scholarly journals Impact of Arctic sea ice variations on winter temperature anomalies in northern hemispheric land areas

2018 ◽  
Vol 52 (5-6) ◽  
pp. 3111-3137 ◽  
Author(s):  
T. Koenigk ◽  
Y. Gao ◽  
G. Gastineau ◽  
N. Keenlyside ◽  
T. Nakamura ◽  
...  
2019 ◽  
Vol 32 (16) ◽  
pp. 5021-5035 ◽  
Author(s):  
Thomas W. Collow ◽  
Wanqiu Wang ◽  
Arun Kumar

Abstract In this study, we investigate links between Arctic sea ice loss and the variability of 2-m temperatures over a 6-month period (November–April) over two domains centered over northern Eurasia and northern North America. Based on data from the Climate Forecast System Reanalysis (CFSR), there has been an increase (a decrease) in recent seasonal temperature variability over Eurasia (North America), which can be attributed to cooling (warming) during the winter months. Decreases in the intraseasonal variability of temperature anomalies, however, are noted in both regions for the November–April period. This study investigates the role of different forcings on the changes seen in the reanalysis product using Atmospheric Model Intercomparison Project simulations forced with repeating sea surface temperature, sea ice, and carbon dioxide concentration relative to climatologies from two different base periods, 1981–90 and 2005–14. The seasonal temperature and intraseasonal anomaly variabilities are examined, and we find that only the simulations with reduction in sea ice (2005–14 base-period sea ice concentration) produce significant decreases in intraseasonal temperature anomaly variability over these regions, agreeing with the CFSR analysis. Runs that reduce sea ice also result in a significant decrease in the frequency and magnitude of extreme warm and cold temperature anomalies. It is proposed that the weakened latitudinal temperature gradient, resulting from decreased sea ice, leads to reduced meridional temperature advection variability, which in turn contributes to the reduction in the variability of temperature anomalies.


Author(s):  
Bingyi Wu ◽  
Zhenkun Li ◽  
Jennifer A. Francis ◽  
Shuoyi Ding

Abstract Arctic warming and its association with the mid-latitudes have been hot topic over the past two decades. Although many studies have explored these issues it is not clear that how their linkage has changed over time. The results show that winter low tropospheric temperatures in Asia experienced two phases over the past two decades. Phase I (2007/2008 to 2012/2013) was characterized by a warm Arctic and cold Eurasia, and phase II by a warm Arctic and warm Eurasia (2013/2014 to 2018/2019). A strengthened association in winter temperature between the Arctic and Asia occurred during phase I, followed by a weakened linkage during phase II. Simulation experiments forced by observed Arctic sea ice variability largely reproduce observed patterns, suggesting that Arctic sea ice loss contributes to phasic (or low-frequency) variations in winter atmosphere and make the Arctic-Asia temperature association fluctuate over time. The weakening of the Arctic-Asia linkage post-2012/2013 was associated with amplified and expanded Arctic warming. The corresponding anomalies in SLP resembled a positive phase North Atlantic Oscillation (NAO) during phase II. This study implies that the phasic warm Arctic-cold Eurasia and warm Arctic-warm Eurasia patterns would alternately happen in the context of Arctic sea ice loss, which increase the difficulty to correctly predict Asian winter temperature.


2020 ◽  
Author(s):  
Esther C. Brady ◽  
Bette L. Otto-Bliesner ◽  
Masa Kageyama ◽  

<p>New to CMIP6 is the Tier 1 lig127k experiment, designed to address the climate responses to stronger orbital forcing than the midHolocene experiment, using the same state-of-the-art models and following a common experimental protocol. We present a multi-model ensemble of 17 climate models, all of which (except for two) have also completed the CMIP6 DECK experiments, looking at the lig127k Arctic’s responses across models and the relationships with each model’s Equilibrium Climate Sensitivity (ECS), preindustrial sea ice thickness and 127ka temperature anomalies.</p><p>Boreal insolation anomalies at 127 ka enhance the seasonal cycle of Arctic sea ice, though with notable differences among the models. The consensus from the lig127k sea ice distributions is a reduced minimum (August-September) summer sea ice extent in the Arctic as compared to the piControl simulations. Sea ice remains above 15% concentrations over the central Arctic Ocean in all but one of the lig127k simulations. More than half of the models simulate a retreat of the Arctic minimum ice edge similar to the average of the last 2 decades. The lig127k minimum Arctic sea ice area anomalies show a strong negative correlation with the Arctic (60-90°N) annual surface temperature anomalies but only a weak correlation with the corresponding June-July-August (JJA) temperature anomalies. Memory in the ocean and cryosphere provide feedbacks to maintain larger positive temperature anomalies, December-January-February (DJF) and annually, in the Arctic than in JJA. The models contributing to the lig127k ensemble have an ECS varying from 2.1 to 5.3°C. There is a notable relationship between the ECS and simulation of lig127k minimum Arctic sea ice area.  With very limited Arctic sea ice proxies for 127 ka, and with evolving interpretation of the relationships of these proxies with sea ice coverage, it is still difficult to rule out the high or low values of ECS from the proxy data.</p>


2017 ◽  
Vol 36 (8) ◽  
pp. 52-58 ◽  
Author(s):  
Cuijuan Sui ◽  
Zhanhai Zhang ◽  
Lejiang Yu ◽  
Yi Li ◽  
Mirong Song

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Chuhan Lu ◽  
Kaili Li ◽  
Shaoqing Xie ◽  
Zhaomin Wang ◽  
Yujing Qin

The variation of autumn Arctic sea ice is a critical indicator of temperature anomalies over the Eurasian continent during winter. The retreat of autumn Arctic sea ice is typically accompanied by negative anomalous winter temperatures over the Eurasian and North American continents. However, such sea ice temperature linkages notably change from month to month. The variation of the autumn Arctic sea ice area and the relationship between the month-to-month sea ice and winter temperature anomalies in China are investigated using the Hadley Centre’s sea ice dataset (HadiSST) and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset (ERA-Interim) during 1979–2018. We present the following results: The sea ice in the Barents and Kara seas (BK) during the autumn and winter seasons shows notable low-frequency variability. The retreat of sea ice in the BK from September to November is significantly associated with negative temperature anomalies in the following winter in China. However, the linkage between the sea ice in the BK in September and the winter temperatures is stronger than that in both October and November. An anomalous positive surface pressure is exhibited over the northwestern part of Eurasia in the winter that is linked to decreasing sea ice in the BK in the preceding September. This surface pressure favors the persistence and intensification of synoptic perturbations, such as blocking highs and surface cold highs, as well as the intensification of the Siberian High and the East Asian winter monsoon. These favorable conditions ultimately contribute to the formation of large-scale winter cold anomalies in China. Compared to low sea ice cover in October and November, a more oceanic heat storage in the upper BK induced by low sea ice cover in the BK leads to a larger heat release to tropospheric atmosphere in winter by surface heat flux and upward longwave radiation in the BK. This regional tropospheric warming results in a higher barotropic positive height anomaly over the Ural Mountains, and then more active cold advection from the high latitude affects East Asia.


2016 ◽  
Vol 47 (7-8) ◽  
pp. 2331-2343 ◽  
Author(s):  
Jinqing Zuo ◽  
Hong-Li Ren ◽  
Bingyi Wu ◽  
Weijing Li

2020 ◽  
pp. 024
Author(s):  
Rym Msadek ◽  
Gilles Garric ◽  
Sara Fleury ◽  
Florent Garnier ◽  
Lauriane Batté ◽  
...  

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.


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