2) in a mature pine forest fuel type on level terrain. The FWI system is strictly a weather-based system providing six main output indices representing fuel moisture and fire behavior potential (Fig. There are numerous reviews and summaries of the components of the CFFDRS (e.g., Stocks et al 1989 Taylor and Alexander 2006 Wotton 2009b) Lawson and Armitage ( 2008) also provide a detailed description of input and usage considerations for the CFFDRS as a whole, including the requirements for obtaining standardized weather observations.
These two systems have also been used extensively in training fire management personnel and studying the relationship between fire and climate change (e.g., Flannigan et al.
The FWI system and FBP system have been widely used to inform management actions such as preparedness planning, resource movement, resource needs assessment, alert levels, and active predictions of fire growth and intensity. Risk of fire occurrence (and expected number of fires), an important part of overall fire danger, is explicitly addressed within the fire occurrence prediction (FOP) System, though no nationally consistent set of equations or methods have been published to date. 1997, Wotton 2009a), at different times of day (Van Wagner 1977), to supplement the three main daily moisture codes used in the FWI System.
#Fire weather calculator series
The accessory fuel moisture (AFM) system provides a series of methods for estimating moisture content in different fuels (Lawson et al. 2009) provide the foundation of wildland fire environment assessment for operational forest fire management decision making across Canada. The Canadian Forest Fire Weather Index (FWI) System (Van Wagner and Pickett 1985 Van Wagner 1987) and the Canadian Forest Fire Behavior Prediction (FBP) System (FCFDG 1992 Hirsch 1996 Wotton et al. The CFFDRS consists of four linked components (Fig. In recent years, a growing number of other countries around the world (e.g., France, Indonesia, Malaysia, Mexico, New Zealand, Portugal, Spain, and the USA) have begun to incorporate the outcome of this research, which is collected in a framework called the Canadian Forest Fire Danger Rating System, into their wildfire operations planning. 2015).įor over 80 years, research on wildland fire ignition and behavior has been incorporated into the operational decision making within wildland fire management agencies in Canada. 2009) and in the near future (e.g., de Groot et al. These expenditures have been and will continue to rise due to more frequent fire occurrences and extreme fire weather conditions in the recent years (e.g., Beverly et al. Canadian wildland fire management agencies spend an average of $800 million per year on fire management. Although wildfire is a natural agent of disturbance over most of the forest landscape of Canada, it is managed when human life, settlements, and infrastructure are at risk. In Canada, an average of about 8000 forest fires occurs each year burning 2 Mha of forests, most of which is burned by stand-renewing, high-intensity crown fire. 2006), which is between 50~90 Mha (Schultz et al. 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.įorest fires are responsible for 14~20% of the annual global burned area (Mouillot and Field 2005 van der Werf et al. 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. In particular, we demonstrate how these functions could be used for large data analysis. 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. 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.
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