Interactive data visualization tool for public understanding of seasonal and interannual changes in sea ice climate indicator

This KM project will translate an existing, previously MEOPAR supported, Google Earth Engine (GEE)-based algorithm for time series analysis of satellite data into an Earth Engine App usable by the public. The algorithm currently extracts a cloud-free, filtered, optical reflectance time series signal of satellite optical reflectance information for 20+ years from the open access MODIS and Lansdat archives.It is initiated by the selection of a point location on a map and can produce a reflectance series for an area as small as 500m by 500m. The output is further decomposed into a set of sea ice indicators linked to physically based reflectance behaviours and thresholds: freeze-up, melt onset, ice break-up, open water. Inter-annual variability and trends in these indicators can be assessed in climate, biogeochemical, and sea ice usage/safety contexts. Key to this KM project is to build on the code and turn it into a published GEE App that is user-friendly for researchers and the public alike, is dynamic and shareable, and enables interaction in spatial and temporal domains. Users will interact with the App and easily access results in order to answer their own questions related to sea ice indicators.