冬季北极海冰体积下降:使用基于被动微波的海冰厚度来减少不确定性
Clement Soriot1,2, Martin Vancoppenolle3, Catherine Prigent4,5
1LERMA, Observatoire de Paris, CNRS, Université PSL, Paris, France. clement.soriot@umanitoba.ca.
Scientific reports
|September 9, 2024
概括
被动微波 (PMW) 数据可以限制北极海冰体积 (SIV) 的演变,减少不确定性. 这项研究表明,PMW海冰厚度 (SIT) 估计与再分析数据保持一致,改善了SIV预测.
科学领域:
- 气候科学 气候科学
- 冰层研究研究 冰层研究
- 遥感 遥感 遥感 遥感
背景情况:
- 北极海冰量 (SIV) 是一个关键的气候指标.
- 在SIV观测和模型输出中存在重大不确定性.
- 正在调查被动微波 (PMW) 数据限制SIV演变的潜力.
研究的目的:
- 评估被动微波 (PMW) 数据是否可以限制北极海冰量 (SIV) 的长期演变.
- 量化从PMW数据和参考再分析中得出的SIV估计之间的差异.
主要方法:
- 使用在激光雷达高度测量上训练的神经网络算法重建PMW海冰厚度 (SIT) 时间序列 (1992-2020).
- 重建的SIV时间序列与PIOMAS再分析数据的比较.
- 分析SIV平均值,趋势和阶段变化.
主要成果:
- 在PMW衍生的SIV变化和PIOMAS重新分析之间发现了强烈的共同点.
- 在SIV平均值 (37%),趋势 (17%) 和阶段变化 (r2=0.55) 中的差异相对较小.
- 季节性和多年性冰覆盖面,以及它们的SIT对比度,有助于减少差异,而多年性SIT是不确定性的来源.
结论:
- 被动微波 (PMW) 数据包含有价值的海冰厚度 (SIT) 信息,可以减少北极海冰体积 (SIV) 的不确定性.
- 通过将动态模型与PMW SIT估计数据同化相结合,可以实现海冰再分析的未来进展.
- 将PMW SIT数据与现有的海冰度同化相结合,为改善SIV预测提供了一条道路.
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