Speaker
Description
University of Calgary Space Remote Sensing (SRS) group operates a comprehensive network of autonomous space weather sensors from sub-auroral to polar cap latitudes. Currently this network consists of more than 120 sensors (auroral cameras, spectrographs, riometers, GNSS, and magnetometers) deployed across 33 sites in Canada, Alaska and Greenland. The operational framework supporting this sensor network includes more than 50,000 real-time data streams that enable automated assessment of instrument health and safety as well as verification of data quality and suitability for downstream real-time processing (e.g., space weather products). Recent work within the operational framework is targeted at higher-level data products that leverage multiple sensors to create continent scale, easily ingestible datasets. As these products transition to real-time availability (expected in the next 6 months) the intention is that they are publicly available to support/inform existing space weather models and systems. In this poster we highlight our newly released gridded optical dataset as one such example of this type of product, which integrates high resolution all-sky imager (ASI) data across several instrument networks into a common gridded format, considering individual instrument factors and calibrations. This dataset is aimed at lowering the barrier of usage for users who may want to incorporate auroral data into models or other space weather prediction systems and is tailored towards uniform information across the region of interest and ease-of-access for multiple applications (modelling, machine learning, visualization, etc.). As the production of these data products transitions to real-time availability (and latency of less than five minutes), more instrument data will be adapted into this format, furthering the capabilities to support, monitor, and advise systems, as well as advance predictive modelling efforts and impact assessment.
