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The ambient atmospheric environment affects the growth and spread of wildland fires, whereas heat and moisture released from the fires and the reduction of the surface drag in the burned areas can significantly alter local atmospheric conditions. Observational studies on fire–atmosphere interactions have used instrumented towers to collect data during prescribed fires, but a few towers in an operational-scale burn plot (usually > 10 3 m2) have made it extremely challenging to capture the myriad of factors controlling fire–atmosphere interactions, many of which exhibit strong spatial variability. Here, we present analyses of atmospheric turbulence data collected using a 4 × 4 array of fast-response sonic anemometers during a fire experiment on a 10 m × 10 m burn plot. In addition to confirming some of the previous findings on atmospheric turbulence associated with low-intensity surface fires, our results revealed substantial heterogeneity in turbulent intensity and heat and momentum fluxes just above the combustion zone. Despite the small plot (100 m2), fire-induced atmospheric turbulence exhibited strong dependence on the downwind distance from the initial line fire and the relative position specific to the fire front as the surface fire spread through the burn plot. This result highlights the necessity for coupled atmosphere–fire behavior models to have 1–2 m grid spacing to resolve heterogeneities in fire–atmosphere interactions that operate on spatiotemporal scales relevant to atmospheric turbulence. The findings here have important implications for modeling smoke dispersion, as atmospheric dispersion characteristics in the vicinity of a wildland fire are directly affected by fire-induced turbulence. [ABSTRACT FROM AUTHOR]

The ambient atmospheric environment affects the growth and spread of wildland fires, whereas heat and moisture release from the fires and the reduction of the surface drag in the burned areas can significantly alter local atmospheric conditions. Observational studies on fire-atmosphere interactions have used instrumented towers to collect data during prescribed fires, but a few towers in an operational scale burn plot (usually > 10³ m²) have made it extremely challenging to capture the myriad of factors controlling fire-atmosphere interactions, many of which exhibit strong spatial variability. Here, we present analyses of atmospheric turbulence data collected using a 4×4 array of fast-response sonic anemometers during a fire experiment on a 10 m × 10 m burn plot. In addition to confirming some of the previous findings on atmospheric turbulence associated with low-intensity surface fires, our results revealed substantial heterogeneity in turbulent intensity and heat and momentum fluxes just above the combustion zone. Despite the small plot (100 m²), fire-induced atmospheric turbulence exhibited strong dependence on the downwind distance from the initial line fire and the relative position specific to the fire front as the surface fire spread through the burn plot. This result highlights the necessity for coupled atmosphere-fire behavior models to have 1–2 m grid spacing to resolve heterogeneities in fire-atmosphere interactions that operate on spatiotemporal scales relevant to atmospheric turbulence. The findings here have important implications for modeling smoke dispersion, as atmospheric dispersion characteristics in the vicinity of a wildland fire are directly affected by fire-induced turbulence. [ABSTRACT FROM AUTHOR]

Fire lines are complex phenomena with a broad range of scales of cross-line dimension, undulations, and along-line variation in heating rates. While some earlier studies have examined parcel processes in two-dimensional simulations, the complexity of fire lines in nature motivates a study in which the impact of three-dimensional fire line details on parcel processes is examined systematically. This numerical modeling study aims to understand how fundamental processes identified in 2D simulations operate in 3D simulations where the fire line is neither straight nor uniform in intensity. The first step is to perform simulations in a 3D model, with no fire line undulations or inhomogeneity. In general, convective modes simulated in the 2D model are reproduced in the 3D model. In one particular case with strong vertical wind shear, new convection develops separate from the main line of convection as a result of local changes to parcel speed and heating. However, in general the processes in the 2D and 3D simulations are identical. The second step is to examine 3D experiments wherein fire line shape and along-line inhomogeneity are varied. Parcel heating, as well as convective mode, is shown to exhibit sensitivity to fire line shape and along-line inhomogeneity. DOI: 10.1175/2009JAS3226.1

Wildfires are capable of inducing atmospheric circulations that result predominantly from large temperature anomalies produced by the fire. The fundamental dynamics through which a forest fire and the atmosphere interact to yield different convective regimes is still not well understood. This study uses the Advanced Regional Prediction System (ARPS) model to investigate the impact of the environmental (i.e., far upstream, undisturbed by fire) wind profile on dry convection above a prescribed heat source of an intensity and spatial scale comparable to a wildfire. Dimensional analysis of the fire-atmosphere problem provides two relevant parameters: a surface buoyancy parameter that addresses the amount of heat a parcel of air receives in transiting above the fire and an advection parameter that addresses the degree to which the environmental wind advects updrafts away from the fire. Two-dimensional simulations are performed in which the upstream surface wind speed and mixed layer mean wind speed are varied independently to better understand the fundamental processes governing the organizational mode and updraft strength. The result of these experiments is the identification of two primary classes of dry convection: plume and multicell. Simulated plume cases exhibit weak advection by the mean wind and are subdivided into intense plume and hybrid classes based on the degree of steadiness within the convection column. Hybrid cases contain columns of largely discrete updrafts versus the more continuous updraft column associated with the intense plume mode. Multicell cases develop with strong mixed layer advection and are subdivided into strong and weak classes based on the depth of convection. Intense plume and strong multicell (hybrid and weak multicell) cases occur when the surface buoyancy is large (small). Parcel analyses are performed to more closely examine the forcing of convection within different areas of the parameter space. The multicell (strong and weak) and intense plume modes are forced by a combination of buoyancy and dynamic pressure gradient forcing associated with the perturbation wind field, whereas the hybrid mode is forced by a combination of buoyancy and dynamic pressure gradient forcing associated with the strong background shear. The paper concludes with a discussion of the degree of nonlinearity that is likely to exist at the fire front for each of the convective modes; nonlinear fire behavior is most likely for the hybrid mode and least likely for the weak multicell mode. Knowledge of the sensitivity of the convective mode to upstream conditions can provide information about the degree of nonlinear or erratic fire behavior expected for a given wind profile upstream of the fire.

Mesoscale models are a class of atmospheric numerical model designed to simulate atmospheric phenomena with horizontal scales of about 2–200 km, although they are also applied to microscale phenomena with horizontal scales of less than about 2 km. Mesoscale models are capable of simulating wildland fire impacts on atmospheric flows if combustion byproducts (e.g., heat, smoke) are properly represented in the model. One of the primary challenges encountered in applying a mesoscale model to studies of fire-perturbed flows is the representation of the fire sensible heat source in the model. Two primary methods have been implemented previously: turbulent sensible heat flux, either in the form of an exponentially-decaying vertical heat flux profile or surface heat flux; and soil temperature perturbation. In this study, the ARPS-CANOPY model, a version of the Advanced Regional Prediction System (ARPS) model with a canopy submodel, is utilized to simulate the turbulent atmosphere during a low-intensity operational prescribed fire in the New Jersey Pine Barrens. The study takes place in two phases: model assessment and model sensitivity. In the model assessment phase, analysis is limited to a single control simulation in which the fire sensible heat source is represented as an exponentially decaying vertical profile of turbulent sensible heat flux. In the model sensitivity phase, a series of simulations are conducted to explore the sensitivity of model–observation agreement to (i) the method used to represent the fire sensible heat source in the model and (ii) parameters controlling the magnitude and vertical distribution of the sensible heat source. In both phases, momentum and scalar fields are compared between the model simulations and data obtained from six flux towers located within and adjacent to the burn unit. The multi-dimensional model assessment confirms that the model reproduces the background and fire-perturbed atmosphere as depicted by the tower observations, although the model underestimates the turbulent kinetic energy at the top of the canopy at several towers. The model sensitivity tests reveal that the best agreement with observations occurs when the fire sensible heat source is represented as a turbulent sensible heat flux profile, with surface heat flux magnitude corresponding to the peak 1 min mean observed heat flux averaged across the flux towers, and an e -folding extinction depth corresponding to the average canopy height in the burn unit. The study findings provide useful guidance for improving the representation of the sensible heat released from low-intensity prescribed fires in mesoscale models. [ABSTRACT FROM AUTHOR]

This study investigates the impact of wind speed and critical level height on dry convection above a prescribed heat source. This is done using the Advanced Regional Prediction System (ARPS) model in its two-dimensional form with an imposed 400-K soil potential temperature perturbation. The result of these experiments is the identification of three modes of convective plumes. The first, termed multicell convective plumes, is analogous to multicell convection generated from squall-line cold pools in the moist atmosphere. The second mode, a deep wave mode, consists of disturbances with wavelengths of 7-10 km and results from the multicell plumes perturbing the dynamically unstable shear flow centered at the critical level. The third mode, termed the intense fire plume, has stronger updrafts than the multicell mode and is marked by quasi-stationary movement and substantial low-level inflow and upper-level outflow. The presence of a critical level is shown to be crucial to the development of both the deep wave and intense plume modes. The intense fire plume mode is most consistent with the so-called fire storm, or conflagration phenomenon, in which strong updrafts and low-level indrafts can produce mesocyclones and tornadic fire whirls capable of significant damage. This study marks an important step in understanding the dynamics behind the fire storm phenomenon, as well as other types of convection (multicell and deep wave) that may be generated by a fire.

Abstract: Before using a fluid dynamics physically based wildfire model to study wildfire, validation is necessary and model results need to be systematically and objectively analyzed and compared to real [...]

Mesoscale models are a class of atmospheric numerical model designed to simulate atmospheric phenomena with horizontal scales of about 2-200 km, although they are also applied to microscale phenomena, with horizontal scales less than about 2 km. Mesoscale models are capable of simulating wildland fire impacts on atmospheric flows if combustion by-products (e.g., heat, smoke) are properly represented in the model. One of the primary challenges encountered in applying a mesoscale model to studies of fire-perturbed flows is the representation of the fire sensible heat source in the model. Two primary methods have been implemented previously: turbulent sensible heat flux, either in the form of an exponentially-decaying vertical heat flux profile or surface heat flux; and soil temperature perturbation. In this study, the ARPS-CANOPY model, a version of the Advanced Regional Prediction System (ARPS) model with a canopy submodel, is utilized to simulate the turbulent atmosphere during a low-intensity operational prescribed fire in the New Jersey Pine Barrens. The study takes place in two phases: model assessment and model sensitivity. In the model assessment phase, analysis is limited to a single control simulation in which the fire sensible heat source is represented as an exponentially-decaying vertical profile of turbulent sensible heat flux. In the model sensitivity phase, a series of simulations are conducted to explore the sensitivity of model-observation agreement to (i) the method used to represent the fire sensible heat source in the model and (ii) parameters controlling the magnitude and vertical distribution of the sensible heat source. In both phases, momentum and scalar fields are compared between the model simulations and data obtained from six flux towers located within and adjacent to the burn unit. The multi-dimensional model assessment confirms that the model reproduces the background and fire-perturbed atmosphere as depicted by the tower observations, although the model underestimates the turbulent kinetic energy at the top of the canopy at several towers. The model sensitivity tests reveal that the best agreement with observations occurs when the fire sensible heat source is represented as a turbulent sensible heat flux profile, with surface heat flux magnitude corresponding to the peak 1-min mean observed heat flux averaged across the flux towers, and an e-folding extinction depth corresponding to the average canopy height in the burn unit. The study findings provide useful guidance for improving the representation of the sensible heat released from low-intensity prescribed fires in mesoscale models. [ABSTRACT FROM AUTHOR]

The increase in wildfire risk in the United States in recent decades has been linked to rapid growth of the wildland‐urban interface and to changing climate. While there have been numerous studies on wildfires and climate change, few have separately assessed the impact of climate response to land‐use‐land‐cover change (LULCC) on wildfires. In this study, we analyse two 10‐year regional climate simulations driven by the current (2011) and future (2100) land‐use‐land‐cover patterns to assess modifications by the projected LULCC to the frequency and severity of fire‐prone atmospheric conditions described by two fire weather indices, the Canadian Forest Fire Weather Index and the Hot‐Dry‐Windy Index. The simulation corresponding to future land‐use‐land‐cover pattern yields higher surface temperature and vapour pressure deficit and lower precipitation compared to the simulation with the current pattern in areas where urbanized landscapes replace forests and grasslands, such as along the Piedmont and outside the Chicagoland region, while in areas where croplands replace forests, such as the southeast Coastal Plains, the results are reversed. These changes to local and regional atmospheric conditions lead to longer fire seasons and more extreme fire‐weather conditions in much of the eastern United States, specifically in the Southeast and Ohio River Valley where significant urban expansion is projected by the end of the century. Whereas in Southern California where some highly flammable shrublands will be replaced by urban or crop lands, fire‐prone atmospheric conditions are likely to be less frequent and less extreme in the future. However, much of California moves towards a year‐round fire season under the projected LULCC. The results suggest that by altering atmospheric conditions, LULCC may play an important role in determining fire regime, but the effects are highly heterogeneous and regionalized. [ABSTRACT FROM AUTHOR]

Abstract: An improved understanding of atmospheric perturbations within and above a forest during a wildland fire has relevance to many aspects of wildland fires including fire spread, smoke transport and dispersion, and tree mortality. In this study, the ARPS‐CANOPY model, a version of the Advanced Regional Prediction System (ARPS) model with a canopy parameterization, is utilized in a series of idealized numerical experiments to investigate the influence of vertical canopy structure on the atmospheric response to a stationary sensible heat flux at the ground (“fire heat flux”), broadly consistent in magnitude with the sensible heat flux from a low‐intensity surface fire. Five vertical canopy structures are combined with five fire heat flux magnitudes to yield a matrix of 25 simulations. Analyses of the fire‐heat‐flux‐perturbed u component of the wind, vertical velocity, kinetic energy, and temperature show that the spatial pattern and magnitude of the perturbations are sensitive to vertical canopy structure. Both vertical velocity and kinetic energy exhibit an increasing trend with increasing fire heat flux that is stronger for cases with some amount of overstory vegetation than cases with exclusively understory vegetation. A weaker trend in cases with exclusively understory vegetation indicates a damping of the atmospheric response to the sensible heat from a surface fire when vegetation is most concentrated near the surface. More generally, the results presented in this study suggest that canopy morphology should be considered when applying the results of a fire‐atmosphere interaction study conducted in one type of forest to other forests with different canopy structures. [ABSTRACT FROM AUTHOR]

Much uncertainty exists regarding the possible role that gaps in forest canopies play in modulating fire- atmosphere interactions in otherwise horizontally homogeneous forests. This study examines the influence of gaps in forest canopies on atmospheric perturbations induced by a low-intensity fire using the ARPS-CANOPY model, a version of the Advanced Regional Prediction System (ARPS) model with a canopy parameterization. A series of numerical experiments are conducted with a stationary low-intensity fire, represented in the model as a line of enhanced surface sensible heat flux. Experiments are conducted with and without forest gaps, and with gaps in different positions relative to the fire line. For each of the four cases considered, an additional simulation is performed without the fire to facilitate comparison of the fire-perturbed atmosphere and the background state. Analyses of both mean and instantaneous wind velocity, turbulent kinetic energy, air temperature, and turbulent mixing of heat are presented in order to examine the fire-perturbed atmosphere on multiple timescales. Results of the analyses indicate that the impact of the fire on the atmosphere is greatest in the case with the gap centered on the fire and weakest in the case with the gap upstream of the fire. It is shown that gaps in forest canopies have the potential to play a role in the vertical as well as horizontal transport of heat away from the fire. Results also suggest that, in order to understand how the fire will alter wind and turbulence in a heterogeneous forest, one needs to first understand how the forest heterogeneity itself influences the wind and turbulence fields without the fire. [ABSTRACT FROM AUTHOR]

This study presents a spatial and temporal climatology of major wildfire events, defined as >100 acres burned (>40.47 ha, where 1 ha = 2.47 acre), in the northeast United States from 1999 to 2009 and the meteorological conditions associated with these events. The northeast United States is divided into two regions: region 1 is centered over the higher terrain of the northeast United States and region 2 is primarily over the coastal plain. About 59% of all wildfire events in these two regions occur in April and May, with ~76% in region 1 and ~53% in region 2. There is large interannual variability in wildfire frequency, with some years having 4-5 times more fire events than other years. The synoptic flow patterns associated with northeast United States wildfires are classified using the North American Regional Reanalysis. The most common synoptic pattern for region 1 is a surface high pressure system centered over the northern Appalachians, which occurred in approximately 46% of all events. For region 2, the prehigh anticyclone type extending from southeast Canada and the Great Lakes to the northeast United States is the most common pattern, occurring in about 46% of all events. A trajectory analysis highlights the influence of large-scale subsidence and decreasing relative humidity during the events, with the prehigh pattern showing the strongest subsidence and downslope drying in the lee of the Appalachians. [ABSTRACT FROM AUTHOR]

The performance of a multimodel ensemble over the northeast United States is evaluated before and after applying bias correction and Bayesian model averaging (BMA). The 13-member Stony Brook University (SBU) ensemble at 0000 UTC is combined with the 21-member National Centers for Environmental Pre-diction (NCEP) Short-Range Ensemble Forecast (SREF) system at 2100 UTC. The ensemble is verified using 2-m temperature and 10-m wind speed for the 2007-09 warm seasons, and for subsets of days with high ozone and high fire threat. The impacts of training period, bias-correction method, and BMA are explored for these potentially hazardous weather events using the most recent consecutive (sequential training) and most recent similar days (conditional training). BMA sensitivity to the selection of ensemble members is explored. A running mean difference between forecasts and observations using the last 14 days is better at removing temperature bias than is a cumulative distribution function (CDF) or linear regression approach. Wind speed bias is better removed by adjusting the modeled CDF to the observation. High fire threat and ozone days exhibit a larger cool bias and a greater negative wind speed bias than the warm-season average. Conditional bias correction is generally better at removing temperature and wind speed biases than sequential training. Greater probabilistic skill is found for temperature using both conditional bias correction and BMA com-pared to sequential bias correction with or without BMA. Conditional and sequential BMA results are similar for 10-m wind speed, although BMA typically improves probabilistic skill regardless of training. [ABSTRACT FROM AUTHOR]

Abstract. On the morning of 2 June 2002, an abandoned campfire grew into a wildfire in the DoubleTroublc State Park in cast-central New Jersey, USA. The wildfire burned 526 ha (1300 acres) and forced the closure of the Garden State Parkway for several hours due to dense smoke. In addition to the presence of dead and dry fuels due to a late spring frost prior to the wildfire, the meteorological conditions at the time of the wildfire were conducive to erratic fire behaviour and rapid fire growth. Observations indicate the occurrence of a substantial drop in relative humidity at the surface accompanied by an increase in wind speed in the vicinity of the wildfire during the late morning and early afternoon of2 June. The surface drying and increase in wind speed are hypothcsised to result from the downward transport of dry, high-momentum air from the middle troposphere occurring in conjunction with a deepening mixed layer. This hypothesis is addressed using a high-resolution mesoscalc model simulation to document the structure and evolution of the planetary boundary layer and lower-tropospheric features associated with the arrival of dry, high-momentum air at the surface coincident with the sudden and dramatic growth of the wildfire. [ABSTRACT FROM AUTHOR]

The major source of uncertainty in wildfire behavior prediction is the transient behavior of wildfire due to changes in flow in the fire's environment. The changes in flow are dominated by two factors. The first is the interaction or 'coupling' between the fire and the fire-induced flow. The second is the interaction or 'coupling' between the fire and the ambient flow driven by turbulence due to wind gustiness and eddies in the atmospheric boundary layer (ABL). In the present study, coupled wildfire-atmosphere large-eddy simulations of grassland fires are used to examine the differences in the rate of spread and area burnt by grass fires in two types of ABL, a buoyancy-dominated ABL and a roll-dominated ABL. The simulations show how a buoyancy-dominated ABL affects fire spread, how a roll-dominated ABL affects fire spread, and how fire lines interact with these two different ABL flow types. The simulations also show how important are fire-atmosphere couplings or fire-induced circulations to fire line spread compared with the direct impact of the turbulence in the two different ABLs. The results have implications for operational wildfire behavior prediction. Ultimately, it will be important to use techniques that include an estimate of uncertainty in wildfire behavior forecasts. [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]

This article cites a study that aims to combine fuel maps, based on data from the Forest Inventory and Analysis program of the U.S. Department of Agriculture Forest Service, with real-time atmospheric data for the creation of a more dynamic index of fire danger. The combination of forest fuel maps with real-time atmospheric data may enable the creation of more dynamic and comprehensive assessments of fire danger. Results indicated that fuel loadings and moisture could be estimated for specific points on a meteorological modeling grid network enabling the one- to two-day prediction of fire danger as well as refined understanding of fire danger across forest ecosystems.

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]

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]

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]