极地研究

极地研究 ›› 2019, Vol. 31 ›› Issue (3): 258-266.DOI: 10.13679/j.jdyj.20180059

• 研究论文 • 上一篇    下一篇

北极海冰密度变化分析及其对海冰厚度估算的影响

李冰洁1  庞小平1,2,3  季青1,2,3   

  1. 1.武汉大学中国南极测绘研究中心, 湖北 武汉 430079; 
    2.极地测绘科学国家测绘地理信息局重点实验室, 湖北 武汉 430079; 
    3.中国高校极地联合研究中心, 北京 100875
  • 收稿日期:2018-10-15 修回日期:2019-01-17 出版日期:2019-09-30 发布日期:2019-09-30
  • 通讯作者: 季青
  • 基金资助:

    国家重点研发计划(2016YFC1402704, 2017YFA0630104)和国家自然科学基金(41576188, 41606215)资助

Analyses of Arctic sea ice density variation and its impact on sea ice thickness retrieval

Li Bingjie1, Pang Xiaoping1,2,3, Ji Qing1,2,3   

  • Received:2018-10-15 Revised:2019-01-17 Online:2019-09-30 Published:2019-09-30
  • Contact: Qing JI

PDF (PC)

631

摘要：

海冰密度是海冰和气候模型的重要物理变量, 也是利用卫星测高数据估算海冰厚度的关键参数。目前各国北极科学考察虽开展了海冰物理观测, 但对近期北极海冰密度现场观测资料的综合分析和挖掘应用不足。在此背景下, 收集了近15年来北极海冰密度现场观测资料, 分析北极海冰密度的变化特征; 对海冰密度实测数据进行克里金插值, 将插值结果输入静力平衡方程模型计算海冰厚度, 探讨海冰密度对海冰厚度卫星测高反演的影响。结果表明, 2000—2015年北极海冰密度变化范围为750—950kg·m–3, 1—9月海冰密度总体上随月份变化呈减小的趋势; 6—9月北极海冰密度随着纬度的增加而减少(75°N—90°N); 通过对比分析表明, 相较于使用海冰密度固定值参与估算海冰厚度, 采用经现场观测数据空间插值后的海冰密度估算海冰厚度的结果更为准确。北极海冰密度现场观测资料的整理分析可为海冰与气候变化等进一步研究提供参考。

关键词: 海冰密度, 现场观测, 变化分析, 海冰厚度

Abstract:

Sea ice density is an important variable of sea ice physics and climate models, and it is key parameter for the retrieval of sea ice thickness from satellite altimeters. Physical investigations of Arctic sea ice have been conducted during many scientific expeditions; however, in situ measurements of sea ice density acquired in recent years still require further sorting and analysis. In this context, we collected 15 years’ data of Arctic sea ice density. We analyzed the variability of sea ice density, calculated sea ice thickness, based on the hydrostatic equation with in situ sea ice density after applying Kriging interpolation, and discussed the influence of sea ice density on sea ice thickness retrieved via satellite altimetry. Results showed that the annual mean sea ice density varied from 750 to 950 kg·m-3 during from 2000 to 2015. From January to September, the monthly mean sea ice density tended to decrease, and it generally decreased with latitude during June–September. Comparative analysis revealed it is more suitable to use sea ice density after data interpolation than to use a fixed constant density for sea ice thickness retrievals. Sorting and analysis of Arctic in situ sea ice density could provide a reference for further research on Arctic sea ice and climate change.

Key words: sea ice density, in situ, variation analyses, sea ice thickness