Rossby wave train and reflects an increased blocking frequency over the Urals and North Asia. We find that the loss in the Arctic sea ice and the upward trends in the PC1/PC2 together account for most of the decadal Arctic warming trend (>80%). However, the decadal Eurasian cooling trends may be primarily ascribed to the two circulation modes alone: all of the cooling in Siberia is contributed to by the PC1, and 65% of the cooling in East Asia by their combination (the contribution by PC2 doubles that by PC1). Enhanced intraseasonal activity of the two circulation modes increases blocking frequencies over Greenland, the Ural region and North Asia, which drive anomalous moisture/heat flux towards the Arctic and alter the downward longwave radiation. It weakens warm advection and enhances advection of Arctic cold airmass towards Eurasia.</p>

scholarly journals Pollution over the Tibetan Plateau Linked to Sea Ice Loss in the Arctic

Eos ◽  
2020 ◽  
Vol 101 ◽  
Author(s):  
Michael Allen
Keyword(s):  
Tibetan Plateau ◽  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
The Tibetan Plateau ◽  
Anthropogenic Aerosol ◽  
Ice Melt ◽  
Arctic Sea ◽  
Aerosol Pollution ◽  
New Research

New research suggests an atmospheric connection between Arctic sea ice melt and anthropogenic aerosol pollution over the Tibetan Plateau.

scholarly journals Sea ice kinematic features in the Arctic outflow region and their associations with Arctic Northeast Passage accessibility

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Dawei Gui ◽  
Xiaoping Pang ◽  
Ruibo Lei ◽  
Xi Zhao ◽  
Jia Wang
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Fram Strait ◽  
The North ◽  
Atmospheric Circulation Indices ◽  
Arctic Sea ◽  
Outflow Region ◽  
Transpolar Drift ◽  
The Impact

<p><strong>Abstract.</strong> Increasing amounts of evidence have proven Arctic sea ice is undergoing remarkable loss. On the bright side, the Arctic sea routes are becoming increasingly accessible. In this study, the NSIDC product of sea ice motion was applied to reconstruct the northward speed of sea ice to obtain the kinematic features of the sea ice in the Arctic outflow region which specially referred to the Fram Strait and to the north of the Northeast Passage (NEP).</p><p>In the Arctic outflow region, the average southward displacement of sea ice in 2007&amp;ndash;2014 (1511&amp;thinsp;km) was more than twice the average prior to 2007 (617&amp;thinsp;km), which indicated continuous enhancement of the Transpolar Drift Stream (TDS) in comparison with previous years. In the regions to the north of the NEP, the long-term trend of northward sea ice speed in the Kara sector was +0.04&amp;thinsp;cm&amp;thinsp;s<sup>&amp;minus;1</sup>&amp;thinsp;year<sup>&amp;minus;1</sup> in spring. A significant statistical relationship was found between the NEP open period and the northward speed of the sea ice to the north of the NEP. The offshore advection of sea ice could account for the opening of sea routes by 33% and 15% in the Kara and Laptev sectors, respectively.</p><p>The atmospheric circulation indices across the TDS, i.e., the Central Arctic Index (CAI), presented more significant correlation than for the Arctic atmospheric Dipole Anomaly index with the open period of the NEP, and the CAI could explain the southward displacement of sea ice toward Fram Strait by more than 45%. The impact from the summer positive CAI reinforces the thinning and mechanical weakening of the sea ice in the NEP region, which promoted the navigability of the NEP.</p>

scholarly journals Two Leading Modes of Wintertime Atmospheric Circulation Drive the Recent Warm Arctic–Cold Eurasia Temperature Pattern

2020 ◽  
Vol 33 (13) ◽  
pp. 5565-5587 ◽  
Author(s):  
Kunhui Ye ◽  
Gabriele Messori
Keyword(s):  
Sea Ice ◽  
Atmospheric Circulation ◽  
North Atlantic ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
The North ◽  
Downward Longwave Radiation ◽  
North Asia ◽  
Arctic Sea ◽  
The North Atlantic

AbstractThe wintertime warm Arctic–cold Eurasia (WACE) temperature trend during 1990–2010 was characterized by accelerating warming in the Arctic region, cooling in Eurasia, and accelerating autumn/winter Arctic sea ice loss. We identify two atmospheric circulation modes over the North Atlantic–northern Eurasian sector that displayed strong upward trends over the same period and can explain a large part of the observed decadal WACE pattern. Both modes bear a close resemblance to well-known teleconnection patterns and are relatively independent from variability in Arctic sea ice cover. The first mode (PC1) captures the recent negative trends in the North Atlantic Oscillation and increased Greenland blocking frequency, while the second mode (PC2) is reminiscent of a Rossby wave train and reflects an increased blocking frequency over the Urals and north Asia. We find that the loss in the Arctic sea ice and the upward trends in PC1 and PC2 together account for most of the decadal Arctic warming trend (>80%). However, the decadal Eurasian cooling trends may be primarily ascribed to the two circulation modes alone: all of the cooling in Siberia is contributed to by PC1 and 65% of the cooling in East Asia by their combination (the contribution by PC2 doubles that by PC1). Enhanced intraseasonal activity of the two circulation modes increases blocking frequencies over Greenland, the Ural region, and north Asia, which drive anomalous moisture/heat flux toward the Arctic and alter the downward longwave radiation. This also weakens warm advection and enhances advection of cold Arctic airmasses towards Eurasia.

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