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Glacial Isostatic Adjustment Contributions to Tide Gauge, Altimetry and GRACE Observations Glenn Milne Dept of Earth Sciences University of Durham, UK Contributors: Mark Tamisiea, Konstantin Latychev, Erik Ivins, Philippe Huybrechts, Jerry Mitrovica, Bert Vermeersen. Edited version: original slides 12-19 removed

Glacial Isostatic Adjustment Contributions to Tide Gauge, Altimetry and GRACE Observations Glenn Milne Dept of Earth Sciences University of Durham, UK

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Glacial Isostatic Adjustment Contributions to Tide Gauge, Altimetry

and GRACE Observations

Glenn MilneDept of Earth Sciences

University of Durham, UK

Contributors: Mark Tamisiea, Konstantin Latychev, Erik Ivins, Philippe Huybrechts, Jerry Mitrovica, Bert Vermeersen.

Edited version: original slides 12-19 removed

http://www.ngdc.noaa.gov/paleo/slides/slideset/index11.htm

GLACIAL ISOSTATIC ADJUSTMENT

Surface Mass Redistribution

Earth Earth Response

• Relative sea level• Geopotential• Rotation vector• 3D solid surface deformation

ModelSurface load + Rotational potential

Rheological Earth model

Better understanding of GIA process

Constraints on Earth rheology

Constraints on surface mass redistribution

Earth Forcing Earth Model

Rotational potentialEuler equations

Surface loading

Ice Model

Multidisciplinary approach

Ocean Model

Sea-level equation

Geometry RheologySpherical/Flat

Internal structure: 1D & 3D

Viscoelastic

Linear and non-linear viscous deformation

Key Elements of a GIA Model

Tamisiea et al., 2003

GIA Response: Driven by Contemporary and Past Mass Flux

How Can the GIA Community Contribute to a Better Understanding of Recent Sea-

Level Changes?

Climate change

SEA-LEVEL FORCINGS

Anthropogenic effects

Ocean dynamics

Solid Earth

motionOcean-

atmosphere interaction

SEA-LEVEL OBSERVATIONS

Proxy recordsTide Gauges

Satellite Gravity

Satellite Altimetry

Ice-ocean mass exchange

Ocean warming

Viscous “Memory” of Solid Earth to Past Ice-Ocean Mass Flux

A

Mitrovica and Milne (2002)

B

The Influence of Variations in Earth Model Viscosity Structure on Observations of

Sea-Level Change

• How sensitive is the GIA signal associated with past ice-ocean mass flux to changes in Earth model viscosity structure?

• Consider the “correction” to be applied to tide gauges, satellite altimetry and GRACE.

• Is the uncertainty in the correction significant compared to errors in the observations?

• Note: results based on a single global ice model.

Douglas, 1997

Employ Careful Selection Criteria to Minimise Influence of Solid Earth Motion

I

I

SLR=1.5±0.1 mm/yr

SLRGIA=1.8±0.1 mm/yr

Influence of Radial Mantle Viscosity Variations on GIA-Correction at Tide

Gauge Sites

LT: 70-120 km UMV: 0.1-1x1021 Pas LMV: 2-50x1021 Pas

GIA Contribution to Observations of Recent Cryosphere Changes?

Satellite Gravity

ICE SHEET OBSERVATIONS

Satellite Altimetry

Airborne Altimetry

Synthetic Aperture

Radar (InSAR)

SEA-LEVEL OBSERVATIONS

Proxy recordsTide Gauges

Satellite Gravity

Satellite Altimetry

• Adopt a few different ice models for Antarctic and Greenland and predict present-day crustal uplift and geoid rate signals.

• Consider only the on-going viscous Earth response to past variations of these ice sheets.

• Influence of Earth model uncertainty is not considered.

How Sensitive are GIA Contributions to Altimetry and GRACE Observations to Differences in

Current Ice Models?

Summary

• Solid Earth motion associated with past ice-ocean mass flux is a significant contaminant signal in observations related to sea-level changes (GRACE, tide gauges and proxy records, Satellite Altimetry) and cryosphere changes (Altimetry and GRACE).

• The accuracy of the climate signal inferred from these observations therefore depends on the accuracy of the GIA model correction.

• The correction applied is sensitive to the adopted ice history and Earth viscosity model.

Recommendations

• GIA community:

- Make predictions available (data correction and site selection)

- Continue to improve and refine Earth and ice components of model

• User community:

- Employ well-calibrated regional models if possible or…

- Use a suite of model predictions

- Use measurements of crustal motion