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Average vertical velocity of the ground predicted by our GIA model ensemble.

Standard deviation of the ground vertical velocity predicted by our GIA model ensemble.

Average Geoid rate predicted by our GIA model ensemble.

Standard deviation of the Geoid rate predicted by our GIA model ensemble.

Average gravity rate predicted by our GIA model ensemble.

Standard deviation of the gravity rate predicted by our GIA model ensemble.

Ground altitude with respect to the local sea level at the chosen time. Below 0, the ground is underwater.

Ground altitude with respect to the local sea level at the chosen time. Below 0, the ground is underwater.

Surface altitude of the oceans, relative to the present-day level.

Altitude of the top of the ice sheets and glaciers with respect to the local sea level at the chosen time.

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Covariance of Stokes Coefficients Rate




Expectation of Stokes Coefficients Rate

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Introduction

20,000 years ago, ice sheets covered not just Greenland and Antarctica, but also much of Canada, northern Europe and Patagonia, while the average sea level was about 120 meters/400 feet lower than today. We present here a reconstruction of the Earth surface during the last ice age.

This is a simulation of Glacial Isostatic Adjustment (GIA): the solid Earth response to the build and collapse of major ice sheets during the last glacial cycle (~120,000 years ago to present-day), and the associated changes in sea level. We used a numerical model featuring:

  • where, when, and how much ice thickness there was throughout the glacial cycle (the ice history).
  • how soft or stiff the rocks are at each depth inside the Earth, and how slow they deform (the mechanical structure of the Earth).

We performed more than 100,000 GIA simulations using variations of these parameters, and looked at how well they compared to geological records of where the sea level was in the past (i.e. corals, fossils characteristic of coastal area, raised beaches) and measures of the land uplift at present-day (GPS velocities). These calculations allowed us to determine what the GIA signal was on average, and what was the level of uncertainty affecting it.

For more information, see our publication: Caron, L., E.R. Ivins, E. Larour, S. Adhikari, J. Nilsson and G. Blewitt (2018), GIA model statistics for GRACE hydrology, cryosphere and ocean science, Geophys. Res. Lett., 45, doi:10.1002/2017GL076644.

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