Synoptic Variability in Satellite Altimeter‐Derived Radar Freeboard of Arctic Sea Ice

Abstract

The Arctic's sea ice cover is retreating as the region continues to warm at nearly four times the global average rate (Rantanen et al., 2022). Alongside a decrease in extent and age (Stroeve & Notz, 2018), the sea ice is thinning (Kwok, 2018;Mallett et al., 2021) and snow depth is declining (Stroeve et al., 2020;Webster et al., 2014). A thinning ice pack affects the thermodynamic processes that govern seasonal ice melt and growth, as well as the dynamic processes that control ice mobility (e.g., Rampal et al., 2009). Assimilation of accurate sea ice thickness and snow depth data into models offers an opportunity to improve the prediction of future sea ice state (e.g., Holland et al., 2021;Mignac et al., 2022). Despite the importance of sea ice thickness, the most accurate estimates come from highly localized in situ observations from autonomous ice-buoys or upward-looking sonar instruments. While airborne-or submarine-based campaigns offer greater spatial coverage, they too remain temporally and spatially constrained. Satellite-mounted laser and radar altimeters offer a potential solution by providing year-round, pan-Arctic monitoring.Several studies have demonstrated an approach to convert Ku-band satellite radar altimeter freeboards from CryoSat-2 (CS2) and Sentinel-3 (S3) to sea ice thickness (Lawrence et al., 2019;Laxon et al., 2013). Sea ice freeboard, the height of the snow-ice interface relative to the surrounding ocean surface, is estimated from the return-time of a radar pulse. Thickness can be derived from the freeboard by applying the assumption of hydrostatic equilibrium together with assumptions concerning the snow, ice and water densities and the snow depth.

Arctic Freeboard and Snow Depth From Near‐Coincident CryoSat‐2 and ICESat‐2 (CRYO2ICE) Observations: A First Examination of Winter Sea Ice During 2020–2022

“…The relatively low C2I snow depth accumulation rate over MYI may also suggest that over thicker snow and older ice, the CS2 radar signal only penetrates a limited depth into the snow (as proposed by Ricker et al., 2015) as potentially suggested by the along‐track observations in Figure 3e. The sensitivity of CS2 radar freeboard observations to short‐term fluctuations in height following synoptic weather/snow‐depth events has been recently documented (Nab et al., 2023). Such weather events and snow accumulation could cause the increase in the CS2 freeboards and scattering horizon due to limited snow pack penetration and/or reflection within snow pack.…”

“…The study of Nab et al. (2023) presented some of the first results of synoptic variability in spaceborne altimeter‐derived radar freeboards, where they suggested that in the period immediately after a snowfall, radar pulses are not scattered from the snow‐ice interface. Furthermore, De Rijke‐Thomas et al.…”

“…Various events like rain-on-snow (Stroeve et al, 2022), flooding of snow packs and refreezing (snow-ice formation), changes in snow salinity (Nandan et al, 2017), brine wicking (Nandan et al, 2020;Rösel et al, 2021), and more, can change the geophysical properties of the snow pack and the principal back scattering horizon that is likely to be encountered by the propagating radar signal (Stroeve et al, 2022;Tonboe et al, 2021). The study of Nab et al (2023) presented some of the first results of synoptic variability in spaceborne altimeter-derived radar freeboards, where they suggested that in the period immediately after a snowfall, radar pulses are not scattered from the snow-ice interface. Furthermore, De Rijke-Thomas et al ( 2023) showed that the radar-scale roughness and slope distributions of the air-snow and snow-ice interfaces strongly impact Ku-band radar scattering from a nadir-looking airborne sensor, suggesting that smoother snow-ice interfaces characteristic of FYI can be more likely to accurately detect the snow-ice interface elevation.…”

“…This is done by assuming that laser/Ka-band signals backscatter at or close to the air-snow interface (Garnier et al, 2021;Guerreiro et al, 2016) and that the Ku-band signals fully penetrate the snow pack, or by calibrating Ka-band and Ku-band freeboards to the air-snow and snow-ice interfaces, respectively, using airborne observations available from the western Arctic (Lawrence et al, 2018). However, recent studies suggest that complete and zero backscattering horizons assumed for Ku-and Ka-band frequencies, respectively, are not necessarily valid for all conditions of the Arctic snow and sea ice pack (King et al, 2018;Nab et al, 2023;Nandan et al, 2023). Furthermore, the roughness within the footprint of the satellite at the scale of sea ice features (like ridges or leads) or small-scale roughness at the scale of the signal wavelength also impact the height of the mean backscattering intensity (Landy et al, 2020).…”

Retrieval of Snow Depth on Arctic Sea Ice From Surface‐Based, Polarimetric, Dual‐Frequency Radar Altimetry

“…Delays in autumn freeze‐up (e.g., Stroeve & Notz, 2018) have also reduced the amount of time during which snow can accumulate on sea ice, leading to shallower snow depths than observed in the past (e.g., Stroeve, Vancoppenolle, et al., 2021; Webster et al., 2014). All these changes add uncertainties to retrievals of snow depth and sea ice thickness from radar altimetry (Landy et al., 2020; Nab et al., 2023; Ricker et al., 2014), necessitating up to date studies of Ku‐ and Ka‐band radar interactions with snow‐covered sea ice with coincident field data for comparison.…”