Abstract
Abstract. We present a global high-resolution calculation of the Canadian Fire Weather Index (FWI) System indices using surface meteorology from the ERA5 HRES reanalysis for 1979–2018. ERA5 HRES represents an improved dataset compared to several other reanalyses in terms of accuracy, as well as spatial and temporal coverage. The FWI calculation is performed using two different procedures for setting the start-up value of the Drought Code (DC) at the beginning of the fire season. The first procedure, which accounts for the effects of inter-seasonal drought, overwinters the DC by adjusting the fall DC value with a fraction of accumulated overwinter precipitation. The second procedure sets the DC to its default start-up value (i.e. 15) at the start of each fire season. We validate the FWI values over Canada using station observations from Environment and Climate Change Canada and find generally good agreement (mean Spearman correlation of 0.77). We also show that significant differences in early season DC and FWI values can occur when the FWI System calculation is started using the overwintered versus default DC values, as is highlighted by an example from 2016 over North America. The FWI System moisture codes and fire behaviour indices are made available for both versions of the calculation at https://doi.org/10.5281/zenodo.3626193 (McElhinny et al., 2020), although we recommend using codes and indices calculated with the overwintered DC, unless specific research requirements dictate otherwise.
Highlights
Climate reanalyses provide a numerical and geospatial description of past and present climate (Bengtsson et al, 2007)
325 The Global Fire Weather Indices dataset developed from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5-HRS Reanalysis product is a publicly available global dataset that presents seven key variables representing fuel moisture (FFMC, Duff Moisture Code (DMC), Drought Code (DC)) and potential fire behavior (ISI, Build-up Index (BUI), Fire Weather Index (FWI), and Daily Severity Rating (DSR))
The dataset covers a period of 1979 to 2018 and accounts for the procedures of using the default DC or alternatively the overwintered DC to calculate fire behavior at fire season start-up. This dataset shows that there can be a significant difference in DC values, 330 at the beginning of the fire season, depending on which procedure is employed, suggesting that fire danger in some regions may be more severe than what is predicted by the default DC
Summary
Climate reanalyses provide a numerical and geospatial description of past and present climate (Bengtsson et al, 2007). This method of climate simulation assimilates weather observations into dynamic climate models of the atmosphere and relevant Earth systems to represent the atmospheric and surface states at a given time, usually for a historical period of multiple decades to near-present. Data configuration for the duration of the simulation, eliminating inhomogeneities that may occur through other modes of climate tracking, and providing a useful tool for studying weather-related phenomenon. In comparing observed and reanalysis-derived indices of fire weather, reanalyses have been found to be an effective tool for indicating fire danger (Bedia et al, 2012; Venalainen et al, 2014; Field et al, 2015). Other studies have investigated the relationship between fire weather indices calculated from reanalyses and measures of the fire regime, such as annual area burned (Bedia et al, 2014), trends in fire season length (Jain et al, 2017), and quantification of global
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