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Towards drift-aware products for sea ice freeboard and thickness, retrieved from satellite altimetry

1 NORCE Norwegian Research Centre

2 Norwegian Meteorological Institute

3 Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research

Robert Ricker1, Thomas Lavergne2, Stefan Hendricks3, Stephan Paul3, Emily Down2, Mari Anne Killie2

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Diana Juncher/ESO, CC BY 4.0

Motion Blur

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Diana Juncher/ESO, CC BY 4.0

Motion Blur

in sea ice freeboard/thickness maps derived from satellite altimetry

Current approach to produce monthly maps:

Daily trajectories

e.g., ICESat-2 ATL10

Collecting trajectories over 1 month

Monthly grid

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Diana Juncher/ESO, CC BY 4.0

Motion Blur

in sea ice freeboard/thickness maps derived from satellite altimetry

ICESat-2 trajectories 1 Nov 2020

Sea ice dynamics during MOSAiC expedition

(drift within 1 month)

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Diana Juncher/ESO, CC BY 4.0

Motion Blur

in sea ice freeboard/thickness maps derived from satellite altimetry

  • Typically, trajectories are collected over a month and averaged within grid cells, regardless the timing of data acquisition and drifting sea ice

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  • Sea ice becomes more mobile in a changing Arctic

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  • Future satellite altimeter sensors will allow for higher resolutions, requiring reduction of motion blur in gridded data

ICESat-2 trajectories 1 Nov 2020

(drift within 1 month)

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Diana Juncher/ESO, CC BY 4.0

Research questions

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  • How can we compensate for motion blur?

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  • What is the impact of motion blur in monthly ice thickness maps derived from satellite altimetry?

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ICESat-2 trajectories 1 Nov 2020

(drift within 1 month)

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Drift-corrected parcel clouds

CCI sea ice drift

CCI sea ice concentration

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Concept for drift-awareness

Daily trajectories

(e.g., freeboard)

Daily parcels

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*.geojson

Full stack

3

Growth corrected stack

4

*.netcdf

Drift-aware gridded product

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Concept for drift-awareness

y

x

t

(z)

t - 15

t + 15

t - 14

t + 14

  • Synergizing sea ice freeboard/thickness and ice motion data

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  • Multidimensional point clouds are produced daily and contain the drift corrected sea ice parcels over a given time span (Lagrangian perspective)

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  • To receive daily sea ice freeboard and thickness maps, the point clouds are evaluated on a grid (Eulerian perspective)

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Full Stack

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Preliminary results – Using ICESat-2 ATL 10

  • Improved mapping of spatial thickness distributions

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  • Daily sea ice freeboard maps

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  • Partial pole hole eclipsing

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  • Reduced “Trackiness”

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Daily Drift-Aware freeboard from October 2020 – April 2021

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Time window: 1 month, +/- 15 days

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Preliminary results – Using NASA’s ICESat-2 ATL 10

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Time offset between target day and day of data acquisition within one month

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Preliminary results – Using NASA’s ICESat-2 ATL 10

Linear distance between location of data acquisition and target day within one month

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Difference between drift-aware and conventional maps

E. Greenland

Beaufort Sea

Drift-aware – Conv.

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Difference between drift-aware and conventional maps

E. Greenland

Beaufort Sea

Drift-aware – Conv.

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What to take home?

  • Daily drift-aware sea ice thickness maps through synergizing sea ice altimetry and ice motion products from passive microwave
  • Improvement of the spatial sea ice freeboard/thickness distributions
  • But likely no significant changes in time series and trends of Arctic/Antarctic mean values
  • Towards a new generation of Level 4 products for sea ice thickness

This work is part of the

ESA Climate Change Initiative