Arctic sea ice freeboard heights from Satellite altimetry Chevron Arctic ...
Arctic sea ice freeboard from ICESat altimetry
NASA
SNAME Luncheon, October 19th, 2011 Vidya Renganathan Contractor, Chevron Arctic Center
Changing ice conditions
What is also important is the ice thickness, its distribution and its inter-annual variability.
2
Why care about sea ice thickness?
Quest for natural resources 3
Why care about sea ice thickness?
UNEP Chevron Arctic Center
Sea routes
Ice management 4
Why care about sea ice thickness?
Bottom force Ice force 10m
Line of excavation
Base Friction
h
1 4
Native sand Chevron Arctic Center
Ice-structure interaction
5
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 other methods?
•
What are the magnitudes of uncertainty in the estimated sea ice freeboard and thickness?
6
Ice Cloud Elevation Satellite – ICESat
NASA
7
Freeboard estimation from ICESat
Total Freeboard = snow surface – sea surface Range (Snow)
Snow surface = Orbital height – Range (Snow)
Chevron Arctic Center
8
Freeboard estimation from ICESat
Total Freeboard = snow surface – sea surface Range (Snow)
1.
“Observed” = Orbital height – Range (sea surface)
2.
Oceanographic models = Geoid + Tides + Mean dynamic topography + inverse barometric effect
Chevron Arctic Center
9
Sea surface heights from models Sea surface = Geoid + Tides + Mean Dyn. Topo. + Inv. Barometric Effect Ice freeboard = Snow surface – Sea surface – Snow depth – errors
Snow depth Freeboard
Tides + Mean Dyn Topo Snow surface
Geoid
Chevron Arctic Center
10
Geoid, Tides, Mean Dynamic Topography
Geoid EIGEN-GL04c model GFZ Germany
Tides AOTIM-5 Oregon State Univ.
Mean Dyn Topo UW Univ. Washington
11
Comparison with ‘observed sea surface’ method
DNSC
Feb 2006 ICESat period 12
Validation of ICESat elevations in Churchill
Precise leveling – Sep 2006
GPS Real-time Kinematic – Mar 2008
Co-incident field measurements were taken along the predicted ICESat track on the ground
13
Validation of ICESat elevations in Churchill
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
14
Sea ice thickness distribution compared to Helicopter Electro-magnetic measurements – May 2006
HEM data: Christian Haas, U of A
Two methods agree within 53 cm 15
Sea ice thickness distribution compared to JIP Arctic Islands thickness data (APOA)
16
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
17
2011 studies – Cryosat-2 radar altimeter
18
Questions?
19
NASA
SNAME Luncheon, October 19th, 2011 Vidya Renganathan Contractor, Chevron Arctic Center
Changing ice conditions
What is also important is the ice thickness, its distribution and its inter-annual variability.
2
Why care about sea ice thickness?
Quest for natural resources 3
Why care about sea ice thickness?
UNEP Chevron Arctic Center
Sea routes
Ice management 4
Why care about sea ice thickness?
Bottom force Ice force 10m
Line of excavation
Base Friction
h
1 4
Native sand Chevron Arctic Center
Ice-structure interaction
5
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 other methods?
•
What are the magnitudes of uncertainty in the estimated sea ice freeboard and thickness?
6
Ice Cloud Elevation Satellite – ICESat
NASA
7
Freeboard estimation from ICESat
Total Freeboard = snow surface – sea surface Range (Snow)
Snow surface = Orbital height – Range (Snow)
Chevron Arctic Center
8
Freeboard estimation from ICESat
Total Freeboard = snow surface – sea surface Range (Snow)
1.
“Observed” = Orbital height – Range (sea surface)
2.
Oceanographic models = Geoid + Tides + Mean dynamic topography + inverse barometric effect
Chevron Arctic Center
9
Sea surface heights from models Sea surface = Geoid + Tides + Mean Dyn. Topo. + Inv. Barometric Effect Ice freeboard = Snow surface – Sea surface – Snow depth – errors
Snow depth Freeboard
Tides + Mean Dyn Topo Snow surface
Geoid
Chevron Arctic Center
10
Geoid, Tides, Mean Dynamic Topography
Geoid EIGEN-GL04c model GFZ Germany
Tides AOTIM-5 Oregon State Univ.
Mean Dyn Topo UW Univ. Washington
11
Comparison with ‘observed sea surface’ method
DNSC
Feb 2006 ICESat period 12
Validation of ICESat elevations in Churchill
Precise leveling – Sep 2006
GPS Real-time Kinematic – Mar 2008
Co-incident field measurements were taken along the predicted ICESat track on the ground
13
Validation of ICESat elevations in Churchill
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
14
Sea ice thickness distribution compared to Helicopter Electro-magnetic measurements – May 2006
HEM data: Christian Haas, U of A
Two methods agree within 53 cm 15
Sea ice thickness distribution compared to JIP Arctic Islands thickness data (APOA)
16
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
17
2011 studies – Cryosat-2 radar altimeter
18
Questions?
19
