Interannual-to-decadal variability of Antarctic ice shelf elevations from

multi-mission satellite radar altimetry

Fernando Paolo; Helen Amanda Fricker Scripps Institution of Oceanography, UCSD

Laurence Padman Earth & Space Research

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Large scale studies on ice shelves

Pritchard et al., 2012Zwally et al., 2005 Shepherd et al., 2010

9 years50 km

DurationSpat. Res.

14 yearsOne value per ice shelf

5 years30 km

ICESat 2003-2008ERS-1/2 1992-2001 ERS-2/Envisat 1994-2008

This study ! ERS-1 + ERS-2 + Envisat, 1992-2012

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The need for multi-mission RA

Long vs short records in detecting climate trends

Our goal: identify interannual to decadal variability on the ice shelf at spatial scales ~20-30 km

Fricker and Padman, 2012

How long? At least decadal observations(20+ years)

Interannual and decadal variability underexplored

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Penetration depth (backscatter)

Penetration depth:

! Water ! "(mm)! Wet snow ! O(cm)! Dry snow ! O(m)

! And varies with time

Radar penetrates into firn layer

(A)

(B)

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CONSTRUCTING TIME SERIES OF dhSimilar (but not the same) method as Davis & Segura (2001), Zwally et al. (2005), Khvorostovsky (2011).

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Averaging in time and space

less crossovers per bin → larger error bars

improved signal-to-noise ratio and no gaps

1 vs 3-month averages

20-30 km bins

3 x

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Averaging time seriesAt every individual grid-cell we have several time series

2) Then we frequency-weighted average the aligned time series

1) To align we use average of the offset for overlap period only

outliers

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Backscatter correction (2 approaches)

Wingham et al., 1998; Davis & Ferguson, 2004; Zwally et al., 2005

→

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Backscatter correction (2 approaches)

Wingham et al., 1998; Davis & Ferguson, 2004; Zwally et al., 2005

(1) absolute values (2) differences (derivative)

backscatter change diff backscatter change

diff

elev

atio

n ch

ange

elev

atio

n ch

ange

→

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Correlation between dh and dAGC

(1)

(2)

ROSSFRIS

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Backscatter correction (approach 3)

What if the correlation is not constant → R(t)?

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Backscatter correction (approach 3)

What if the correlation is not constant → R(t)?

Correlation

Sensitivity

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NOW SOME RESULTS

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20-year trend in elevation change(original grid)

High spatial and temporal variability

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Note: 2001 was chosen to avoid a big calving event

20-year trend in elevation change(original grid)

High spatial and temporal variability

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High interannual variability

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Coherent changes?Tracking coherent events around the Antarctic margin

?

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DO WE KNOW WHAT WE ARE MEASURING?

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Envisat vs ICESat

Subsampling RAaccording ICESatcampaigns

SubsamplingRA accordingICESat coverage

Observations by both satellites at the same location at the same time!

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Envisat vs ICESat

Subsampling RAaccording ICESatcampaigns

Envisat ICESat

SubsamplingRA accordingICESat coverage

Observations by both satellites at the same location at the same time!

6-year trends in elevation change

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Area-averaged time series (1)

Envisat with no backscatter correction

ROSS Ice Shelf

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Area-averaged time series (2)

Envisat with backscatter correction (approach 1)

ROSS Ice Shelf

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Area-averaged time series (3)

Envisat with backscatter correction (approach 2)

ROSS Ice Shelf

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Area-averaged time series (4)

ICESat with no inter-campaign biases applied

ROSS Ice Shelf

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Area-averaged time series (5)

ICESat with inter-campaign biases applied (Urban)

ROSS Ice Shelf

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Area-averaged time series (6)

ICESat with inter-campaign biases applied (Zwally)

ROSS Ice Shelf

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What is signal and what is noise?

Pritchard et al., 2012

Two different methods and the same pattern ! the features are in the data!

Cross-over analysis Along-track analysis

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Summary

! Continuous long (~20 year) time series of ice shelf elevation constructed from multi-mission RA

! Reveals large variability both in time and space that can be misinterpreted as trends in single-mission satellite analyses

! (Future work) Use elevation variability to identify oceanic and atmospheric forcings affecting ice-shelf mass balance

! Issues! Relative error (precision) vs absolute error (penetration)! Different backscatter and biases yield different results! Why don't Envisat and ICESat agree for 2004-2010? What

are they measuring differently?

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We thank

! NASA NESSF Fellowship

! Jay Zwally & Jairo Santana (NASA/GSFC)

! Curt Davis (UM) & Duncan Wingham (UCL)

! NASA grants NNX06AD40G and NNX10AG19G

! ESA for ERS-1, ERS-2 and Envisat altimeters

! San Diego Super Computer Center

! Python and Open Source

fpaolo@ucsd.edu

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Antarctic ice shelf mask

A reliable and complete ice shelf mask is a problem

So we (Geir Moholdt) created our own using all data available: MOA (Scambos et al. 2007), ASAID (Bindschadler et al. 2011), InSAR (Rignot et al. 2011), ICESat (Fricker/Brunt et al. 2006-10)

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Challenges of multi-mission integration

! Differences between missions:

- RA systems, orbit configurations, time spans...

! Radar interaction with time variable surface properties! Spatial and temporal dependent corrections:

- Ocean tides (for high lat)

- Atm pressure (IBE)

- Surface density (firn densification)

- Penetration depth (backscatter)

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How to reduce the noise?

! Due to hydrostatic equilibrium the altimeter only see 10% of the grounded ice signal (in elevation change)

! So to increase signal-to-noise ratio → requires lots of averaging both in time and space

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The uncertainty

! How well do we know the error?

! What do error bars in the time series actually represent?

! What about the uncertainty in penetration depth?

O(m/cm)

After all the averaging a mean error is: ± 5-20 cm over 20-30 km

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High spatial and temporal variability

Note: 2001 was chosen to avoid a big calving event

20-year trend in elevation change(original grid)