Senior Research Scientist
Julienne Stroeve is a senior scientist at the National Snow and Ice Data Center, specializing in remote sensing of the crysophere. She is also affiliated with the University of Manitoba during a seven-year tenure there as a Canada C150 Chair, and also as a Professor at University College London. Her research groups focus on improving sea ice retrievals using satellites, the impacts of sea ice loss on extreme weather events and northern communities, and future projections of ice conditions. She regularly conducts fieldwork in the Arctic and Antarctic to collect validation data for sea ice algorithms as well as deploy buoys and moorings. Stroeve’s work is regularly featured in documentaries, and at policy meetings. She is passionate about informing policy makers and the general public about the urgency of limiting global warming to less than 2°C.
Improving satellite retrievals of ice thickness and snow depth: Sea ice thickness and snow depth play key roles in the energy balance of the Arctic. Radar and laser altimeters provide a means to retrieve sea ice thickness and snow depth over sea ice on a pan-Arctic scale, yet neither of these systems directly measure the ice thickness or the snow depth. Instead they infer the height of the ice (or someplace in the snowpack) above the ocean surface (radar altimetry) or the height of the snow plus ice above the ocean surface (laser altimetry). In other words, thickness is inferred from radar or laser freeboards. To convert either observation to ice thickness requires information on snow depth and density, as well as ice density. Another complication is that radar freeboard will depend strongly on frequency and snowpack properties (density, salinity, temperature). Thus, while some studies have suggested the difference between radar and laser freeboards can provide an estimate of snow depth, this will depend strongly on snowpack properties. To better understand how snowpack properties impact radar backscatter, Stroeve and colleagues deployed a dual-frequency Ka/Ku band radar during the year-long MOSAiC Arctic drift expedition. This data is providing insights on how to improve retrieval of both ice thickness and snow depth with current and future planned satellite missions.