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A fire weather index (FWI) is developed using wildfire occurrence data and Automated Surface Observing System weather observations within a subregion of the northeastern United States (NEUS) from 1999 to 2008. Average values of several meteorological variables, including near-surface temperature, relative humidity, dewpoint, wind speed, and cumulative daily precipitation, are compared on observed wildfire days with their climatological average ('climatology') using a bootstrap resampling approach. Average daily minimum relative humidity is significantly lower than climatology on wildfire occurrence days, and average daily maximum temperature and average daily maximum wind speed are slightly higher on wildfire occurrence days. Using the potentially important weather variables (relative humidity, temperature, and wind speed) as inputs, different formulations of a binomial logistic regression model are tested to assess the potential of these atmospheric variables for diagnosing the probability of wildfire occurrence. The FWI is defined using probabilistic output from the preferred binomial logistic regression configuration. Relative humidity and temperature are the only significant predictors in the binomial logistic regression. The binomial logistic regression model is reliable and has more probabilistic skill than climatology using an independent verification dataset. Using the binomial logistic regression output probabilities, an FWI is developed ranging from 0 (minimum potential) to 3 (high potential) and is verified independently for two separate subdomains within the NEUS. The climatology of the FWI reproduces observed fire occurrence probabilities between 1999 and 2008 over a subdomain of the NEUS. [ABSTRACT FROM AUTHOR]

This study examines the sensitivity of mean and turbulent flow in the planetary boundary layer and roughness sublayer to a low-intensity fire and evaluates whether the sensitivity is dependent on canopy and background atmospheric properties. The ARPS-CANOPY model, a modified version of the Advanced Regional Prediction System (ARPS) model with a canopy parameterization, is utilized for this purpose. A series of numerical experiments are conducted to evaluate whether the ability of the fire to alter downstream wind, temperature, turbulent kinetic energy (TKE), and vertical heat flux differs between forested and open areas, sparse and dense forests, weak and strong background flow, and neutral and convective background stability. Analysis of all experiments shows that, in general, mean and turbulent flow both prior to and during a low-intensity fire is damped in the presence of a canopy. Greater sensitivity to the fire is found in cases with strong ambient wind speed than in cases with quiescent or weak wind speed. Furthermore, sensitivity of downstream atmospheric conditions to the fire is shown to be strongest with a neutrally stratified background. An analysis of the TKE budget reveals that both buoyancy and wind shear contribute to TKE production during the period of time in which the fire conditions are applied to the model. On the basis of the results of the ARPS simulations, caution is advised when applying ARPS-simulation results to predictions of smoke transport and dispersion: smoke-model users should consider whether canopy impacts on the atmosphere are accounted for and whether neutral stratification is assumed. [ABSTRACT FROM AUTHOR]

Smoke prediction products are one of the tools used by land management personnel for decision making regarding prescribed fires. This study documents the application to a prescribed fire of a smoke prediction system that employs ARPS-CANOPY, a modified version of the Advanced Regional Prediction System (ARPS) model containing a canopy submodel, as the meteorological driver. In this paper, the performance of ARPS-CANOPY in simulating meteorological fields in the vicinity of a low-intensity fire is assessed using flux-tower data collected prior to and during a low-intensity prescribed fire in the New Jersey Pine Barrens in March 2011. A three-dimensional high-resolution plant area density dataset is utilized to define the characteristics of the canopy, and the fire is represented in ARPS-CANOPY as a heat flux to the atmosphere. The standard ARPS model is compared with reanalysis and upper-air data to establish that the model can simulate the observed synoptic-mesoscale and planetary boundary layer features that are salient to this study. ARPS-CANOPY profiles of mean turbulent kinetic energy, wind speed/direction, and temperature exhibit patterns that appear in the flux-tower observations during both the preburn phase of the experiment and the period of time the flux tower experienced perturbed atmospheric conditions due to the impinging fire. Last, the character and source of turbulence in and around the fire line are examined. These results are encouraging for smoke prediction efforts since transport of smoke from low-intensity fires is highly sensitive to the near-surface meteorological conditions and, in particular, turbulent flows. [ABSTRACT FROM AUTHOR]

The Haines index (HI) is a fire-weather index that is widely used as an indicator of the potential for dry, low-static-stability air in the lower atmosphere to contribute to erratic fire behavior or large fire growth. This study examines the interannual variability of HI over North America and its relationship to indicators of large-scale circulation anomalies. The results show that the first three HI empirical orthogonal function modes are related respectively to El Niño-Southern Oscillation (ENSO), the Arctic Oscillation (AO), and the interdecadal sea surface temperature variation over the tropical Pacific Ocean. During the negative ENSO phase, an anomalous ridge (trough) is evident over the western (eastern) United States, with warm/dry weather and more days with high HI values in the western and southeastern United States. During the negative phase of the AO, an anomalous trough is found over the western United States, with wet/cool weather and fewer days with high HI, while an anomalous ridge occurs over the southern United States-northern Mexico, with an increase in the number of days with high HI. After the early 1990s, the subtropical high over the eastern Pacific Ocean and the Bermuda high were strengthened by a wave train that was excited over the tropical western Pacific Ocean and resulted in warm/dry conditions over the southwestern United States and western Mexico and wet weather in the southeastern United States. The above conditions are reversed during the positive phase of ENSO and AO and before the early 1990s. [ABSTRACT FROM AUTHOR]