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Arctic sea ice freeboard from ICESat altimetry
SNAME Luncheon, October 19th, 2011 Vidya Renganathan Contractor, Chevron Arctic Center
NASA
Changing ice conditions
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Arctic sea ice freeboard from ICESat altimetry NASA SNAME - - PowerPoint PPT Presentation
Arctic sea ice freeboard from ICESat altimetry NASA SNAME - - PowerPoint PPT Presentation
Arctic sea ice freeboard from ICESat altimetry NASA SNAME Luncheon, October 19 th , 2011 Vidya Renganathan Contractor, Chevron Arctic Center Changing ice conditions What is also important is the ice thickness, its distribution and its
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Why care about sea ice thickness?
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Quest for natural resources
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Why care about sea ice thickness?
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Sea routes Ice management
UNEP Chevron Arctic Center
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Why care about sea ice thickness?
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Ice-structure interaction
I ce force 4 1 1 0 m Base Friction h Line of excavation
Native sand
Bottom force
Chevron Arctic Center
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Research Objective
Can ICESat laser altimetry data provide sea ice freeboard and thickness estimates?
- How do the sea ice freeboards derived in this study compare with other
methods?
- How do the sea ice thicknesses derived in this study compare with
- ther methods?
- What are the magnitudes of uncertainty in the estimated sea ice
freeboard and thickness?
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Ice Cloud Elevation Satellite – ICESat
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NASA
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Freeboard estimation from ICESat
Range (Snow)
Snow surface = Orbital height – Range (Snow)
Chevron Arctic Center
Total Freeboard = snow surface – sea surface
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Freeboard estimation from ICESat
Range (Snow)
1. “Observed” = Orbital height – Range (sea surface) 2. Oceanographic models
= Geoid + Tides + Mean dynamic topography + inverse barometric effect
Chevron Arctic Center
Total Freeboard = snow surface – sea surface
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Sea surface = Geoid + Tides + Mean Dyn. Topo. + Inv. Barometric Effect Ice freeboard = Snow surface – Sea surface – Snow depth – errors
Sea surface heights from models
Snow surface Tides + Mean Dyn Topo
Snow depth Freeboard
Geoid
Chevron Arctic Center
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Geoid, Tides, Mean Dynamic Topography
Geoid EIGEN-GL04c model GFZ Germany Mean Dyn Topo UW
- Univ. Washington
Tides AOTIM-5 Oregon State Univ.
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Comparison with ‘observed sea surface’ method
Feb 2006 ICESat period
DNSC
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Validation of ICESat elevations in Churchill
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Precise leveling – Sep 2006 GPS Real-time Kinematic – Mar 2008
Co-incident field measurements were taken along the predicted ICESat track on the ground
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Validation of ICESat elevations in Churchill
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Surface Type ICESat – Precise leveling (m)
Wetlands 0.60 Runway 0.20 Boreal forests 0.90 Coast > 1.0 Tidal flats 0.30
Surface Type ICESat – GPS RTK (m) Sea ice < 0.10
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Sea ice thickness distribution compared to Helicopter Electro-magnetic measurements – May 2006
Two methods agree within 53 cm
HEM data: Christian Haas, U of A
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Sea ice thickness distribution compared to JIP Arctic Islands thickness data (APOA)
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Summary and Outlook
Summary
- Freeboard distributions show good agreement with ‘observed’ freeboards
- Sea ice thickness shows good agreement with HEM-based thickness estimates and
JIP data (APOA)
- Sensitivity analysis indicates an error of about 24 cm in freeboard estimates
- Sensitivity analysis indicates an error of about < 98 cm in thickness estimates
Outlook
- Mean Dynamic Topography was the major source of error
- The accuracy of this method will improve automatically when the accuracy of the
component models continues to improve in the future
- An optimal Sea Surface Height estimate can be obtained by combining both
‘observed’ and modeled SSH www.ucalgary.ca/engo_webdocs/AB/10.20301_VRenganathan.pdf
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2011 studies – Cryosat-2 radar altimeter
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