CoAuthors

Donghui Yi (NOAA Laboratory for Satellite Altimetry, USA); Oliwia Baney (University of Maryland, USA); Kyle Duncan (University of Maryland, USA)

The Arctic Ocean experiences enhanced sensitivity to global temperature increases due to the positive sea-ice ocean albedo feedback. This has resulted in an acceleration of warming in the Arctic region since 2000, where temperatures are now rising at rates 2-3 times the global average. In turn this warming has contributed to the continued downward trend in sea ice extent over the last three decades and recent evidence suggests that this decline can impact mid-latitude weather.

Here we discuss exploiting satellite laser and radar altimeter (LaRA) observations of the ice cover to better constrain the evolution of snow depth on sea ice. Snow on Arctic sea ice has a long correlation length-scale (order kilometers) since snow accumulation on the sea ice cover, and its redistribution, are associated with synoptic events. Thus, obtaining direct estimates of snow on sea ice is also useful for constraining the precipitation over the Arctic Ocean in winter. In addition, knowledge of the seasonal evolution of snow depth on sea ice provides important insights about changes in marine mammal habitat.

In August 2020, as part of the ESA Cryo2Ice program, the semi-major axis of the CryoSat-2 orbit was raised by ~900 m providing periodic synchronicity in the longitude of both the ICESat-2 and CryoSat-2 satellites, every 19th CryoSat-2 revolution and 20th ICESat-2 revolution. Here we exploit the Cryo2Ice orbit resonance to perform cross-calibration of sea ice and lead heights at two electromagnetic frequencies. Using Cryo2Ice data we estimate the seasonal evolution of snow depth on sea ice. To do this we exploit the difference in radar and laser penetration depths into the snow pack. Typically, in dry snow conditions, the laser return from ICESat-2 originates from the air/snow interface, while the return from CryoSat-2 is from the snow/ice interface. We combine freeboard measurements retrieved from different scattering horizons to directly estimate the snow depth. Focusing on the last three winter periods (2018-2021) we demonstrate remarkable consistency between the two independent estimates of sea ice freeboard and we discuss the evolution of snow on sea ice throughout the winter season. Our results demonstrate the relationship between snow depth and ice type/age, wherein deeper snow is seen to accumulate over multi-year ice, in line with previous studies. Ultimately this work will lead to improved estimates of sea ice thickness from satellite techniques, since all current ice thickness retrieval techniques (from both altimeters, passive microwave, and infrared methods) require an estimate of snow depth as an auxiliary input parameter.