Sea ice is frozen sea water that insulates the atmosphere from the ocean in the polar regions. Sea ice is at the same time a key indicator, and a key actor of the changing climate with implications at all latitudes. Pushed by winds and ocean currents, sea ice is always on the move. Sea ice motion reacts to the changing polar environment, be it the changes of the sea ice itself (e.g. thinner sea ice tends to move faster) or of its driving forces (stronger winds push sea ice farther). Both in the Arctic and Antarctic, trends in sea ice motion have been documented from long records of observations. Sea ice motion is both straightforward and challenging to measure. On the one hand, it does not require advanced instrumentation: a GNSS receiver is enough to record the successive positions of an on-ice platform and assemble a trajectory. From the satellite view-point, the motion tracking algorithms rely mostly on image processing techniques that do not require advanced understanding of the physics of the ice motion, nor of the interaction of the electromagnetic signal with the sea ice. On the other hand, sea-ice motion is a vector quantity which adds complexity when defining it (is it a velocity? a net displacement over a specified time duration? what unit should we use?), storing it (as magnitude/direction? as vector components? along which axes to define the components ?) and comparing different sources (comparison over similar time duration, point-like vs area measurement, etc…) Non-linear transformations are frequently involved (e.g. from vector components to velocities) that can introduce pseudo-biases making it difficult to compare climate trends. As of today, there does not exist rigorous metrology approaches to uncertainty characterization of satellite-based sea-ice motion algorithms or data products, and cal/val exercises rely heavily on comparison to on-ice trajectories. How do we improve from there? In this contribution, we introduce the challenges posed by observing sea-ice motion for climate change monitoring. We raise the questions introduced above, aiming at identifying recommendations for standardization and best practices to harmonize the approaches and reduce the danger for sub-optimal exploitation of existing and future observing capabilities.
Topic : Theme 1: Cryosphere monitoring.
Reference : T1-E8
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