@ARTICLE{Duan_Chenglin_Sea_2019,
 author={Duan, Chenglin and Dong, Sheng and Wang, Zhifeng},
 volume={vol. 40},
 number={No 3},
 journal={Polish Polar Research},
 pages={205-225},
 howpublished={online},
 year={2019},
 publisher={Polish Academy of Sciences},
 publisher={Committee on Polar Research},
 abstract={In this paper, the recent ice regime variations in the Kara Sea have been described and quantified based on the high-resolution remote sensing database from 2003 to 2017. In general, the Kara Sea is fully covered with thicker sea ice in winter, but sea ice cover is continuously declining during the summer. The year 2003 was the year with the most severe ice conditions, while 2012 and 2016 were the least severe. The extensive sea ice begins to break up before May and becomes completely frozen at the end of December again. The duration of ice melting is approximately twice than that of the freezing. Since 2007, the minimum ice coverage has always been below 5%, resulting in wide open-waters in summer. Furthermore, the relevant local driving factors of external atmospheric forcing on ice conditions have been quantitatively calculated and analyzed. Winter accumulated surface air temperature has been playing a primary role on the ice concentration and thickness condition in winter and determining ice coverage index in the following melt-freeze stage. Correlation coefficients between winter accumulated temperature and ice thickness anomaly index, the ice coverage anomaly index, duration of melt-freeze stage can approach -0.72, -0.83 and 0.80, respectively. In summer, meridional winds contribute closely to summer ice coverage anomaly index, with correlation coefficient exceeding 0.80 since 2007 and 0.90 since 2010.},
 type={Article},
 title={Sea ice regime in the Kara Sea during 2003–2017 based on high-resolution satellite data},
 URL={http://ochroma.man.poznan.pl/Content/113182/PDF/PPR%203-19%202-C.Duan.pdf},
 doi={10.24425/ppr.2019.129671},
 keywords={Arctic, ice regime, spatio-temporal variation, ice coverage anomaly index, atmospheric forcing factor, correlation analysis},
}