scholarly journals Wintertime Cold Extremes in Northeast China and Their Linkage with Sea Ice in Barents-Kara Seas

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 386
Author(s):  
Yongyue Luo ◽  
Chun Li ◽  
Jian Shi ◽  
Xiadong An ◽  
Yaqing Sun

The impacts of Arctic sea ice on the interannual variability of winter extreme low temperature (WELT) in Northeast China (NEC) and the associated atmospheric circulation patterns are explored in this study based on meteorological observation and the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP/NCAR) reanalysis data. Results show that WELT in NEC has prominent interannual variability. We further use ±0.8 standard deviation as the threshold to select the years of frequent and rare extreme low temperature anomalies. Using composite analysis, we find that there are significant negative geopotential height anomalies at 500 hPa over NEC and positive geopotential height anomalies along the Arctic region, which represent the intensification of the East Asian trough (EAT) and the negative Arctic Oscillation (AO) phase in the years of more frequent WELT. The opposite characteristics are detected in the years of rare WELT. Furthermore, we determine that the Barents-Kara Seas are key sea ice regions in Arctic area. In the years of frequent WELT, the decrease of autumn Barents-Kara Seas sea ice and the positive sea surface temperature anomaly can last until the following winter, which is conducive to the intensification of anticyclonic anomalies in Ural regions and the northward extension of Ural ridge (UR). The northerly flow in front of UR guides the cold air penetrating southward from polar regions. Moreover, the anomalous cyclone over East Asia deepens the EAT. The northerly wind behind EAT guides the cold air to the NEC region, causing the wintertime low temperature there. The almost opposite situation occurs in the years of rare WELT.

2020 ◽  
Vol 12 (7) ◽  
pp. 1060 ◽  
Author(s):  
Lise Kilic ◽  
Catherine Prigent ◽  
Filipe Aires ◽  
Georg Heygster ◽  
Victor Pellet ◽  
...  

Over the last 25 years, the Arctic sea ice has seen its extent decline dramatically. Passive microwave observations, with their ability to penetrate clouds and their independency to sunlight, have been used to provide sea ice concentration (SIC) measurements since the 1970s. The Copernicus Imaging Microwave Radiometer (CIMR) is a high priority candidate mission within the European Copernicus Expansion program, with a special focus on the observation of the polar regions. It will observe at 6.9 and 10.65 GHz with 15 km spatial resolution, and at 18.7 and 36.5 GHz with 5 km spatial resolution. SIC algorithms are based on empirical methods, using the difference in radiometric signatures between the ocean and sea ice. Up to now, the existing algorithms have been limited in the number of channels they use. In this study, we proposed a new SIC algorithm called Ice Concentration REtrieval from the Analysis of Microwaves (IceCREAM). It can accommodate a large range of channels, and it is based on the optimal estimation. Linear relationships between the satellite measurements and the SIC are derived from the Round Robin Data Package of the sea ice Climate Change Initiative. The 6 and 10 GHz channels are very sensitive to the sea ice presence, whereas the 18 and 36 GHz channels have a better spatial resolution. A data fusion method is proposed to combine these two estimations. Therefore, IceCREAM will provide SIC estimates with the good accuracy of the 6+10GHz combination, and the high spatial resolution of the 18+36GHz combination.


2016 ◽  
Vol 97 (11) ◽  
pp. 2163-2176 ◽  
Author(s):  
Abhay Devasthale ◽  
Joseph Sedlar ◽  
Brian H. Kahn ◽  
Michael Tjernström ◽  
Eric J. Fetzer ◽  
...  

Abstract Arctic sea ice is declining rapidly and its annual ice extent minima reached record lows twice during the last decade. Large environmental and socioeconomic implications related to sea ice reduction in a warming world necessitate realistic simulations of the Arctic climate system, not least to formulate relevant environmental policies on an international scale. However, despite considerable progress in the last few decades, future climate projections from numerical models still exhibit the largest uncertainties over the polar regions. The lack of sufficient observations of essential climate variables is partly to blame for the poor representation of key atmospheric processes, and their coupling to the surface, in climate models. Observations from the hyperspectral Atmospheric Infrared Sounder (AIRS) instrument on board the National Aeronautics and Space Administration (NASA)’s Aqua satellite are contributing toward improved understanding of the vertical structure of the atmosphere over the poles since 2002, including the lower troposphere. This part of the atmosphere is especially important in the Arctic, as it directly impacts sea ice and its short-term variability. Although in situ measurements provide invaluable ground truth, they are spatially and temporally inhomogeneous and sporadic over the Arctic. A growing number of studies are exploiting AIRS data to investigate the thermodynamic structure of the Arctic atmosphere, with applications ranging from understanding processes to deriving climatologies—all of which are also useful to test and improve parameterizations in climate models. As the AIRS data record now extends more than a decade, a select few of many such noteworthy applications of AIRS data over this challenging and rapidly changing landscape are highlighted here.


2018 ◽  
Author(s):  
Monica Ionita ◽  
Klaus Grosfeld ◽  
Patrick Scholz ◽  
Renate Treffeisen ◽  
Gerrit Lohmann

Abstract. Sea ice in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad interest exists on sea ice coverage, variability and long term change. However, its predictability is complex and it depends on various atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we developed a robust statistical model based on oceanic and different atmospheric variables to calculate an estimate of the September sea ice extent (SSIE) on monthly time scale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' atmospheric and oceanic conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea ice formation.


MAUSAM ◽  
2021 ◽  
Vol 62 (4) ◽  
pp. 609-616
Author(s):  
AMITA PRABHU ◽  
P.N. MAHAJAN ◽  
R.M. KHALADKAR

The development in the satellite microwave technology during the past three decades has offered an opportunity to the scientific community to access the sea ice data over the polar regions, which was otherwise inaccessible for continuous monitoring by any other means. The present study focuses on the trends in the Sea Ice Extent (SIE) over different sectors of the Arctic and the Antarctic regions and the interannual variability in their extremes. In general, the data over the period (1979-2007) reveal marked interannual variability in the sea ice cover with an increasing and the decreasing trend over the Antarctic and the Arctic region respectively. Over the southern hemisphere, only the Bellingshausen and Amundsen Seas sector shows an exceptional decreasing trend. However, in the northern hemisphere, all the sectors show a decreasing trend, with the Kara and Barents Seas sector being the most prominent one. Although, the decreasing trend of the SIE over the Arctic could be attributed to the global warming, an intriguing question still remains as to why the other polar region shows a different behaviour.


2020 ◽  
Vol 33 (11) ◽  
pp. 4907-4925 ◽  
Author(s):  
Xiaoye Yang ◽  
Gang Zeng ◽  
Guwei Zhang ◽  
Zhongxian Li

AbstractThe paths of winter cold surge (CS) events in East Asia (EA) from 1979 to 2017 are tracked by the Flexible Particle (FLEXPART) model using ERA-Interim daily datasets, and the probability density distribution of the paths is calculated by the kernel density estimation (KDE) method. The results showed that the paths of CSs are significantly correlated with the intensity of the CSs, which shows an interdecadal transition from weak to strong around 1995. CS paths can be classified into two types, namely, the western path type and the northern path type, which were more likely to occur before and after 1995, respectively. Before 1995, the cold air mainly originated from Europe and moved from west to east, and the synoptic features were associated with the zonal wave train. After 1995, cold air accumulated over western Siberia and then invaded EA along the northern path, and the synoptic features were mainly associated with the blocking structure. The geopotential height (GPH) anomalies over the Arctic were abnormally strong. This paper further analyzes the relationship between CSs and winter sea ice concentration (SIC) in the Arctic. The results show that the intensity of CSs is negatively correlated with the Barents SIC (BSIC). When the BSIC declines, the upward wave flux over the Barents Sea is enhanced and expanded to the midlatitude region. GPH anomalies over the Arctic are positive and form a negative AO-like pattern, which is conducive to the formation of the northern path CS. Furthermore, the observed results are supported by numerical experiments with the NCAR Community Atmosphere Model, version 5.3 (CAM5.3).


2019 ◽  
Vol 11 (12) ◽  
pp. 1490 ◽  
Author(s):  
Chengfei Jiang ◽  
Mingsen Lin ◽  
Hao Wei

When the Haiyang-2B (HY-2B) was launched into space to form a star network with the Haiyang-2A (HY-2A), it provided new data sources for the sea ice research of the Earth’s polar regions. The ability of altimeter echoes to distinguish sea ice and sea water is usable in operational ice charting. In this research study, the level 1B (L1B) data of HY-2A/B altimeter from November 2018 was used to analyze the altimeter waveforms from the polar regions. The Suboptimal Maximum Likelihood Estimation (SMLE) and Offset Center of Gravity (OCOG) tracking packages could maintain the waveform characteristics of diffused and quasi-specular surfaces by comparison. Also, they could be utilized to distinguish sea ice from seawater in the polar regions. It was determined that the types of echoes obtained from the seawater were diffuse. Also, some “ocean-like” waveform data had existed for the old ice formations in the Arctic regions during the study period. The types of echoes obtained from Arctic sea ice were found to be mainly quasi-specular. In the present study, three methods (Threshold segmentation, K-nearest-neighbor (KNN), and Lib-Support Vector machine (LIBSVM)) with four waveform parameters (Automatic Gain Control (AGC) and Pulse Peaking (PP) values of the Ku and C Bands) were adopted to distinguish between the sea ice and seawater areas. The accuracy rate of the separation results for the LIBSVM except band Ku from HY-2B ALT was found to be less than 40% in Antarctic. Meanwhile, the other two methods were observed to have maintained the waveforms correctly at accuracy rates of approximately 80% in Antarctic and the Arctic. In addition, the observed distinguishing errors were located in the regions of the old ice of the Arctic region. In addition, due to the summer melting processes, the large number of ice floes and the snow cover had made it difficult to distinguish the seawater and sea ice in the Antarctic regions.


2020 ◽  
pp. 1-67
Author(s):  
Shuoyi Ding ◽  
Bingyi Wu ◽  
Wen Chen

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.


2016 ◽  
Vol 29 (2) ◽  
pp. 401-417 ◽  
Author(s):  
Russell Blackport ◽  
Paul J. Kushner

Abstract The impact that disappearing Arctic sea ice will have on the atmospheric circulation and weather variability remains uncertain. In this study, results are presented from a sea ice perturbation experiment using the coupled Community Climate System Model, version 4 (CCSM4). By decreasing the albedo of the sea ice, the impact of an ice-free summertime Arctic on the coupled ocean–atmosphere system is isolated in an idealized but energetically self-consistent way. The multicentury equilibrium response is examined, as well as the transient response in an initial condition ensemble. The perturbation drives pronounced year-round sea ice thinning, Arctic warming, Arctic amplification, and moderate global warming. Even in the almost complete absence of summertime sea ice, the atmospheric general circulation response is very weak and the transient response is small compared to the internal variability. Surface temperature variability is reduced on all time scales over most of the middle and high latitudes with a 50% reduction in the standard deviation of temperature over the Arctic Ocean. The reduction is attributed to decreased temperature gradients and increased maritime influence once the sea ice melts. This reduced variability extends weakly into the variability of the midlatitude and free tropospheric geopotential height (less than 10% reduction in the standard deviation). Consistently, eddy geopotential height variability is found to decrease while geopotential isopleth meandering, which reflects Arctic amplified warming, increases moderately. The sign of these changes is consistent with recent observations, but the size of these changes is relatively small.


Author(s):  
Stephan Juricke ◽  
Thomas Jung

The influence of a stochastic sea ice strength parametrization on the mean climate is investigated in a coupled atmosphere–sea ice–ocean model. The results are compared with an uncoupled simulation with a prescribed atmosphere. It is found that the stochastic sea ice parametrization causes an effective weakening of the sea ice. In the uncoupled model this leads to an Arctic sea ice volume increase of about 10–20% after an accumulation period of approximately 20–30 years. In the coupled model, no such increase is found. Rather, the stochastic perturbations lead to a spatial redistribution of the Arctic sea ice thickness field. A mechanism involving a slightly negative atmospheric feedback is proposed that can explain the different responses in the coupled and uncoupled system. Changes in integrated Antarctic sea ice quantities caused by the stochastic parametrization are generally small, as memory is lost during the melting season because of an almost complete loss of sea ice. However, stochastic sea ice perturbations affect regional sea ice characteristics in the Southern Hemisphere, both in the uncoupled and coupled model. Remote impacts of the stochastic sea ice parametrization on the mean climate of non-polar regions were found to be small.


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