Improved Canadian Arctic Sea Ice Thickness Estimates
Communities in the Canadian Arctic depend on the sea ice for traditional hunting and harvesting activities. The presence of sea ice also protects coastal communities from waves during storms. The loss of sea ice however is impacting stability of the ice, making travel across sea ice less predictable and more dangerous, and coastal communities are more at risk to storm surges. Ecosystems that depend on the ice area also changing rapidly, with still unknown impacts on ocean primary productivity, while polar bears, seals and whales are having to find new habits. As sea ice continues to decline, it is imperative to better understand the drivers of current and future sea ice changes so that we can improve our ability to forecast ice conditions at various time-scales, from near-real-time for safe marine navigation, to seasonal and decadal for planning purposes.
Satellite-based observations are the only way to observe sea ice changes on a large spatial and temporal time-scales. While 40 years of sea ice concentration have been retrieved from satellite, documenting how quickly sea ice is declining in the Canadian Arctic, we do not have a similarly long-term data record of sea ice thickness. New satellite systems are starting to improve our ability to observe sea ice thickness at large spatial scales. Ice thickness is a central state variable used to initialize seasonal ice forecasting in prediction models such as the Canadian Seasonal to Interannual Prediction System (CanSIPS) and are crucial for supporting safer marine operations. This project will address a critical research gap that impacts the accuracy of satellite-derived sea ice thickness estimates from the Canadian Arctic. In particular, this project will integrate newly developed snow products along with ice freeboard data from the from the European Space Agency’s (ESA) space-based CryoSat-2 radar altimeter and NASA’s ICESat-2 laser altimeter, to improve sea ice thickness estimates within the context of regional-scale seasonal ice forecasting.