Statistical modelling of wildfire size and intensity: a step toward meteorological forecasting of summer extreme fire risk

C Hernandez,P Drobinski,C Keribin,S Turquety

doi:10.5194/angeo-33-1495-2015

Abstract

Abstract. In this article we investigate the use of statistical methods for wildfire risk assessment in the Mediterranean Basin using three meteorological covariates, the 2 m temperature anomaly, the 10 m wind speed and the January–June rainfall occurrence anomaly. We focus on two remotely sensed characteristic fire variables, the burnt area (BA) and the fire radiative power (FRP), which are good proxies for fire size and intensity respectively. Using the fire data we determine an adequate parametric distribution function which fits best the logarithm of BA and FRP. We reconstruct the conditional density function of both variables with respect to the chosen meteorological covariates. These conditional density functions for the size and intensity of a single event give information on fire risk and can be used for the estimation of conditional probabilities of exceeding certain thresholds. By analysing these probabilities we find two fire risk regimes different from each other at the 90 % confidence level: a "background" summer fire risk regime and an "extreme" additional fire risk regime, which corresponds to higher probability of occurrence of larger fire size or intensity associated with specific weather conditions. Such a statistical approach may be the ground for a future fire risk alert system.

Highlights

IntroductionAmong the first are the fire risk indices, such as the Canadian Fire Weather Index (Van Wagner, 1974, 1987; Van Wagner and Pickett, 1985)
In order to better manage fire risk, several methods have been investigated
Among the first are the fire risk indices, such as the Canadian Fire Weather Index (Van Wagner, 1974, 1987; Van Wagner and Pickett, 1985). This index relates to the expected intensity of the fire line, expressed in energy output rate per unit length of fire front. It is currently used as a fire risk indicator by the European Forest Fire Information System (EFFIS) of the Joint Research Center (JRC) of the European Commission

Summary

Introduction

Among the first are the fire risk indices, such as the Canadian Fire Weather Index (Van Wagner, 1974, 1987; Van Wagner and Pickett, 1985) This index relates to the expected intensity of the fire line, expressed in energy output rate per unit length of fire front. It can be used in conjunction with the Canadian Fire Weather Index but is deemed less informative These indices are empirically calibrated for predicting whether the atmospheric and hydrological conditions are prone to fire development. More in-depth simulations, using fully physical models such as FIRETEC (Linn et al, 2002), can provide accurate predictions of the propagation of a fire This method can be very demanding computation-wise

Objectives

Methods

Conclusion