An examination of the sensitivity of numerically simulated wildfires to low-level atmospheric stability and moisture, and the consequences for the Haines Index

Abstract

The Haines Index, an operational fire–weather index introduced in 1988 and based on the observed stability and moisture content of the near-surface atmosphere, has been a useful indicator of the potential for high-risk fires in low wind conditions and flat terrain. The Haines Index is of limited use, however, as a predictor of actual fire behavior. To develop a fire–weather index to predict severe or erratic wildfire behavior, an understanding of how the ambient lower-level atmospheric stability and moisture affects the growth of a wildfire is needed. This study is a first step in this process. This study investigates, through four comparative numerical simulations with a coupled wildfire–atmosphere model, the sensitivity of wildland fires to atmospheric stability and moisture, and in the process explores the correspondence between atmospheric stability and moisture, wildfire behavior, and the Haines Index. In the first three fire simulations, the model atmosphere was initially set to identical moisture but different instability conditions that correspond to Haines Indexes for low, moderate, and high potential for severe fire development. In the fourth fire simulation, the initial atmospheric and moisture conditions were for a high-risk fire Haines Index rating, but different from the initial conditions of dryness and stability of the previous experiments. The study indicates that high-risk fire development is sensitive to near-surface atmospheric stability and moisture, and that there is a range of atmospheric stability and moisture conditions that is important to the development of severe or erratic fire behavior, and that this range is within the atmospheric stability and moisture conditions represented by a Haines Index for high potential for severe fire. The analyses also suggest that there is a substantial latitude of fire behavior for fires rated as this Index, indicating that this Index should be further divided, or refined.

A decision support system for managing forest fire casualties

“…It is very useful for the forest managers to be able to simulate the temporal evolution of a fire and to estimate the costs related to the operations needed for fire defence, as well as to losses due to wildfire destruction (Jenkins, 2002;Vakalis et al, 2004). Simulations are based on a very detailed forest fire spread engine that calculates fire propagation and fire characteristics for every cell.…”

Climatological and statistical characteristics of the Haines Index for North America

“…Jenkins 2002Jenkins , 2004. Underlying these proposals is a stilltIDresolved operational and philosophical issue regarding the Haines Index and indices in general.…”

Evaluation of wildfire propagation susceptibility in grasslands using burned areas and multivariate logistic regression

“…Both temporal and spatial scales are beyond the limitation of the current fire behaviour simulations (McGrattan 2005). In current fire behaviour models (Rothermel 1972;Clark et al 1999;Jenkins 2002;Mell et al 2007), wind velocity and wind direction are the main factors. In this study, the wind factors and other meteorological data, such as precipitation and relative humidity, were excluded for the following reasons: (1) meteorological gauges in the grasslands do not provide wind data; (2) even if wind data were available, it would be difficult to incorporate this information over such a long time period (10 days or longer) into susceptibility modelling; (3) the grasslands are located in a semi-arid area, so there is very little precipitation during wildfire seasons, which means the grasslands endure extreme drought during this time; (4) the vast spatial scale requires meteorological data to be interpolated (Jiang, Liu, and Wang 2001); (5) the interpolation from the very few weather stations is not reliable, especially for precipitation (Skok and Vrhovec 2006;Gu, Shi, and Chen 2006); and (6) dead FMC is totally controlled by meteorological factors; consequently, it was excluded in our wildfire propagation susceptibility modelling.…”