On the projection of future fire danger conditions with various instantaneous/mean-daily data sources

S Herrera,J Fernández,J M Moreno,J M Gutiérrez,J Bedia

doi:10.1007/s10584-012-0667-2

S Herrera, J Fernández + Show 3 more

Open Access

https://doi.org/10.1007/s10584-012-0667-2

Copy DOI

Abstract

Fire danger indices are descriptors of fire potential in a large area, and combine a few variables that affect the initiation, spread and control of forest fires. The Canadian Fire Weather Index (FWI) is one of the most widely used fire danger indices in the world, and it is built upon instantaneous values of temperature, relative humidity and wind velocity at noon, together with 24 hourly accumulated precipitation. However, the scarcity of appropriate data has motivated the use of daily mean values as surrogates of the instantaneous ones in several studies that aimed to assess the impact of global warming on fire. In this paper we test the sensitivity of FWI values to both instantaneous and daily mean values, analyzing their effect on mean seasonal fire danger (seasonal severity rating, SSR) and extreme fire danger conditions (90th percentile, FWI90, and FWI>30, FOT30), with a special focus on its influence in climate change impact studies. To this aim, we analyzed reanalysis and regional climate model (RCM) simulations, and compared the resulting instantaneous and daily mean versions both in the present climate and in a future scenario. In particular, we were interested in determining the effect of these datasets on the projected changes obtained for the mean and extreme seasonal fire danger conditions in future climate scenarios, as given by a RCM. Overall, our results warn against the use of daily mean data for the computation of present and future fire danger conditions. Daily mean data lead to systematic negative biases of fire danger calculations. Although the mean seasonal fire danger indices might be corrected to compensate for this bias, fire danger extremes (FWI90 and specially FOT30) cannot be reliably transformed to accommodate the spatial pattern and magnitude of their respective instantaneous versions, leading to inconsistent results when projected into the future. As a result, we advocate caution when using daily mean data and strongly recommend the application of the standard definition for its calculation as closely as possible. Threshold-dependent indices derived from FWI are not reliably represented by the daily mean version and thus can neither be applied for the estimation of future fire danger season length and severity, nor for the estimation of future extreme events.

Highlights

Climate and weather are key controlling factors of wildfire occurrence and spread (Rothermel, 1972; Chandler et al, 1983), and studies around the globe show that fire activity is closely related to these variables (Flannigan and Harrington, 1988; Vazquez and Moreno, 1993; Littell et al, 2009; Carvalho et al, 2008; Good et al, 2008; Costa et al, 2011)
In order to assess the skill of daily mean Fire Weather Index (FWI) to detect extreme events, defined as values above FWI90, we identified extreme events using the 12-UTC FWI and we computed the probability of detection (POD) as the percentage of those extreme events detected by the daily mean FWI
We considered again seasonal severity rating (SSR), FWI90 and frequency-over-threshold 30 (FOT30) and analyzed the results of the A1B transient projections obtained with the regional climate model (RCM)

Summary

Introduction

Climate and weather are key controlling factors of wildfire occurrence and spread (Rothermel, 1972; Chandler et al, 1983), and studies around the globe show that fire activity is closely related to these variables (Flannigan and Harrington, 1988; Vazquez and Moreno, 1993; Littell et al, 2009; Carvalho et al, 2008; Good et al, 2008; Costa et al, 2011). Understanding the links between climate/weather and wildfires in the past is important for fire management planning in fire-prone regions. This understanding is utmost critical for projecting climate change impacts in future fire activity due to the projected changes in climate extremes favoring fire in many regions of the world (Seneviratne et al, 2012). Forest fires agencies have used for decades various fire danger indices to characterize fire potential in a region by combining the relevant climatic variables into one or a few values (Fugioka et al, 2009), leading to indices that act as meters that allow comparisons among fire seasons and across fire regions, and that can be used to project future changes in fire potential due to global warming (Stocks et al, 1998; Brown et al, 2004; Hennessy et al, 2005; Moriondo et al, 2006)

Objectives

Methods

Results

Conclusion