Evaluation of Gridded Precipitation Data and Interpolation Methods for Forest Fire Danger Rating in Alberta, Canada
The Canadian Forest Fire Weather Index (FWI) System is the primary measurement of wildfire danger in Canada. Among the four weather inputs of the FWI System indices, interpolating the daily precipitation is a key challenge of mapping fire danger in remote areas.
This work compares the performance of the Canadian Precipitation Analysis (CaPA) System and six interpolation methods to find the best fire danger rating in Alberta, Canada. Results showed that the CaPA System had only average performance due to limited radar coverage (10%) in the forested area. However, using the CaPA System as a covariate in an interpolation method called regression kriging produced significantly better precipitation and FWI System estimates. Accurately estimating the fire danger will result in better daily preparedness planning (e.g., resource allocation) for the wildfire management agencies. We propose that the fire danger indices can be improved by using regression kriging to combine gridded estimates (i.e., CaPA System) and weather station observations.
Performance of interpolation methods increased with greater weather station density. We found a threshold of > 0.5 weather stations /10 000 km2 is needed for regression kriging with CaPA to become appreciably better than the CaPA System alone. Alternatively, we recommend that Environment and Climate Change Canada (ECCC) assimilate data from the Alberta fire weather station network into the CaPA System for more accurate precipitation estimates as the two weather station networks are independent.
Xinli Cai authored this research as part of her MSc. degree under the supervision of Dr. Mike Flannigan at the University of Alberta. This research was recently published in the Journal of Geophysical Research: Atmospheres.
Currently, Xinli and her colleagues at the Northern Forestry Centre, CFS are working on optimizing the interpolation algorithms used in the Canadian Spatial Fire Management System (SFMS). Xinli is currently rebuilding the national fire weather database (1979-2018) by integrating weather station observations from the provincial fire management agencies and ECCC and recalculating the FWI using improved interpolation algorithms.