Dr Adam Steer
Press 's' (not p) while viewing to see slide notes.
Dr Christopher Watson :: Dr Jan Lieser :: Dr Arko Lucieer :: Dr Jon Osborn
Dr Petra Heil (AAD) :: Dr Anthony Worby (ACE CRC) :: Dr Robert Massom (AAD) :: Dr Guy Williams
Peter Jansen :: Kym Newbery :: Helicopter Resources :: P & O Polar :: Many minions who dug holes in the freezing cold.
The formation of sea ice on the southern ocean provides salty cold water to drive oceanic overturning circulation.
When present, sea ice interferes with ocean/atmosphere heat exchange - acting as an insulator
Sea ice interferes with the exchange of momentum between the ocean and atmosphere. Its drift also transports fresh water from the site of ice formation to the site of ice melt
Sea ice provides a unique winter habitat for life in the southern ocean, and its melt contributes to spring plankton blooms
The thickness distribution of Antarctic sea ice is a key measure of the magnitude of all these effects.
The thickness distribution of Antarctic sea ice is very dynamic, and very poorly described. Its variability at floe to sub-floe scales is unknown.
Circumpolar sea ice thickness distribution monitoring is really only feasible using satellite instruments, and the only instruments which are so far practial are altimeters - for example ICESat/GLAS, or CryoSAT-2
...but sea ice is highly variable at sub-100m scales - which satellite altimeters cannot (yet) detect
...and we didn't know if empirical relationships used for estimating sea ice thickness using altimetry work at high resolutions
...and finally - we didn't know how to properly validate estimates of sea ice thickness from altimetry + empirical models
Can we estimate sea ice thickness over areas big enough to compare with satellites, at a resolution comparable to field observations?
Figure 3 in Worby, A. P., Geiger, C. A., Paget, M. J., Woert, M. L. V., Ackley, S. F., and Deliberty, T. L., 2008a: Thickness distribution of Antarctic sea ice. Journal of Geophysical Research, 113, 1–14.
The Aerial Photography, Pyrometer and Laser Scanner (APPLS) instrument package
So we take LiDAR observations. Now what? How do we know where 'sea level' is? And our survey medium is always moving.
A ship, some drills, many minions, and a robotic total station
Drill holes are fun, but generally collect very small 2D samples at disparate locations and times. Sea ice is three dimensional. How do we get that missing dimension and use these labour-intensive data well? Also, how well do altimetry-based estimates match observations?
Ship-based ice observations of ice thickness form the 'validation mainstay' - do altimetry-based estimates match these?
Figure 6 in Worby, A. P., Geiger, C. A., Paget, M. J., Woert, M. L. V., Ackley, S. F., and Deliberty, T. L., 2008a: Thickness distribution of Antarctic sea ice. Journal of Geophysical Research, 113, 1–14.
Observing ice draft from below...
Photo by the ROV team (Klaus Meiners, Kym Newbery et al), and borrowed from here: https://www.whoi.edu/news-release/SeabedAntarctic
Mainly determining 'sea level' from LiDAR observations
Sparse observations, limited to survey transect lines - so snow depth must be estimated over a full LiDAR swath
3912 drill holes with snow depth and total freeboard
Data were provided by Dr. Guy Williams - see:
Williams, G., Maksym, T., Wilkinson, J., Kunz, C., Murphy, C., Kimball, P., and Singh, H., 2014b: Thick and deformed Antarctic sea ice mapped with autonomous underwater vehicles. Nature Geoscience, (November), 1–7.
What to use? Range from 870 - 930 kg/m3
Solution - empirically determine a 'floe scale' ice density using observed ice draft
For this site, AUV draft and LiDAR draft are strongly correlated if we remove any spatial component and do a simple Spearman's Rho (0.7).
This means that most of the time there is thick ice under surface ridges. However, it's also easy to see that modelling ice draft from topography produces artificially deep and narrow ice keels.
The spreading of keels below ridges is well known, but rarely directly sampled.
Using ship-based airborne sensors, we can investigate of sea ice which is too thick to navigate, too thin to walk on, and too far away/logistically difficult to approach using a fixed-wing flown-from-land aircraft
For the region studied, in situ observations underestimate ice thickness due to logistically-driven observer bias
Data quality improvements are simple - funding the work is less straightforward
This approach is optimised with a well coordinated and mutli-faceted field program
The airborne observations, ground survey and AUV observations are all interdependent. Take away one and the result is substantially degraded.
Over 4 field campaigns the APPLS instrument collected more than 30 000 aerial photos, and hundreds of nautical miles of LiDAR.
These lie waiting for a keen analyst!
Questions? Comments? Field survey funding offers?
Fork my code (or make it go): http://github.com/adamsteer