Visualizing Ensembles with Python in the Prairie and Arctic Storm Prediction Center

In 2011, the Prairie and Arctic Storm Prediction Center (PASPC) in Winnipeg, Manitoba, Canada began a pilot project to introduce a greater use of ensemble products in an operational setting. The PASPC faces unique daily challenges in balancing heavy workloads and timely hazardous weather forecasting covering a large area of responsibility encompassing much of western and northern Canada. With its powerful assortment of scientific modules, Python provided an ideal platform for rapidly deploying, evaluating and redeveloping products on this scale based on immediate feedback from operational forecasters. Model data from the North American Ensemble Forecast System (NAEFS) and a custom mesoscale ensemble suite unique to the PASPC were used to visualize ensemble output tailored to the day-to-day needs of PASPC Operations. In addition to more standard fields, specialized data clustering and aggregation of multiple ensemble runs were also evaluated and revealed consistent limitations in the underlying numerical models. In this presentation, the utility and pitfalls of these new products are discussed, with emphasis to aiding and supporting operational forecasters.