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The ventilation index (VI) is an index that describes the potential for smoke or other pollutants to disperse from a source. In this study, a Lagrangian particle dispersion model was utilized to examine smoke dispersion and the diagnostic value of VI during a September 2018 prescribed fire in southwestern Colorado. Smoke dispersion in the vicinity of the fire was simulated using the FLEXPART-WRF particle dispersion model, driven by meteorological outputs from Advanced Regional Prediction System (ARPS) simulations of the background (non-fire) conditions. Two research questions are posed: (1) Is a horizontal grid spacing of 4 km comparable to the finest grid spacing currently used in operational weather models and sufficient to capture the spatiotemporal variability in wind and planetary boundary layer (PBL) structure during the fire? (2) What is the relationship between VI and smoke dispersion during the prescribed fire event, as measured by particle residence time within a given horizontal or vertical distance from each particle's release point? The ARPS no-fire simulations are shown to generally reproduce the observed variability in weather variables, with greatest fidelity to observations found with horizontal grid spacing of approximately 1 km or less. It is noted that there are considerable differences in particle residence time (i.e., dispersion) at different elevations, with VI exhibiting greater diagnostic value in the southern half of the domain, farthest from the higher terrain across the north. VI diagnostic value is also found to vary temporally, with diagnostic value greatest during the mid-morning to mid-afternoon period, and lowest during thunderstorm outflow passage in the late afternoon. Results from this study are expected to help guide the application of VI in complex terrain, and possibly inform development of new dispersion potential metrics. [ABSTRACT FROM AUTHOR]

The impact of a forest canopy on smoke concentration is assessed by applying a numerical weather prediction model coupled with a Lagrangian particle dispersion model to two low-intensity wildland (prescribed) fires in the New Jersey Pine Barrens. A comparison with observations indicates that the coupled numerical model can reproduce some of the observed variations in surface smoke concentrations and plume heights. Model sensitivity analyses highlight the effect of the forest canopy on simulated meteorological conditions, smoke concentrations, and plume heights. The forest canopy decreases near-surface wind speed, increases buoyancy, and increases turbulent mixing. Sensitivities to the time of day, plant area density profiles, and fire heat fluxes are documented. Analyses of temporal variations in smoke concentrations indicate that the effect of the transition from a daytime to a nocturnal planetary boundary layer is weaker when sensible heat fluxes from the fires are stronger. The results illustrate the challenges in simulating meteorological conditions and smoke concentrations at scales where interactions between the fire, fuels, and atmosphere are critically important. The study demonstrates the potential for predictive tools to be developed and implemented that could help fire and air-quality managers assess local air-quality impacts during low-intensity wildland fires in forested environments. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper, we describe and analyze a climatology of the Hot-Dry-Windy Index (HDW), with the goal of providing fire-weather forecasters with information about the daily and seasonal variability of the index. The 30-year climatology (1981–2010) was produced using the Climate Forecast System Reanalysis (CFSR) for the contiguous United States, using percentiles to show seasonal and geographical variations of HDW contained within the climatology. The method for producing this climatology is documented and the application of the climatology to historical fire events is discussed. We show that the HDW climatology provides insight into near-surface climatic conditions that can be used to identify temperature and humidity trends that correspond to climate classification systems. Furthermore, when used in conjunction with daily traces of HDW values, users can follow trends in HDW and compare those trends with historical values at a given location. More usefully, this climatology adds value to HDW forecasts; by combining the CFSR climatology and a Global Ensemble Forecast System (GEFS) ensemble history and forecast, we can produce a single product that provides seasonal, climatological, and short-term context to help determine the appropriate fire-management response to a given HDW value. [ABSTRACT FROM AUTHOR]

Atmospheric turbulent circulations in the vicinity of wildland fire fronts play an important role in the transfer of momentum into and out of combustion zones, which in turn can potentially affect the behavior and spread of wildland fires. The vertical turbulent transfer of momentum is accomplished via individual sweep, ejection, outward interaction, and inward interaction events, collectively known as sweep-ejection dynamics. This study examined the sweep-ejection dynamics that occurred before, during, and after the passage of a surface fire front during a prescribed fire experiment conducted in an open-canopied forest in the New Jersey Pine Barrens. High-frequency (10 Hz), tower-based, sonic anemometer measurements of horizontal and vertical wind velocity components in the vicinity of the fire front were used to assess the relative frequencies of occurrence of the different types of momentum-flux events, their contributions to the overall momentum fluxes, and their periodicity patterns. The observational results suggest that the presence of surface fire fronts in open-canopied forests can substantially change the sweep-ejection dynamics that typically occur when fires are not present. In particular, sweep events resulting in the downward transport of high horizontal momentum air from above were found to be more prominent during fire-front-passage periods. [ABSTRACT FROM AUTHOR]

Lower-tropospheric wind maxima, known as low-level jets (LLJs), play a vital role in weather and climate around the world. In this study, two 10-year (2006–2015) regional climate simulations using current (2011) and future (2100) land-use/land-cover (LULC) patterns over the continental United States (CONUS) are used to assess the sensitivity of LLJ properties, including jet occurrence, maximum speed, and the elevation of the maximum, to changes in LULC. The three simulated LLJ properties exhibit greater sensitivity in summer than in winter. Summertime jets are projected to increase in frequency in the central CONUS, where cropland replaces grassland, and decrease in parts of the Ohio-River Valley and the Southeast, particularly Florida, where urban expansion occurs. Little change is projected for wintertime jet frequency. Larger modifications to jet speed and elevations are projected in parts of the Ohio River Valley, the upper Southeast, and the Intermountain West. While there is some evidence of weaker, more elevated jets with urban expansion, the connection between changes in jet speed and elevation and changes in LULC patterns at a given location is weak. This result suggests that LULC will primarily affect the large-scale atmospheric conditions that contribute to the formation of LLJs, particularly in winter. [ABSTRACT FROM AUTHOR]