A link between sea ice concentration in Kara Sea in November and large scale atmospheric circulation

Author(s):  
Karim A. Shukurov ◽  
Vladimir A. Semenov
2019 ◽  
Vol 65 (2) ◽  
pp. 125-147
Author(s):  
I. D. Rostov ◽  
E. V. Dmitrieva ◽  
N. I. Rudykh ◽  
A. A. Vorontsov

The paper discusses air (Ta) and sea surface temperature (SST) year-to-year variability due to warming of the Kara Sea, using the data from regular observations at the meteorological stations Roshydromet (GMS) in 1978–2017, NOAA optimum interpolation and reanalysis data. We use the methods of cluster, correlation analysis and Empirical Orthogonal Functions (EOF). We investigate possible cause and effect relationships of these changes with the variations of the wind field components, climatic indices and the sea ice concentration field. The cluster analysis of the three main EOF components has allowed us to identify four areas on the basis of the nature of changes of the water temperature anomalies field. The climatic changes in these areas, in the coastal and island zones of the Kara Sea have manifested themselves in the steady increase of the annual air temperature at GMS from 0,47–0,77 °C/10 years on the southwest coast to 1,33–1,49 °C/10 years in the north of the sea. This is equivalent to warming from 1,9 to 6,0 °C in the last 40 years. For the open sea the value of the Ta trend is about 1,22 °C/10 years, which corresponds to an increase in the average Ta by 4,9 °C in the last 40 years. This value is approximately 3 times greater than that for all the Northern hemisphere for the same period.Annualy, the maximal trend was observed in November and April mainly and exceeded 2–3 °C/10 years at some of the stations. We identify anomalously warm (2016 and 2012) and anomalously cold (1978, 1979, 1992 and 1998) years: the warmest year was 2012, the coldest — 1979. Positive SST trends were observed over all the sea area during the warm period of year (to 1 °C/10 years). SST increased to 2,4 °C, which is approximately 1,5 times greater than the corresponding SST values for the Northern hemisphere. The maximum SST trend (0,4 °C/10 years) was observed in the northwest and southwest parts of the sea. From June to August the trends of SST exceed the annual ones 1,5–2 times. Interannual SST and Ta variations are characterized by close correlation links. Until approximately 1998–2004 the warming was rather insignificant, and after that the growth rate of Ta and SST increased many fold. Apparently it indicates changes in the mode and the large-scale atmospheric circulation in the early 2000s. We also observed a trend of strengthening of the southern wind during the cold period of the year and the northern one — in the warm period (0,5–0,6 m/s in 40 years). It is shown that there is a close correlation between the Ta increase and the changes in the meridional component of the wind speed during the cold period of the year for all the sea areas. For the warm period it is statistically insignificant both for Ta and SST. For the cold season we observed a contribution of the large-scale mode of atmospheric circulation into the variability of V component of the wind speed. The conribution was expressed through the indeces NAO, SCAND, Pol/EUR, AZOR, ISL and the differences of ISLSIB. For the warm season this contribution is expressed through the NAO, SCAND and AO only. For the warm period we showed statistically significant correlation between the increase in SST, Ta and the processes parametrized by the AMO, EA/WR and AZOR indeces. For the cold period the indeces are AMO, Pol/Eur, SIB and ISL SIB. The interannual variations of the sea ice concentration field are characterized by close correlation with Ta changes both in the annual cycle and during the periods of ice cover formation and evolution (R = –0,7... –0,9). For these periods we showed statistically significant relationships between the first EOF mode fluctuations and two climatic indeces — AMO (R = 0,5) and Pol/Eur (R = 0,4). The relationships between the temporary variability of the sea ice concentration and the wind field characteristics are weaker and statistically significant only for the meridional component of the wind speed (R = –0,4).


1984 ◽  
Vol 5 ◽  
pp. 61-68 ◽  
Author(s):  
T. Holt ◽  
P. M. Kelly ◽  
B. S. G. Cherry

Soviet plans to divert water from rivers flowing into the Arctic Ocean have led to research into the impact of a reduction in discharge on Arctic sea ice. We consider the mechanisms by which discharge reductions might affect sea-ice cover and then test various hypotheses related to these mechanisms. We find several large areas over which sea-ice concentration correlates significantly with variations in river discharge, supporting two particular hypotheses. The first hypothesis concerns the area where the initial impacts are likely to which is the Kara Sea. Reduced riverflow is associated occur, with decreased sea-ice concentration in October, at the time of ice formation. This is believed to be the result of decreased freshening of the surface layer. The second hypothesis concerns possible effects on the large-scale current system of the Arctic Ocean and, in particular, on the inflow of Atlantic and Pacific water. These effects occur as a result of changes in the strength of northward-flowing gradient currents associated with variations in river discharge. Although it is still not certain that substantial transfers of riverflow will take place, it is concluded that the possibility of significant cryospheric effects and, hence, large-scale climate impact should not be neglected.


2013 ◽  
Vol 9 (6) ◽  
pp. 6515-6549 ◽  
Author(s):  
F. Klein ◽  
H. Goosse ◽  
A. Mairesse ◽  
A. de Vernal

Abstract. The consistency between a new quantitative reconstruction of Arctic sea-ice concentration based on dinocyst assemblages and the results of climate models has been investigated for the mid-Holocene. The comparison shows that the simulated sea-ice changes are weaker and spatially more homogeneous than the recorded ones. Furthermore, although the model-data agreement is relatively good in some regions such as the Labrador Sea, the skill of the models at local scale is low. The response of the models follows mainly the increase in summer insolation at large scale. This is modulated by changes in atmospheric circulation leading to differences between regions in the models that are albeit smaller than in the reconstruction. Performing simulations with data assimilation using the model LOVECLIM amplifies those regional differences, mainly through a reduction of the southward winds in the Barents Sea and an increase in the westerly winds in the Canadian Basin of the Arctic. This leads to an increase in the ice concentration in the Barents and Chukchi Seas and a better agreement with the reconstructions. This underlines the potential role of atmospheric circulation to explain the reconstructed changes during the Holocene.


2021 ◽  
Vol 13 (21) ◽  
pp. 4421
Author(s):  
Stefan Kern

The European Organisation for the Exploitation of Meteorological Satellites-Ocean and Sea Ice Satellite Application Facility–European Space Agency-Climate Change Initiative (EUMETSAT-OSISAF–ESA-CCI) Level-4 sea-ice concentration (SIC) climate data records (CDRs), named SICCI-25km, SICCI-50km and OSI-450, provide gridded SIC error estimates in addition to SIC. These error estimates, called total error henceforth, comprise a random, uncorrelated error contribution from retrieval and sensor noise, aka the algorithm standard error, and a locally-to-regionally correlated contribution from gridding and averaging Level-2 SIC into the Level-4 SIC CDRs, aka the representativity error. However, these CDRs do not yet provide an error covariance matrix. Therefore, correlation scales of these error contributions and the total error in particular are unknown. In addition, larger-scale SIC errors due to, e.g., unaccounted weather influence or mismatch between the actual ice type and the algorithm setup are neither well represented by the total error, nor are their correlation scales known for these CDRs. In this study, I attempt to contribute to filling this knowledge gap by deriving spatial correlation length scales for the total error and the large-scale SIC error for high-concentration pack ice. For every grid cell with >90% SIC, I derive circular one-point correlation maps of 1000 km radius by computing the cross-correlation between the central 31-day time series of the errors and all other 31-day error time series within that circular area (disc) with 1000 km radius. I approximate the observed decrease in the correlation away from the disc’s center with an exponential function that best fits this decrease and thereby obtain the correlation length scale L sought. With this approach, I derive L separately for the total error and the large-scale SIC error for every high-concentration grid cell, and map, present and discuss these for the Arctic and the Southern Ocean for the year 2010 for the above-mentioned products. I find correlation length scales are substantially smaller for the total error, mostly below ~200 km, than the SIC error, ~200 km to ~700 km, in both hemispheres. I observe considerable spatiotemporal variability of the SIC error correlation length scales in both hemispheres and provide first directions to explain these. For SICCI-50km, I present the first evidence of the method’s robustness for other years and time series of L for 2003–2010.


2017 ◽  
Author(s):  
Alexandru Gegiuc ◽  
Markku Similä ◽  
Juha Karvonen ◽  
Mikko Lensu ◽  
Marko Mäkynen ◽  
...  

Abstract. For navigation in Baltic Sea ice during winter season, parameters such as ice edge, ice concentration, ice thickness, ice drift and degree of ridging are usually reported daily in the manually prepared Ice Charts, which provide icebreakers essential information for route optimization and fuel calculations. However, manual ice charting requires long analysis times and detailed analysis is not possible for large scale maps (e.g. Arctic Ocean). Here, we propose a method for automatic estimation of degree of ridging density in the Baltic Sea region, based on RADARSAT-2 C-band dual-polarized (HH/HV channels) SAR texture features and the sea ice concentration information extracted from the Finnish Ice Charts. The SAR images were first segmented and then several texture features were extracted for each
 segment. Using the Random Forest classification, we classified them into four classes of ridging intensity and compared them to the reference data extracted from the digitized Ice Charts. The overall agreement between the ice chart based degree of ice ridging (DIR) and the automated results varied monthly, being 83 %, 63 % and 81 % in January, February and March 2013, respectively. The correspondence between the degree of ice riding of the manual Ice Charts and the actual ridge density was good when this issue was studied based on an extensive field campaign data in March 2011.


2019 ◽  
Vol 32 (9) ◽  
pp. 2553-2568 ◽  
Author(s):  
Yong Liu ◽  
Huopo Chen ◽  
Huijun Wang ◽  
Jianqi Sun ◽  
Hua Li ◽  
...  

Abstract Lake ice phenology, as an indicator for climate variability and change, exerts a great influence on regional climate and hydrometeorology. In this study, the changing characteristics of lake ice phenology at Lake Qinghai (LQH) are investigated using retrieved historical datasets during 1979–2016. The results show that the variation of the lake freeze-up date over LQH is characterized by a strong interannual variability. Further analysis has revealed that November sea ice concentration (SIC) variation in the Kara Sea can exert a great impact on the freeze-up date at LQH. During the low sea ice years, the open sea serves as a strong diabatic heating source, largely contributing to the enhanced Arctic Eliassen–Palmer flux, which then results in the deceleration of zonal wind in the middle and high latitudes. In addition to this, accompanied with the decreasing Kara SIC, the enhanced stationary Rossby wave flux propagating along the high-latitude regions may further exert remarkable influences in deepening the East Asian trough, which provides a favorable atmospheric circulation pattern for cold air intrusion from the Arctic and Siberian regions to mainland China. The decreased surface air temperature would thus advance the freezing date over LQH. Furthermore, the close relationship between atmospheric circulation anomalies and Kara SIC variations is validated by a large ensemble of simulations from the Community Earth System Model, and the atmospheric circulation patterns induced by the SIC anomalies are reproduced to some extent. Therefore, the November Kara Sea ice anomaly might be an important predictor for the variation in the freeze-up date at LQH.


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