Ice-free period detection uncertainties over the coastal  zones

Shabanov, P.A.; Shabanova, N.N.; Ogorodov, S.A.

Авторы: Shabanov P.A., Shabanova N.N., Ogorodov S.A.
Сборник: Proceedings of the 14th International MEDCOAST Congress on Coastal and Marine Sciences, Engineering, Management and Conservation
Серия: MEDCOAST 2019
Том: 2
Год издания: 2019
Место издания: Mediterranean Coastal Foundation Grand Yazici Club Turban Hotel, Marmaris, Turkey
Первая страница: 663
Последняя страница: 674
Аннотация: The ice-free period detection uncertainties are reviewed using satellite-derived sea ice concentration data. A case study of Marresalya, western Yamal Peninsula, the Kara Sea is considered. The ice-free period characteristics, obtained from four satellite sea ice concentration datasets with different spatial resolution and algorithms, were tested for sensitivity to averaging radius (range from 15 km to 50 km with 5 km lag) and were compared with observations from Marresalya station. We found, that the accuracy of ice-free period characteristics estimations (in terms of root mean square errors and linear tendencies) could be improved by averaging sea ice concentration data in radius 25-40 km. It was also shown, that the NSIDC datasets provides the best estimations despite the coarse spatial resolution. High-resolution data (< 10 km) include too much interannual noises in the nearshore pixel time series. It complicates ice-free period characteristics estimations. The satellite sea ice concentration datasets comparison shows the weak linkage of ice-free period characteristics estimations to averaging radius in terms of root mean square errors and reveals medium sensitivity in a case of tendencies estimations. Due to critical data noises in OSI SAF data in the coastal zone before 1987 and high interannual variations in sea ice concentrations in ASI AMSR-E and ASI SSM/I time series, the NSIDC dataset provides the best conditions to ice-free period estimations. Such concentration data could be successfully used in Arctic coastal zones. As was shown by authors on IGARSS 2019 conference presentation, ensemble approach provides better results than NSIDC only. Ensemble estimations, which include ASI SSM/I and ASI AMSR/E data, are closer to observations and reproduce the main tendencies in ice-free period changes during the last 35 years near Marresalya. It is as an additional method to improve the accuracy of ice-free period characteristics estimations, which could be combined with pixels averaging approach.
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