Optimising Interannual Sea Ice Thickness Variability Retrieved From CryoSat‐2.

Satellite radar altimeters like CryoSat‐2 estimate sea ice thickness by measuring the return‐time of transmitted radar pulses, reflected from the sea ice and ocean surface, to measure the radar freeboard. Converting freeboard to thickness requires an assumption regarding the fractional depth of the snowpack from which the radar waves backscatter (α) $(\alpha)$. We derive sea ice thickness from CryoSat‐2 radar freeboard data with incremental values for α $\alpha $, for the 2010–2021 winter periods. By comparing these to sea ice thickness estimates derived from upward‐looking sonar moorings, we find that α $\alpha $ values between 35%–80% result in the best representation of interannual variability observed over first‐year ice, reduced to < ${< } $55% over multi‐year ice. The underestimating bias in retrievals caused by optimizing this metric can be removed by reducing the waveform retracking threshold to 20%–50%. Our results pave the way for a new generation of 'partial penetration' sea ice thickness products from radar altimeters. Plain Language Summary: Satellite altimeters like CryoSat‐2 can be used to estimate sea ice thickness by estimating how far sea ice floes stick out above the waterline. This is done by measuring the time taken for radar waves to travel to the surface of the ice floe and back to the altimeter. All current winter sea ice thickness estimates assume that the radar waves return entirely from the sea ice surface, and not from the overlying snow cover. A growing body of research suggests this may not be the case, with weather and snow conditions affecting the fraction of the detected radar power that comes from the ice surface. We consider how well CryoSat‐2 estimates capture whether the ice is thicker or thinner than usual at a given time of year. We find that its skill is highest when we assume that 35%–80% of the radar power comes from the sea ice surface, and 20%–65% comes from the snow surface. However, improving this aspect of skill makes the sea ice thickness estimates too low. To address this, we show that a simple change in the waveform processing method can counter this bias. Key Points: CryoSat‐2 retrievals of sea ice thickness have historically been tuned to minimize bias rather than to capture interannual variabilityWe use upward‐looking sonar moorings to tune the treatment of both waveform retracking and snowpack penetration by radar wavesTuning to optimize interannual variability indicates partial penetration for all retracking thresholds [ABSTRACT FROM AUTHOR]