2017年夏季北极中央航道海冰观测特征及海冰密集度遥感产品评估
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摘要
2017年夏季中国第八次北极科学考察期间,"雪龙"号极地考察船首次成功穿越北极中央航道,期间全程开展了海冰要素的人工观测。中央航道走航期间的平均海冰密集度和平均冰厚分别为0.64和1.5 m,海冰密集度时空变化大且以厚当年冰为主,高纬密集冰区的浮冰大小显著高于海冰边缘区。基于"雪龙"号的船基走航观测海冰密集度评估比较了国际上常用的5种常用的微波遥感反演海冰密集度产品,同走航目测海冰密集度点对点的比较,误差最大的为德国不来梅大学AMSR2基于Bootstrap算法的产品,平均误差和均方根误差分别为0.19和0.28;误差最小的为欧洲气象卫星应用组织基于AMSR2数据和OSHD和TUD两种不同算法的产品,平均误差分别为-0.02和0.01,均方根误差均为0.20。从日平均比较来看,AMSR2基于Bootstrap算法的误差最大,平均误差和均方根误差分别为0.15和0.20;AMSR2/OSI SAF(TUD)的误差最小,平均误差和均方根误差分别为0.0和0.11,OSI SAF产品更接近人工观测结果。
In summer 2017, for the first time, the Chinese R/V Xuelong successfully passed through the Central Arctic Passage(CAP) during the Chinese National Arctic Research Expedition(CHINARE 2017), the ship-based sea ice observations were carried out during this cruise. The results showed that the CAP was mainly occupied by thick first-year ice, the average sea ice concentration(SIC) and thickness along the CAP were 0.64 and 1.5 m, respectively; the ice floes in the central Arctic Ocean are significantly larger than the sea ice edge area. The 5 commonly used passive microwave satellite retrieved SIC datasets with a spatial resolution higher than 10 km were inter-compared and assessed using the ship-based SIC. The point to point comparison showed the AMSR2 SIC datasets(Bootstrap algorithm) released by University of Bremen had the largest bias and rms(root mean square) values with 0.19 and 0.28, while the AMSR2 SIC datasets(OSHD and TUD algorithm, respectively) released by Ocean and Sea Ice Satellite Application Facility(OSI SAF) were with the smallest bias of-0.02 and 0.01, and the rms values were both 0.20. The daily mean comparison showed that the AMSR2 SIC dataset(Bootstrap algorithm) released by University of Bremen and the AMSR2/OSI SAF(TUD) dataset had the largest(0.15 and 0.20) and smallest(0.0 and 0.11) mean bias and rms values, respectively.
In summer 2017, for the first time, the Chinese R/V Xuelong successfully passed through the Central Arctic Passage(CAP) during the Chinese National Arctic Research Expedition(CHINARE 2017), the ship-based sea ice observations were carried out during this cruise. The results showed that the CAP was mainly occupied by thick first-year ice, the average sea ice concentration(SIC) and thickness along the CAP were 0.64 and 1.5 m, respectively; the ice floes in the central Arctic Ocean are significantly larger than the sea ice edge area. The 5 commonly used passive microwave satellite retrieved SIC datasets with a spatial resolution higher than 10 km were inter-compared and assessed using the ship-based SIC. The point to point comparison showed the AMSR2 SIC datasets(Bootstrap algorithm) released by University of Bremen had the largest bias and rms(root mean square) values with 0.19 and 0.28, while the AMSR2 SIC datasets(OSHD and TUD algorithm, respectively) released by Ocean and Sea Ice Satellite Application Facility(OSI SAF) were with the smallest bias of-0.02 and 0.01, and the rms values were both 0.20. The daily mean comparison showed that the AMSR2 SIC dataset(Bootstrap algorithm) released by University of Bremen and the AMSR2/OSI SAF(TUD) dataset had the largest(0.15 and 0.20) and smallest(0.0 and 0.11) mean bias and rms values, respectively.
引文
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[18] Spreen G, Kaleschke L, Heygster G. Sea ice remote sensing using AMSR-E 89-GHz channels[J]. Journal of Geophysical Research: Oceans, 2008, 113(C2): C02S03.
[19] Comiso J C. SSM/I sea ice concentrations using the Bootstrap algorithm[R]. NASA Report. Linthicum Heights, MD: NASA Center for Aerospace Information, 1995.
[20] Lavelle J, Tonboe R, Tian T, et al. Product User Manual for the OSI SAF AMSR-2 Global Sea Ice Concentration[Z]. Product OSI-408. Danish Meteorological Institute, 2016.
[21] Tonboe R, Lavelle J, Pfeiffer R H, et al. Product User Manual for OSI SAF Global Sea Ice Concentration[Z]. Product OSI-401-b. Danish Meteorological Institute, 2017.
[22] Lu Peng, Leppranta M, Cheng Bin, et al. Influence of melt-pond depth and ice thickness on Arctic sea-ice albedo and light transmittance[J]. Cold Regions Science & Technology, 2016, 124: 1-10.
[23] 唐述林, 李宁. 基于走航观测的夏季南极海冰分布特征分析[J]. 冰川冻土, 2008, 30(2): 211-217. Tang Shulin, Li Ning. Analysis of the signature of summer Antarctic sea ice distribution by ship-based ice observation[J]. Journal of Glaciology and Geocryology, 2008, 30(2): 211-217.
[2] Kwok R, Untersteiner N. New high-resolution images of summer Arctic Sea Ice[J]. EOS, Transactions, American Geophysical Union, 2011, 92(7): 53-54.
[3] Cavalieri D J, Parkinson C L. Arctic sea ice variability and trends, 1979-2010[J]. The Cryosphere, 2012, 6(4): 881-889.
[4] Zhao Jinping, Barber D, Zhang Shugang, et al. Record low sea-ice concentration in the central Arctic during summer 2010[J]. Advances in Atmospheric Sciences, 2018, 35(1): 106-115.
[5] 郝光华, 苏洁, 黄菲. 北极冬季季节性海冰双模态特征分析[J]. 海洋学报, 2015, 37(11): 11-22. Hao Guanghua, Su Jie, Huang Fei. Analysis of the dual-mode feature of Arctic seasonal sea ice[J]. Haiyang Xuebao, 2015, 37(11): 11-22.
[6] Serreze M C, Stroeve J, Barrett A P, et al. Summer atmospheric circulation anomalies over the Arctic Ocean and their influences on September sea ice extent: a cautionary tale[J]. Journal of Geophysical Research: Atmospheres, 2016, 121(19): 11463-11485.
[7] Stroeve J C, Kattsov V, Barrett A, et al. Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations[J]. Geophysical Research Letters, 2012, 39(16): L16502.
[8] Jahn A, Kay J E, Holland M M, et al. How predictable is the timing of a summer ice-free Arctic?[J]. Geophysical Research Letters, 2016, 43(17): 9113-9120.
[9] Humpert M, Raspotnik A. The future of arctic shipping along the transpolar sea route[C]. 2012 Arctic Yearbook, 2012: 281-307.
[10] Lei Ruibo, Xie Hongjie, Wang Jia, et al. Changes in sea ice conditions along the Arctic Northeast Passage from 1979 to 2012[J]. Cold Regions Science & Technology, 2015, 119: 132-144.
[11] Jung T, Gordon N D, Bauer P, et al. Advancing polar prediction capabilities on daily to seasonal time scales[J]. Bulletin of the American Meteorological Society, 2016, 97(9): 1631-1647.
[12] Yang Qinghua, Losa S N, Losch M, et al. The role of atmospheric uncertainty in Arctic summer sea ice data assimilation and prediction[J]. Quarterly Journal of the Royal Meteorological Society, 2015, 141(691): 2314-2323.
[13] Yang Qinghua, Losa S N, Losch M, et al. Assimilating summer sea-ice concentration into a coupled ice-ocean model using a LSEIK filter[J]. Annals of Glaciology, 2015, 56(69): 38-44.
[14] Hao Guanghua, Su Jie. A study on the dynamic tie points ASI algorithm in the Arctic Ocean[J]. Acta Oceanologica Sinica, 2015, 34(11): 126-135.
[15] Yang Q, Losch M, Losa S N, et al. The benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation[J]. The Cryosphere Discussions, 2015, 9(2): 2543-2562.
[16] 赵杰臣, 周翔, 孙晓宇, 等. 北极遥感海冰密集度数据的比较和评估[J]. 遥感学报, 2017, 21(3): 351-364. Zhao Jiechen, Zhou Xiang, Sun Xiaoyu, et al. The inter comparison and assessment of satellite sea-ice concentration datasets from the arctic[J]. Journal of Remote Sensing, 2017, 21(3): 351-364.
[17] Worby A, Allison I, Dirita V. A Technique for making ship-based observations of Antarctic Sea Ice thickness and characteristics[R]. Research Report No. 14. Hobart: Australia Antarctic Division, 1999.
[18] Spreen G, Kaleschke L, Heygster G. Sea ice remote sensing using AMSR-E 89-GHz channels[J]. Journal of Geophysical Research: Oceans, 2008, 113(C2): C02S03.
[19] Comiso J C. SSM/I sea ice concentrations using the Bootstrap algorithm[R]. NASA Report. Linthicum Heights, MD: NASA Center for Aerospace Information, 1995.
[20] Lavelle J, Tonboe R, Tian T, et al. Product User Manual for the OSI SAF AMSR-2 Global Sea Ice Concentration[Z]. Product OSI-408. Danish Meteorological Institute, 2016.
[21] Tonboe R, Lavelle J, Pfeiffer R H, et al. Product User Manual for OSI SAF Global Sea Ice Concentration[Z]. Product OSI-401-b. Danish Meteorological Institute, 2017.
[22] Lu Peng, Leppranta M, Cheng Bin, et al. Influence of melt-pond depth and ice thickness on Arctic sea-ice albedo and light transmittance[J]. Cold Regions Science & Technology, 2016, 124: 1-10.
[23] 唐述林, 李宁. 基于走航观测的夏季南极海冰分布特征分析[J]. 冰川冻土, 2008, 30(2): 211-217. Tang Shulin, Li Ning. Analysis of the signature of summer Antarctic sea ice distribution by ship-based ice observation[J]. Journal of Glaciology and Geocryology, 2008, 30(2): 211-217.
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