Dominant Characteristics of early autumn Arctic sea ice variability and its impact on Winter Eurasian climate

2020 ◽  
pp. 1-67
Author(s):  
Shuoyi Ding ◽  
Bingyi Wu ◽  
Wen Chen
Keyword(s):  
Sea Ice ◽  
Geopotential Height ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Height Anomaly ◽  
Geopotential Height Anomaly ◽  
Arctic Sea ◽  
Westerly Winds ◽  
The Arctic Region

AbstractThe present study investigated dominant characteristics of autumn Arctic sea ice concentration (SIC) interannual variations and impacts of September-October (SO) mean SIC anomalies in the East Siberian-Chukchi-Beaufort (EsCB) Seas on winter Eurasian climate variability. Results showed that the decreased SO EsCB sea ice is favorable for tropospheric warming and positive geopotential height anomaly over the Arctic region one month later through transporting much more heat fluxes to the atmosphere from the open water. When entering the early winter (ND(0)J(1)), enhanced upward propagation of quasi-stationary planetary waves in the mid-high latitudes generates anomalous Eliassen-Palm flux convergence in the upper troposphere, which decelerates the westerly winds and maintains the positive geopotential height anomaly in the Arctic region. This anticyclonic anomaly extends southward into the central-western Eurasia and leads to evident surface cooling there. Two months later, it further develops toward downstream accompanied by a deepened trough, making the northeastern China experience a colder late winter (JFM(1)). Meanwhile, an anticyclonic anomaly over the eastern North Pacific excites a horizontal eastward wave train and contributes to positive (negative) geopotential height anomaly around the Greenland (Europe), favoring negative surface temperature anomaly over western Europe. In addition, the stratospheric polar vortex is also significantly weakened in the wintertime, which is attributed to decreased meridional temperature gradient and decelerated westerly winds provides a favorable condition for much more quasi-stationary planetary waves propagating into the stratosphere. Some major features of atmospheric responses to EsCB sea ice loss are well reproduced in the CAM4 sensitivity experiments.

Dominant Characteristics of early autumn Arctic sea ice variability and its impact on Winter Eurasian climate

2020 ◽  
Author(s):  
Shuoyi Ding ◽  
Bingyi Wu ◽  
Wen Chen
Keyword(s):  
Climate Variability ◽  
Sea Ice ◽  
Geopotential Height ◽  
Physical Mechanism ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Height Anomaly ◽  
Geopotential Height Anomaly ◽  
Early Autumn ◽  
Arctic Sea

<p>The present study investigated dominant characteristics of autumn Arctic sea ice concentration (SIC) interannual variations, and examined impacts of SIC anomalies in the East Siberian-Chukchi-Beaufort (EsCB) Seas on winter Eurasian climate variability and the associated possible physical mechanism. Results showed that the Arctic SIC variations in both September and October display a certain continuity to some extent, thus, we chose the September-October (SO) mean SIC as a factor to explore its delayed impacts on winter atmosphere. Dominant features of Arctic SIC variability in SO is characterized by sea ice loss in the EsCB Seas, with more evident interannual variability since the late 1990s. Such a change can be attributed to the central Arctic pattern of atmospheric variability. Along with the global warming, the interannual variation of sea ice in the EsCB Seas seemingly exerts an increasingly role in the Northern Hemispheric climate variability. When the EsCB sea ice decreases in the early autumn (SO), a barotropic response of wave number 2 structure with significant warming and positive geopotential height anomaly dominates the Arctic region a month later. Then, in the early winter (ND(0)J(1)), the Arctic anticyclonic anomaly extends southward into the central-western Eurasia and leads to evident surface cooling there. Two month later, it further develops toward downstream accompanied by a deepened trough, making the East Asia experience a colder late winter (JFM(1)), especially in the northeastern China. Meanwhile, enhanced North Pacific anticyclonic perturbation excites an eastward wave train and contributes to positive geopotential height anomaly around the Greenland. Combined with a cyclonic anomaly to its southeast, a dipole structure forms and favors negative surface temperature anomaly covering the western Europe. In addition, a weakened polar vortex in the lower stratosphere can be observed during the boreal winter. Similar atmospheric responses to EsCB sea ice loss are well reproduced in the simulation experiments, not only supporting the conclusions from observational analyses, but also illustrating the possible physical mechanism to some extent.</p>

scholarly journals Recent summer Arctic atmospheric circulation anomalies in a historical perspective

2014 ◽  
Vol 8 (5) ◽  
pp. 4823-4847 ◽  
Author(s):  
A. Belleflamme ◽  
X. Fettweis ◽  
M. Erpicum
Keyword(s):  
Sea Ice ◽  
Atmospheric Circulation ◽  
Greenland Ice Sheet ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Arctic Sea ◽  
Circulation Anomalies ◽  
Arctic Sea Ice Loss ◽  
The Arctic Region

Abstract. A significant increase in the summertime occurrence of a high pressure area over the Beaufort Sea and Greenland has been observed from the beginning of the 2000's, and particularly between 2007 and 2012. These circulation anomalies are likely partly responsible for the enhanced Greenland ice sheet melt as well as the Arctic sea ice loss observed since 2007. Therefore, it is interesting to analyse whether similar conditions might have happened since the late 19th century over the Arctic region. We have used an atmospheric circulation type classification based on daily mean sea level pressure and 500 hPa geopotential height data from four reanalysis datasets (ERA-Interim, ERA-40, NCEP/NCAR, and 20CRv2) to put the recent circulation anomalies in perspective with the atmospheric circulation variability since 1871. We found that circulation conditions similar to 2007–2012 have occurred in the past, despite a higher uncertainty of the reconstructed circulation before 1940. But the recent anomalies largely exceed the interannual variability of the atmospheric circulation of the Arctic region. These circulation anomalies are linked with the North Atlantic Oscillation suggesting that they are not limited to the Arctic. Finally, they favour summertime Arctic sea ice loss.

scholarly journals Snowmelt onset over Arctic sea ice from passive microwave satellite data: 1979–2012

2014 ◽  
Vol 8 (6) ◽  
pp. 2089-2100 ◽  
Author(s):  
A. C. Bliss ◽  
M. R. Anderson
Keyword(s):  
Sea Ice ◽  
Microwave Radiometer ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Data Set ◽  
Brightness Temperatures ◽  
Arctic Sea ◽  
Microwave Imager ◽  
The Arctic Region

Abstract. An updated version (Version 3) of the Snow Melt Onset Over Arctic Sea Ice from SMMR (Scanning Multichannel Microwave Radiometer) and SSM/I-SSMIS (Special Sensor Microwave/Imager-Special Sensor Microwave Imager/Sounder) Brightness Temperatures data set is now available. The data record has been reprocessed and extended to cover the years 1979–2012. From this data set, a statistical summary of melt onset (MO) dates on Arctic sea ice is presented. The mean MO date for the Arctic Region is 13 May (132.5 DOY – day of year) with a standard deviation of ±7.3 days. Regionally, mean MO dates vary from 15 March (73.2 DOY) in the St. Lawrence Gulf to 10 June (160.9 DOY) in the Central Arctic. Statistically significant decadal trends indicate that MO is occurring 6.6 days decade−1 earlier in the year for the Arctic Region. Regionally, MO trends are as great as −11.8 days decade−1 in the East Siberian Sea. The Bering Sea is an outlier and MO is occurring 3.1 days decade−1 later in the year.

scholarly journals Arctic sea ice melt onset from passive microwave satellite data: 1979–2012

2014 ◽  
Vol 8 (3) ◽  
pp. 3037-3055 ◽  
Author(s):  
A. C. Bliss ◽  
M. R. Anderson
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Data Set ◽  
Ice Melt ◽  
Brightness Temperatures ◽  
East Siberian Sea ◽  
Arctic Sea ◽  
The Arctic Region

Abstract. An updated version of the Snow Melt Onset Over Arctic Sea Ice from SMMR and SSM/I-SSMIS Brightness Temperatures is now available. The data record has been re-processed and extended to cover the years 1979–2012. From this data set, a statistical summary of melt onset (MO) dates on Arctic sea ice is presented. The mean MO date for the Arctic Region is 13 May (132.5 DOY) with a standard deviation of ±7.3 days. Regionally, mean MO dates vary from 15 March (73.2 DOY) in the St. Lawrence Gulf to 10 June (160.9 DOY) in the Central Arctic. Statistically significant decadal trends indicate that MO is occurring 6.6 days decade−1 earlier in the year for the Arctic Region. Regionally, MO trends are as great as −11.8 days decade−1 in the East Siberian Sea. The Bering Sea is an outlier and MO is occurring 3.1 days decade−1 later in the year.

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 Record high Pacific Arctic seawater temperatures and delayed sea ice advance in response to episodic atmospheric blocking

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tsubasa Kodaira ◽  
Takuji Waseda ◽  
Takehiko Nose ◽  
Jun Inoue
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
Sea Surface ◽  
The Arctic ◽  
Atmospheric Blocking ◽  
Sea Ice Extent ◽  
The Pacific ◽  
Arctic Sea ◽  
Highly Correlated

AbstractArctic sea ice is rapidly decreasing during the recent period of global warming. One of the significant factors of the Arctic sea ice loss is oceanic heat transport from lower latitudes. For months of sea ice formation, the variations in the sea surface temperature over the Pacific Arctic region were highly correlated with the Pacific Decadal Oscillation (PDO). However, the seasonal sea surface temperatures recorded their highest values in autumn 2018 when the PDO index was neutral. It is shown that the anomalous warm seawater was a rapid ocean response to the southerly winds associated with episodic atmospheric blocking over the Bering Sea in September 2018. This warm seawater was directly observed by the R/V Mirai Arctic Expedition in November 2018 to significantly delay the southward sea ice advance. If the atmospheric blocking forms during the PDO positive phase in the future, the annual maximum Arctic sea ice extent could be dramatically reduced.

scholarly journals The potential of sea ice leads as a predictor for summer Arctic sea ice extent

2018 ◽  
Vol 12 (12) ◽  
pp. 3747-3757 ◽  
Author(s):  
Yuanyuan Zhang ◽  
Xiao Cheng ◽  
Jiping Liu ◽  
Fengming Hui
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Strong Relationship ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Leads ◽  
Arctic Sea Ice Extent

Abstract. The Arctic sea ice extent throughout the melt season is closely associated with initial sea ice state in winter and spring. Sea ice leads are important sites of energy fluxes in the Arctic Ocean, which may play an important role in the evolution of Arctic sea ice. In this study, we examine the potential of sea ice leads as a predictor for summer Arctic sea ice extent forecast using a recently developed daily sea ice lead product retrieved from the Moderate-Resolution Imaging Spectroradiometer (MODIS). Our results show that July pan-Arctic sea ice extent can be predicted from the area of sea ice leads integrated from midwinter to late spring, with a prediction error of 0.28 million km2 that is smaller than the standard deviation of the observed interannual variability. However, the predictive skills for August and September pan-Arctic sea ice extent are very low. When the area of sea ice leads integrated in the Atlantic and central and west Siberian sector of the Arctic is used, it has a significantly strong relationship (high predictability) with both July and August sea ice extent in the Atlantic and central and west Siberian sector of the Arctic. Thus, the realistic representation of sea ice leads (e.g., the areal coverage) in numerical prediction systems might improve the skill of forecast in the Arctic region.

scholarly journals The role of moisture transport for precipitation in the inter-annual and inter-daily fluctuations of the Arctic sea ice extension

2019 ◽  
Vol 10 (1) ◽  
pp. 121-133 ◽  
Author(s):  
Luis Gimeno-Sotelo ◽  
Raquel Nieto ◽  
Marta Vázquez ◽  
Luis Gimeno
Keyword(s):  
Sea Ice ◽  
Moisture Transport ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Melting ◽  
Sea Ice Extent ◽  
Moisture Sources ◽  
Arctic Sea

Abstract. By considering the moisture transport for precipitation (MTP) for a target region to be the moisture that arrives in this region from its major moisture sources and which then results in precipitation in that region, we explore (i) whether the MTP from the main moisture sources for the Arctic region is linked with inter-annual fluctuations in the extent of Arctic sea ice superimposed on its decline and (ii) the role of extreme MTP events in the inter-daily change in the Arctic sea ice extent (SIE) when extreme MTP simultaneously arrives from the four main moisture regions that supply it. The results suggest (1) that ice melting at the scale of inter-annual fluctuations against the trend is favoured by an increase in moisture transport in summer, autumn, and winter and a decrease in spring and, (2) on a daily basis, extreme humidity transport increases the formation of ice in winter and decreases it in spring, summer, and autumn; in these three seasons extreme humidity transport therefore contributes to Arctic sea ice melting. These patterns differ sharply from that linked to the decline on a long-range scale, especially in summer when the opposite trend applies, as ice melt is favoured by a decrease in moisture transport for this season at this scale.

scholarly journals Future emissions from oil, gas, and shipping activities in the Arctic

2011 ◽  
Vol 11 (2) ◽  
pp. 4913-4951 ◽  
Author(s):  
G. P. Peters ◽  
T. B. Nilssen ◽  
L. Lindholt ◽  
M. S. Eide ◽  
S. Glomsrød ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Oil And Gas ◽  
Arctic Region ◽  
Gas Production ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Emission Inventories ◽  
Oil And Gas Production ◽  
The Arctic Region

Abstract. The Arctic sea-ice is retreating faster than predicted by climate models and could become ice free during summer this century. The reduced sea-ice extent may effectively "unlock" the Arctic Ocean to increased human activities such as transit shipping and expanded oil and gas production. Travel time between Europe and the north Pacific Region can be reduced by up to 50% with low sea-ice levels and the use of this route could increase substantially as the sea-ice retreats. Oil and gas activities already occur in the Arctic region and given the large undiscovered petroleum resources increased activity could be expected with reduced sea-ice. We use a detailed global energy market model and a bottom-up shipping model with a sea-ice module to construct emission inventories of Arctic shipping and petroleum activities in 2030 and 2050. The emission inventories are on a 1× 1 degree grid and cover both short-lived pollutants and ozone pre-cursors (SO2, NOx, CO, NMVOC, BC, OC) and the long-lived greenhouse gases (CO2, CH4, N2O). We find rapid growth in transit shipping due to increased profitability with the shorter transit times compensating for increased costs in traversing areas of sea-ice. Oil and gas production remains relatively stable leading to reduced emissions from emission factor improvements. The location of oil and gas production moves into locations requiring more ship transport relative to pipeline transport, leading to rapid emissions growth from oil and gas transport via ship. Our emission inventories for the Arctic region will be used as input into chemical transport, radiative transfer, and climate models to quantify the role of Arctic activities in climate change compared to similar emissions occurring outside of the Arctic region.

scholarly journals The potential of sea ice leads as a predictor for seasonal Arctic sea ice extent prediction

2018 ◽  
Author(s):  
Yuanyuan Zhang ◽  
Xiao Cheng ◽  
Jiping Liu ◽  
Fengming Hui
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Strong Relationship ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Leads ◽  
Arctic Sea Ice Extent

Abstract. The Arctic sea ice extent throughout the melt season is closely associated with initial sea ice state in winter and spring. Sea ice leads are important sites of energy fluxes in the Arctic Ocean, which may play an important role in the evolution of Arctic sea ice. In this study, we examine the potential of sea ice leads as a predictor for seasonal Arctic sea ice extent forecast using a recently developed daily sea ice leads product retrieved from Moderate-Resolution Imaging Spectroradiometer. Our results show that July pan-Arctic sea ice extent can be accurately predicted from the area of sea ice leads integrated from mid-winter to late spring. However, the predictive skills for August and September pan-Arctic sea ice extent are very low. When the area of sea ice leads integrated in the Atlantic and central and west Siberian sector of the Arctic is used, it has a significantly strong relationship (high predictability) with both July and August sea ice extent in the Atlantic and central and west Siberian sector of the Arctic. Thus, the realistic representation of sea ice leads (e.g., the areal coverage) in numerical prediction systems might improve the skill of forecast in the Arctic region.

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