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Towards high resolution estimates of East Antarctic pack ice thickness


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Steer, AD (2016) Towards high resolution estimates of East Antarctic pack ice thickness. PhD thesis, University of Tasmania.

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The area of the Southern Ocean covered by sea ice is relatively well described by a longterm
time series of satellite observations spanning over 35 years. Throughout the seasonal
cycle, Antarctic sea-ice cover varies between approximately 3 x 10⁶ km² at the end of
summer to approximately 20 x 10⁶ km² during winter. This has profound implications for
ocean-atmosphere heat and momentum exchange and also for global oceanic circulation
induced by sea-ice production and melt. However, the thickness distribution of Antarctic
sea-ice is poorly described. Without detailed knowledge of the distribution of sea-ice
thickness (and hence volume) it is difficult to assess the magnitude of its influence, and
its feedback within the ocean-ice-atmosphere system. Current estimates of the sea-ice
thickness distribution derived from satellite-based altimetry rely on empirical models
describing the relationship between sea-ice topography, snow depth and sea-ice draft. The
input to these empirical models include approximations for the density of snow, sea ice and
seawater, and relationships between snow depth and the total freeboard (ice + snow) of
sea ice derived from sparse in-situ observations. Further, observations from comparatively
lower resolution satellite altimetry remain insensitive to small scale features that often
characterise sea ice.

This research estimates high-resolution sea-ice thickness from airborne nadir-looking
photography and Light Detection and Ranging (LiDAR), deployed over East Antarctic
pack ice between 2007 and 2012. It presents a detailed analysis of empirical models for
snow depth estimation derived from in-situ observations. For altimetry without coincident
methods to remotely sense the snow/ice interface, using an empirical relationship between
snow depth and measured elevation is the only available means to estimate snow depth.
This represents a novel direct comparison between empirical snow depth models and
in situ observations at scales of less than hundreds of metres. Examination of sources
of uncertainty in altimetry observations follow, with the development of a method for
deriving the uncertainty of each point position in a LiDAR swath. This allows the
rigorous propagation of uncertainties from the airborne instruments through to snow
depth and ice thickness estimates. A unique comparison of draft estimates from airborne
LiDAR with sea-ice draft mapped by upward looking SONAR from an underwater robot
forms a key component of this research. SONAR-based ice drafts are used to empirically
derive parameters for the ice thickness model applied to airborne LiDAR observations.
Using the same small patch of sea ice, relationships between surface and under-ice
features are explored, providing a unique insight into how well ice drafts derived from
surface topography characterise the under-ice environment. The empirically derived model
parameters from this exercise are then applied to a larger-scale dataset, which is compared
to near-coincident ship-based visual sea-ice observations (using the ASPeCt protocol).

Using in situ and sonar observations collected by an Autonomous Underwater Vehicle
(AUV) to inform parameter choices for modelling sea ice thickness from LiDAR altimetry,
a close match between sub-floe scale ice draft from AUV and LiDAR-derived estimates was
obtained. The ice density parameter used in the model was artificially high, at 915.6kgm³
compared to observed values which ranged from 800 kg m³ to 870 kg m³ on SIPEX-II.
The distribution of ice keels associated with surface ridges was broadly similar in both
AUV observations and LiDAR-derived estimates, although keels modelled using surface
topography are narrower and deeper than keels present in the AUV observations. Smallscale
topography was also added at the ice-ocean interface for draft estimates from airborne
LiDAR, reflecting the influence of snow dunes at the surface. Importantly, co registration
of in situ, AUV and airborne observations shows clearly that in situ observations captured
only the thinnest and least deformed region of the surveyed ice floe.

At a broader scale, the knowledge gained from validating sea ice thickness estimates over a
single floe was applied to a 120 km flight leg with a near-coincident ASPeCt ship-based ice
thickness observations. The distribution of ice thickness estimates from airborne LiDAR
exhibited a shallow peak in the 3m to 4m range, where ship-based observations were
predominantly showing ice thicknesses between 1 m to 2 m. This pattern is also seen for
the smaller floe-scale study, suggesting that in situ observations for regions of deformed
ice o↵ East Antarctica may only represent one tail of the sea-ice thickness distribution.
The implications for the use of in situ observations in tuning algorithms for satellite-based
estimates of sea-ice thickness are clear, suggesting a bias toward thin ice especially in
regions of heavy deformation.

This work advocates for the combination of multiple observation types and techniques
given their ability to offer insight into biases that affect a particular method at a particular
spatial scale. Technologies spanning in situ, airborne and satellite platforms have a strong
and integrated future in sea-ice observation.

Item Type: Thesis (PhD)
Keywords: Sea ice, airborne LiDAR, ice thickness, East Antarctica, observation
Copyright Information:

Copyright 2016 the Author

Additional Information:

Chapter 2 appears to be the equivalent of a post-print version of an article published as: Steer, A., Heil, P., Watson, C., Massom, R. A., Lieser, J. L., Ozsoy-Cicek, B., 2016. Estimating small-scale snow depth and ice thickness from total freeboard for East Antarctic sea ice, Deep sea research. Part II, Topical studies in oceanography, 131, 41-52

Date Deposited: 11 Apr 2017 01:29
Last Modified: 05 May 2017 02:19
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