A multi-frequency altimetry snow depth product over Arctic sea ice.

Sea ice thickness is an essential variable to understand and forecast the dynamic ice cover and can be estimated by satellite altimetry. Nevertheless, it is affected by uncertainties especially from snow depth, a key parameter to derive it from ice freeboard. We developed a snow depth product based on the differences between CryoSat-2 SAR Ku and IceSat-2 laser altimeters which have different snow penetration capabilities.

Scalable interpolation of satellite altimetry data with probabilistic machine learning.

We present GPSat; an open-source Python programming library for performing efficient interpolation of non-stationary satellite altimetry data, using scalable Gaussian process techniques. We use GPSat to generate complete maps of daily 50 km-gridded Arctic sea ice radar freeboard, and find that, relative to a previous interpolation scheme, GPSat offers a 504 × computational speedup, with less than 4 mm difference on the derived freeboards on average. We then demonstrate the scalability of GPSat through freeboard interpolation at 5 km resolution, and Sea-Level Anomalies (SLA) at the resolution of the altimeter footprint.