Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Interannual and decadal variations of 
Antarctic ice shelves using multi-mission 
satellite radar altimetry, and links wit...
Presentation outline 
1. Background 
Importance, Hypothesis, Evidence 
2. Thesis 
Chapter 1, Chapter 2, Chapter 3 
3. Summ...
Why do we care? 
Ice-sheet mass loss Sea-level rise
Why do we care? 
Ice-sheet mass loss Sea-level rise 
Shepherd et al., 2012 
Antarctica 
Greenland 
Glaciers 
Ice volume 
3...
Why Antarctica? 
The marine 
Ice-sheet instability 
Bed above sea level 
Vaughan and Arthern, 2007 
Increased discharged w...
Why ice shelves? 
ice shelves are the 
“interface” between 
the ice sheet and 
the ocean 
Fig. Ice-shelf coverage 
by sate...
Ice-shelf buttressing 
Compressive stress is a result of ice-shelf buttressing 
Hughes, 2011 
OCEAN GROUNDED ICE 
Ice rise...
Ice-shelf-ocean interaction 
100s km 
1-2 km 
Fig. M. Craven, AAD 
Three modes of basalt melt (Jacobs et al., 1992)
Ice-shelf-ocean heat exchange 
Jenkins et al., 2010 
Melt rates of 10s m/yr
Ice-shelf-ocean heat exchange 
CDW all the way to the sub-ice-shelf cavity 
Melt rates of 10s m/yr 
Jenkins et al., 2010 J...
Ice-shelf and grounded-ice thinning 
Pritchard et al., 
2012
Evidence on ice-shelf buttressing 
Rignot et al., 2004
Previous studies 
ERS-1/2 1992-01 ERS-2/Envisat 1994-08 ICESat 2003-08 
Zwally et al., 2005 Shepherd et al., 2010 Pritchar...
My contribution 
1. Derive reliable time series of elevation 
change over the longest possible time period 
2. Quantify lo...
Thesis structure 
Chapter 1 → The methodology 
(Generate the dataset) 
Chapter 2 → Radar-Laser comparison 
(Validate the d...
Chapter 1 
Constructing time series of 
elevation change
Satellite altimetry missions 
Twenty years of continuous data over the ice shelves
The challenge of multi-mission 
integration 
Differences between missions: 
– RA systems, orbit configurations, time spans...
The challenge over ice shelves 
Due to hydrostatic equilibrium the altimeter only see 
10-15% of the grounded ice signal (...
Averaging in time 
Monthly 
averages 
Seasonal 
averages 
Time steps → 3-month blocks of data
Averaging in space 
3 x 
One month of data 
~750 bins with 15 to 200 observations (for FRIS)
Averaging time series 
82 time series per bin (x 2) 
61,500 time series for FRIS (x 2) 
Matrix before 
Matrix after
Inter-mission cross-calibration 
ERS-1 ERS-2 Envisat 
What happens when there are no data in the overlapping period?
The backscatter problem 
k e ( x , t ) 
ρs( x , t ) 
Remy et al., 2012 
Penetration: 
Densification:
Backscatter correction 
hc (t)=h(t)−s g (t)−h0 
Amplitude series 
Differenced series 
Elevation 
Backscatter 
Done for eac...
Time-varying backscatter 
hc (t)=h(t )−s(t ) g (t )−h0(t ) 
ERS-1 ERS-2 Envisat 
Done for each grid-cell
Different corrections, different 
results? 
Amplitude ts 
Differenced ts
Different corrections, different 
results? 
Different fluctuation and trend 
Constant correlation 
Variable correlation 
A...
Chapter 2 
Envisat (radar) vs ICESat (laser) 
inter-comparison
Two altimeters, one purpose 
Envisat (Radar) 
– microwave (λ ~ 2.5 cm) 
– wide footprint (3 km) 
– all weather 
– continuo...
Do they measure the same thing? 
First time this 
comparison is 
done in this way
Do they measure the same thing? 
Envisat ICESat 
We need an explanation for such differences! 
First time this 
comparison...
Two ways of estimating elevation 
changes 
∂ h 
∂ t Dh 
1) Eulerian (fixed): 
2) Lagrangian (moving): 
Dt =∂ h 
∂ t + u⋅∇ ...
Footprint differences 
ICESat footprint (70 m) is about 
0.05% of RA-2 footprint (3 km)
Is radar ∂ h / ∂ t Eulerian?
Is radar ∂ h / ∂ t Eulerian?
What is signal and what is noise? 
ICESat data are very noisy! How much can we trust? 
Cross-over analysis Along-track ana...
Chapter 3 
Variability of Antarctic ice-shelf 
elevations
Our main goal 
– Search for mechanisms that could explain the 
observed variability in h( x , t )
Ice-shelf mass balance 
∂ h 
∂ t = ∂Δ 
∂ t −M ∂ 
∂ t ρw − 
M dm ∂ 
1+∫0 
1(m) 
∂ t ρf − 
+ (ρi −1−ρw − 
1)(M˙ s+ M˙ b+ u⋅∇...
Variability within an ice shelf 
We are able to resolve 
the “fine” spatial scales
Spatio-temporal change in ∂ h / ∂ t 
Why aren't 
thinning/thickening 
regions “fixed”?
Correlations, correlations... 
Fig. J. Allen, NASA 
Data NSIDC 
What is the relation 
to sea-ice variability? 
– Sea ice p...
Large-scale coherent events? 
AMERY 
FRIS 
ROSS 
Decadal oscillation 
In phase?
Thesis summary 
Generate a 20-year long and high resolution 
dataset of thickness variation for all Antarctic 
ice shelves...
Upcoming SlideShare
Loading in …5
×

PhD Qualifying

759 views

Published on

Interannual and decadal variations of Antarctic ice shelves using multi-mission satellite radar altimetry, and links with oceanic and atmospheric forcings

  • Be the first to comment

PhD Qualifying

  1. 1. Interannual and decadal variations of Antarctic ice shelves using multi-mission satellite radar altimetry, and links with oceanic and atmospheric forcings Fernando S. Paolo PhD Qualifying, May 20, 2013 Scripps Institution of Oceanography University of California, San Diego
  2. 2. Presentation outline 1. Background Importance, Hypothesis, Evidence 2. Thesis Chapter 1, Chapter 2, Chapter 3 3. Summary Results and Big Picture
  3. 3. Why do we care? Ice-sheet mass loss Sea-level rise
  4. 4. Why do we care? Ice-sheet mass loss Sea-level rise Shepherd et al., 2012 Antarctica Greenland Glaciers Ice volume 3 mm/yr (~1.8 from Cryosphere)
  5. 5. Why Antarctica? The marine Ice-sheet instability Bed above sea level Vaughan and Arthern, 2007 Increased discharged with grounding-line retreat → unstable condition! Fig. M. Helper Data BEDMAP
  6. 6. Why ice shelves? ice shelves are the “interface” between the ice sheet and the ocean Fig. Ice-shelf coverage by satellite altimetry missions
  7. 7. Ice-shelf buttressing Compressive stress is a result of ice-shelf buttressing Hughes, 2011 OCEAN GROUNDED ICE Ice rise Confining embayment Ice rumple Calving front
  8. 8. Ice-shelf-ocean interaction 100s km 1-2 km Fig. M. Craven, AAD Three modes of basalt melt (Jacobs et al., 1992)
  9. 9. Ice-shelf-ocean heat exchange Jenkins et al., 2010 Melt rates of 10s m/yr
  10. 10. Ice-shelf-ocean heat exchange CDW all the way to the sub-ice-shelf cavity Melt rates of 10s m/yr Jenkins et al., 2010 Jacobs et al., 2011
  11. 11. Ice-shelf and grounded-ice thinning Pritchard et al., 2012
  12. 12. Evidence on ice-shelf buttressing Rignot et al., 2004
  13. 13. Previous studies ERS-1/2 1992-01 ERS-2/Envisat 1994-08 ICESat 2003-08 Zwally et al., 2005 Shepherd et al., 2010 Pritchard et al., 2012 9 years 50 km Duration Spt. Res. 14 years One trend per ice shelf 5 years 30 km To detect climate signals we need long and continuous records!
  14. 14. My contribution 1. Derive reliable time series of elevation change over the longest possible time period 2. Quantify long-term trends 3. Quantify interannual-to-decadal variability 4. Identify causes of temporal and spatial variability
  15. 15. Thesis structure Chapter 1 → The methodology (Generate the dataset) Chapter 2 → Radar-Laser comparison (Validate the dataset) Chapter 3 → Ice-shelf variability (Analyze the dataset)
  16. 16. Chapter 1 Constructing time series of elevation change
  17. 17. Satellite altimetry missions Twenty years of continuous data over the ice shelves
  18. 18. The challenge of multi-mission integration Differences between missions: – RA systems, orbit configurations, time spans... Radar interaction with variable surf. properties: ρs ( x , t ) ke( x , t) – Surface density, – Penetration depth, Spatial and temporal dependent corrections: – Ocean tide + load (for high lat) – Atm pressure (IBE) – Regional sea-level rise
  19. 19. The challenge over ice shelves Due to hydrostatic equilibrium the altimeter only see 10-15% of the grounded ice signal (in elevation change) So to increase signal-to-noise ratio requires lots of averaging both in time and space
  20. 20. Averaging in time Monthly averages Seasonal averages Time steps → 3-month blocks of data
  21. 21. Averaging in space 3 x One month of data ~750 bins with 15 to 200 observations (for FRIS)
  22. 22. Averaging time series 82 time series per bin (x 2) 61,500 time series for FRIS (x 2) Matrix before Matrix after
  23. 23. Inter-mission cross-calibration ERS-1 ERS-2 Envisat What happens when there are no data in the overlapping period?
  24. 24. The backscatter problem k e ( x , t ) ρs( x , t ) Remy et al., 2012 Penetration: Densification:
  25. 25. Backscatter correction hc (t)=h(t)−s g (t)−h0 Amplitude series Differenced series Elevation Backscatter Done for each grid-cell
  26. 26. Time-varying backscatter hc (t)=h(t )−s(t ) g (t )−h0(t ) ERS-1 ERS-2 Envisat Done for each grid-cell
  27. 27. Different corrections, different results? Amplitude ts Differenced ts
  28. 28. Different corrections, different results? Different fluctuation and trend Constant correlation Variable correlation Amplitude ts Differenced ts How significant are these differences?
  29. 29. Chapter 2 Envisat (radar) vs ICESat (laser) inter-comparison
  30. 30. Two altimeters, one purpose Envisat (Radar) – microwave (λ ~ 2.5 cm) – wide footprint (3 km) – all weather – continuous sampling – penetrates into snow ICESat (Laser) – visible (λ ~ 650 nm) – narrow footprint (70 m) – cloud interaction – campaign mode – top-of-snow reflection
  31. 31. Do they measure the same thing? First time this comparison is done in this way
  32. 32. Do they measure the same thing? Envisat ICESat We need an explanation for such differences! First time this comparison is done in this way
  33. 33. Two ways of estimating elevation changes ∂ h ∂ t Dh 1) Eulerian (fixed): 2) Lagrangian (moving): Dt =∂ h ∂ t + u⋅∇ h (t1) A (t2) A' B A'-A = Euler B-A = Lagrange
  34. 34. Footprint differences ICESat footprint (70 m) is about 0.05% of RA-2 footprint (3 km)
  35. 35. Is radar ∂ h / ∂ t Eulerian?
  36. 36. Is radar ∂ h / ∂ t Eulerian?
  37. 37. What is signal and what is noise? ICESat data are very noisy! How much can we trust? Cross-over analysis Along-track analysis Pritchard et al., 2012 Two different techniques, same pattern → features are in the data!
  38. 38. Chapter 3 Variability of Antarctic ice-shelf elevations
  39. 39. Our main goal – Search for mechanisms that could explain the observed variability in h( x , t )
  40. 40. Ice-shelf mass balance ∂ h ∂ t = ∂Δ ∂ t −M ∂ ∂ t ρw − M dm ∂ 1+∫0 1(m) ∂ t ρf − + (ρi −1−ρw − 1)(M˙ s+ M˙ b+ u⋅∇ M+ M ∇⋅u) Altimeter observation Sea-level variations Ocean-density changes Firn compaction Ice-ocean density contrast Surface accumulation rate Basal accumulation rate Advection of thickness gradient and flow divergence Shepherd et al., 2003; Padman et al., 2012
  41. 41. Variability within an ice shelf We are able to resolve the “fine” spatial scales
  42. 42. Spatio-temporal change in ∂ h / ∂ t Why aren't thinning/thickening regions “fixed”?
  43. 43. Correlations, correlations... Fig. J. Allen, NASA Data NSIDC What is the relation to sea-ice variability? – Sea ice protects ice shelves by cooling air temperatures and dampening waves. – Also affects mode 1 of basal melt. Is there any relation to climate Indices (ENSO, SAM, ZW3)? – EOF analysis on h(x,t)
  44. 44. Large-scale coherent events? AMERY FRIS ROSS Decadal oscillation In phase?
  45. 45. Thesis summary Generate a 20-year long and high resolution dataset of thickness variation for all Antarctic ice shelves. Better understand the radar altimeter signal interaction with ice surfaces, and its effect in the final estimates. Estimate long-term trends and explain the variability in Antarctic ice-shelf thickness for the last two decades.

×