Fire weather indices are commonly used by fire weather forecasters to predict when weather conditions will make a wildland fire difficult to manage. Complex interactions at multiple scales between fire, fuels, topography, and weather make these predictions extremely difficult. We define a new fire weather index called the Hot-Dry-Windy Index (HDW). HDW uses the basic science of how the atmosphere can affect a fire to define the meteorological variables that can be predicted at synoptic-and meso-alpha-scales that govern the potential for the atmosphere to affect a fire. The new index is formulated to account for meteorological conditions both at the Earth’s surface and in a 500-m layer just above the surface. HDW is defined and then compared with the Haines Index (HI) for four historical fires. The Climate Forecast System Reanalysis (CFSR) is used to provide the meteorological data for calculating the indices. Our results indicate that HDW can identify days on which synoptic-and meso-alpha-scale weather processes can contribute to especially dangerous fire behavior. HDW is shown to perform better than the HI for each of the four historical fires. Additionally, since HDW is based on the meteorological variables that govern the potential for the atmosphere to affect a fire, it is possible to speculate on why HDW would be more or less effective based on the conditions that prevail in a given fire case. The HI, in contrast, does not have a physical basis, which makes speculation on why it works or does not work difficult because the mechanisms are not clear.

Among the key issues in smoke management is predicting the magnitude and location of smoke effects. These vary in severity from hazardous (acute health conditions and drastic visibility impairment to transportation) to nuisance (regional haze), and occur across a range of scales (local to continental). Over the years a variety of tools have been developed to aid in predicting smoke effects. This review follows the development of these tools, from various indices and simple screening models to complex air quality modelling systems, with a focus on how each tool represents key processes involved in smoke transport.

We present Daysmoke, an empirical-statistical plume rise and dispersion model for simulating smoke from prescribed burns. Prescribed fires are characterized by complex plume structure including multiple-core updrafts which makes modeling with simple plume models difficult. Daysmoke accounts for plume structure in a three-dimensional veering/sheering atmospheric environment, multiple-core updrafts, and detrainment of particulate matter. The number of empirical coefficients appearing in the model theory is reduced through a sensitivity analysis with the Fourier Amplitude Sensitivity Test (FAST). Daysmoke simulations for “bent-over” plumes compare closely with Briggs theory although the two-thirds law is not explicit in Daysmoke. However, the solutions for the “highly-tilted” plume characterized by weak buoyancy, low initial vertical velocity, and large initial plume diameter depart considerably from Briggs theory. Results from a study of weak plumes from prescribed burns at Fort Benning GA showed simulated ground-level PM_2.5 comparing favorably with observations taken within the first eight kilometers of eleven prescribed burns. Daysmoke placed plume tops near the lower end of the range of observed plume tops for six prescribed burns. Daysmoke provides the levels and amounts of smoke injected into regional scale air quality models. Results from CMAQ with and without an adaptive grid are presented.

The Fosberg fire weather index is a simple tool for evaluating the potential influence of weather on a wildland fire based on temperature, relative humidity and wind speed. A modification to this index that includes the impact of precipitation is proposed. The Keetch-Byram drought index is used to formulate a ‘fuel availability’ factor that modifies the response of the fire weather index. Comparisons between the original and modified indices are made using historical fire data from the Florida Division of Forestry. The addition of the fuel availability factor helps increase the utility of the fire weather index as it offers an improved relationship between the index and area burned.