cffdrs: an R package for the Canadian Forest Fire Danger Rating System

Abstract

Introduction: The Canadian Forest Fire Danger Rating System (CFFDRS) is a globally known wildland fire risk assessment system, and two major components, the fire weather index system and the fire behavior prediction system, have been extensively used both nationally and internationally to aid operational wildland fire decision making. Methods: In this paper, we present an overview of an R package cffdrs, which is developed to calculate components of the CFFDRS, and highlight some of its functionality. In particular, we demonstrate how these functions could be used for large data analysis. Results and Discussion: With this cffdrs package, we provide a portal for not only a collection of R functions dealing with all available components in CFFDRS but also a platform for various additional developments that are useful for the understanding of fire occurrence and behavior. This is the first time that all relevant CFFDRS methods are incorporated into the same platform, which can be accessed by both the management and research communities.

Variability and drivers of burn severity in the northwestern Canadian boreal forest

“…Fire Weather Index System indexes were calculated from the interpolated temperature, precipitation, relative humidity, and wind speed using the cffdrs package (Wang et al. ), with starting values from the interpolated values of the FFMC, DMC, and DC from the previous day (Jain et al. ).…”

Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

“…Note that the marginal distributions of the seven bias corrected variables are identical for QDM, MBCp, MBCr, and MBCn; only the dependence between variables differs. In all cases, 3-hourly values are interpolated to 12:00 LST and FWI is calculated using software by Wang et al (2013).…”

Spatial Pattern of the Seasonal Drought/Burned Area Relationship across Brazilian Biomes: Sensitivity to Drought Metrics and Global Remote-Sensing Fire Products

“…All daily values were then averaged on a monthly time step. Only FWI components and SPEI in different time-scales were computed, respectively, by functions developed in fwi.fbp library [54] from R cran program [55] and the monthly data available in SPEI database [51], which covers the global frequency of SPEI at scales from 1 to 48 months at 0.5 • gridded spatial resolution [56], using the same CRU-NCEP climate variables. In this SPEI database, the reference period for the calculation corresponds to the whole study.…”