Developing user-informed fire weather projections for Canada
Laura Van de Vliet, Jeremy Fyke, Sonya Nakoneczny, Trevor Q. Murdock, Pouriya Jafarpur
Abstract
• Novel fire weather projections based on bias adjusted regional climate model output. • Substantial, robust increases in fire weather projected across most of Canada. • User feedback informed product development and delivery mechanism. • Fire weather projections available at https://climatedata.ca/fire-weather/ . Increasing fire danger due to climate-driven fire weather changes has expanded demand for projections of future wildfire information for Canada. Addressing this need, we developed “CanLEAD-FWI,” consisting of novel, high-resolution projections of fire weather and an associated user-facing climate services delivery mechanism. Based on the Canadian Forest Fire Weather Index (FWI) System ( Van Wagner, 1987 ) with multivariate bias-adjusted output from the CanLEAD-CanRCM4-EWEMBI large ensemble ( Cannon et al., 2021 ), CanLEAD-FWI provides various wildfire-relevant indicators. Comparison against two gridded observation-based datasets provides an estimate of observational uncertainty in historical FWI System component extremes, with historical CanLEAD-FWI generally situated between these two datasets. Over the 21st century, CanLEAD-FWI projects substantial, robust increases in the severity and frequency of high fire weather and a lengthening fire season across much of Canada, although the magnitude and spatial extent of increases depend on the metric and FWI System component. To enhance data utility for decision-making and consider diverse user needs, we integrated two rounds of user engagement into product development. A web-based application was designed to address user feedback, support best practices, and reduce decision overload. CanLEAD-FWI addresses a growing need in the Canadian climate services space for both projected climate impact data and associated training and support. By combining user feedback, best practices for climate services, and expert knowledge, we aim to enhance the appropriate integration of fire weather information into long-term decision-making.