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Estimating small-scale snow depth and ice thickness from total freeboard for East Antarctic sea ice

机译:从南极东部干冰的总干舷估算小规模雪深和冰厚

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摘要

Deriving the snow depth on Antarctic sea ice is a key factor in estimating sea-ice thickness distributions from space or airborne altimeters. Using a linear regression to model snow depth from observed 'total freeboard', or the snow/ice surface elevation relative to sea level is an efficient and promising method for the estimation of snow depth for instruments which only detect the uppermost surface of the sea-ice conglomerate (e.g. laser altimetry). However the Antarctic pack-ice zone is subject to substantial variability due to synoptic-scale weather forcing. Ice formation, motion and melt undergo large spatio-temporal variability throughout the year. In this paper we estimate snow depth from total freeboard for the ARISE (2003), SIPEX (2007) and SIPEX-II (2012) research voyages to the East Antarctic pack-ice zone. Using in situ data we investigate variability in snow depth and show that for East Antarctica, relationships between snow depth and total freeboard vary between each voyage. At a resolution of metres to tens of metres, we show how regression-based snow-depth models track total freeboard and generally over-estimate snow depth, especially on highly deformed sea ice and at sites where ice freeboard makes a substantial contribution to total freeboard. For a set of 3192 records we obtain an in situ mean snow depth of 0.21 m (sigma = 0.19 m). Using a regression model derived from all in situ points we obtain the same mean, with a slightly lower variability (sigma = 0.16 m). Using voyage-specific subsets of the data to derive regression models and estimate snow depth, mean snow depths ranged from 0.19 m (model derived from SIPEX observations) to 0.25 m (model derived from SIPEX-II observations). While small, these discrepancies impact ice thickness estimation using the assumption of hydrostatic equilibrium. Mean in situ ice thickness for all samples is 1.44 m (sigma = 1.19 m). Using empirical models for snow depth, ice thickness varies from 1.0 to 1.8 m with the best match to the in situ mean given when snow depth is derived using a snow depth model from all observations (1.53 m, sigma = 1.55 m). However, mean values only tell part of the story when investigating the sea-ice thickness distribution. Here we explicitly show how modelling snow depth and ice thickness based on a total freeboard signal compares with in situ observations. This provides insight into the confidence we place in ice thickness distributions derived using a total freeboard signal and empirically-derived models for snow depth. (C) 2016 Elsevier Ltd All rights reserved.
机译:推导南极海冰上的积雪深度是从空间高度计或空中高度计估算海冰厚度分布的关键因素。使用线性回归从观测到的“总干舷”或相对于海平面的雪/冰表面高程来模拟积雪深度是一种有效且有前途的方法,可用于仅检测海洋最上层表面的仪器估计积雪深度的方法。冰块(例如激光测高仪)。但是,由于天气尺度的天气强迫,南极积冰区的变化很大。一年中,冰的形成,运动和融化经历较大的时空变化。在本文中,我们估算了ARISE(2003年),SIPEX(2007年)和SIPEX-II(2012年)研究航行至南极东部pack冰区的总干舷的积雪深度。利用原位数据,我们研究了积雪深度的变化,并表明对于南极东部,积雪深度与总干舷之间的关系在每次航行之间都存在差异。在几米到几十米的分辨率下,我们展示了基于回归的积雪深度模型如何跟踪总干舷,并且通常高估了积雪深度,尤其是在高度变形的海冰上以及在干舷对总干舷有重大贡献的地点。对于一组3192条记录,我们获得的原位平均积雪深度为0.21 m(sigma = 0.19 m)。使用从所有原位点得出的回归模型,我们可以获得相同的平均值,但变异性略低(sigma = 0.16 m)。使用特定于航程的数据子集来得出回归模型并估计积雪深度,平均积雪深度范围从0.19 m(根据SIPEX观测值得出的模型)到0.25 m(根据SIPEX-II观测值得出的模型)。尽管很小,但这些差异会影响静水平衡假设下的冰厚度估算。所有样品的平均原位冰厚为1.44 m(sigma = 1.19 m)。使用雪深经验模型,当从所有观测值中使用雪深模型得出雪深时(1.53 m,sigma = 1.55 m),冰厚在1.0到1.8 m之间变化,与原位平均值最匹配。但是,平均值在调查海冰厚度分布时只能说明部分情况。在这里,我们明确显示了如何根据总干舷信号对积雪深度和冰层厚度进行建模与原位观测结果进行比较。这可以洞悉我们对使用总干舷信号和经验得出的雪深模型得出的冰厚分布的置信度。 (C)2016 Elsevier Ltd保留所有权利。

著录项

  • 来源
    《Deep-Sea Research》 |2016年第9期|41-52|共12页
  • 作者单位

    Australian Antarctic Div, Dept Environm, Kingston, Tas, Australia|Univ Tasmania, Antarctic Climate & Ecosyst Cooperat Res Ctr, Hobart, Tas, Australia|Univ Tasmania, Sch Land & Food, Hobart, Tas, Australia;

    Australian Antarctic Div, Dept Environm, Kingston, Tas, Australia|Univ Tasmania, Antarctic Climate & Ecosyst Cooperat Res Ctr, Hobart, Tas, Australia;

    Univ Tasmania, Sch Land & Food, Hobart, Tas, Australia;

    Australian Antarctic Div, Dept Environm, Kingston, Tas, Australia|Univ Tasmania, Antarctic Climate & Ecosyst Cooperat Res Ctr, Hobart, Tas, Australia;

    Univ Tasmania, Antarctic Climate & Ecosyst Cooperat Res Ctr, Hobart, Tas, Australia;

    Istanbul Tech Univ, Maritime Fac, Istanbul, Turkey;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Sea ice; East Antarctica; Snow depth; Empirical modelling; Total freeboard; Ice-thickness estimate;

    机译:海冰;南极东部;雪深;经验模型;总干舷;冰厚估计;

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