Rain on snow (ROS) understudied in sea ice remote sensing: a multi-sensor analysis of ROS during MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate)

Abstract

Abstract. Arctic rain on snow (ROS) deposits liquid water onto existing snowpacks. Upon refreezing, this can form icy crusts at the surface or within the snowpack. By altering radar backscatter and microwave emissivity, ROS over sea ice can influence the accuracy of sea ice variables retrieved from satellite radar altimetry, scatterometers, and passive microwave radiometers. During the Arctic Ocean MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, there was an unprecedented opportunity to observe a ROS event using in situ active and passive microwave instruments similar to those deployed on satellite platforms. During liquid water accumulation in the snowpack from rain and increased melt, there was a 4-fold decrease in radar energy returned at Ku- and Ka-bands. After the snowpack refroze and ice layers formed, this decrease was followed by a 6-fold increase in returned energy. Besides altering the radar backscatter, analysis of the returned waveforms shows the waveform shape changed in response to rain and refreezing. Microwave emissivity at 19 and 89 GHz increased with increasing liquid water content and decreased as the snowpack refroze, yet subsequent ice layers altered the polarization difference. Corresponding analysis of the CryoSat-2 waveform shape and backscatter as well as AMSR2 brightness temperatures further shows that the rain and refreeze were significant enough to impact satellite returns. Our analysis provides the first detailed in situ analysis of the impacts of ROS and subsequent refreezing on both active and passive microwave observations, providing important baseline knowledge for detecting ROS over sea ice and assessing their impacts on satellite-derived sea ice variables.

Sea ice in the Arctic Transpolar Drift in 2020/21: thermodynamic evolution of different ice types

“…The formation of snow ice and superimposed ice not only directly contribute to the ice mass balance but also alter active and passive microwave signals, which in turn affect any satellite remote sensing retrievals of sea ice geophysical variables. Such an effect has already been identified for the rain-on-ice event occurred on 13-14 September 2020 (Gabarró et al, 2022;Stroeve et al, 2022). As we have shown, subsequent close-to-zero air temperature and dynamic deformation events may promote the temporary melting of snow and the formation of snow ice or superimposed ice even during winter.…”

“…In addition, the abnormally large precipitation equivalent in the study region during the year 2020-2021 (Figure 4b), which may lead to a larger accumulation of snow, as well as formations of snow ice or superimposed ice, in the observation footprint of Ku-band synthetic aperture radar altimeter of CryoSat-2. Both processes can lead to the reduction of the penetrability of the altimeter in the snow layer (Ricker et al, 2014;Stroeve et al, 2022), thus leading to larger ice freeboard and greater retrieved ice thickness. This effect would be amplified during the freezing season as the snow thickening, which may also lead to a greater sea ice growth rate obtained by the CryoSat-2-SMOS product compared to the buoy measurement.…”

“…Subsequently, the ice started to cool from both above and below (Figure 6b). However, a pronounced warm air intrusion event occurred on 13-14 September, which was also accompanied by rainfall (Gabarró et al, 2022;Stroeve et al, 2022). This rain-on-snow event resulted in a slight snow melt of ~0.04 m, and a temporary warming of the top ice layer.…”

“…This rain-on-snow event resulted in a slight snow melt of ~0.04 m, and a temporary warming of the top ice layer. The liquid water deposited on the existing snowpack during this event has produced icy crusts at the surface or within the snowpack upon refreezing, resulting in the formation of superimposed ice at some sites of the CO3 (Stroeve et al, 2022). However, no superimposed ice was observed at the Level 1 site.…”

A long-term proxy for sea ice thickness in the Canadian Arctic: 1996–2020

“…This is illustrated well in Figure 7, where the SIT proxy product does in places differ from the local ULS SIT observations, but agrees well with CryoSat-2 observations in all panels. There are known limitations to CryoSat-2 SIT retrievals -e.g., the likely incorrect assumption that the Ku-band radar signal penetrates the snow layer in all cases (Willatt et al, 2011;Nandan et al, 2017;Stroeve et al, 2022;Nab et al, 2023), the instrument not being able to measure freeboards lower than 2.5 cm (Landy et al, 2020), and the need for a reliable snow depth product to convert from radar freeboard to SIT (Glissenaar et al, 2021) -which will propagate into this SIT proxy-product.…”