Journal articles on the topic 'WRF and SFIRE'
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1
Kochanski, A. K., M. A. Jenkins, J. Mandel, J. D. Beezley, C. B. Clements, and S. Krueger. "Evaluation of WRF-SFIRE performance with field observations from the FireFlux experiment." Geoscientific Model Development 6, no. 4 (August 2, 2013): 1109–26. http://dx.doi.org/10.5194/gmd-6-1109-2013.
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Abstract. This study uses in situ measurements collected during the FireFlux field experiment to evaluate and improve the performance of the coupled atmosphere–fire model WRF-SFIRE. The simulation by WRF-SFIRE of the experimental burn shows that WRF-SFIRE is capable of providing realistic head-fire rate of spread and vertical temperature structure of the fire plume, and fire-induced surface flow and vertical velocities within the plume up to 10 m above ground level. The simulation captured the changes in wind speed and direction before, during, and after fire front passage, along with the arrival times of wind speed, temperature, and updraft maxima, at the two instrumented flux towers used in FireFlux. The model overestimated vertical wind speeds and underestimated horizontal wind speeds measured at tower heights above 10 m. It is hypothesized that the limited model spatial resolution led to overestimates of the fire front depth, heat release rate, and updraft speed. However, on the whole, WRF-SFIRE simulated fire plume behavior that is consistent with FireFlux observations. The study suggests optimal experimental pre-planning, design, and execution strategies for future field campaigns that are intended to evaluate and develop further coupled atmosphere–fire models.
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Mandel, J., J. D. Beezley, and A. K. Kochanski. "Coupled atmosphere-wildland fire modeling with WRF 3.3 and SFIRE 2011." Geoscientific Model Development 4, no. 3 (July 7, 2011): 591–610. http://dx.doi.org/10.5194/gmd-4-591-2011.
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Abstract. We describe the physical model, numerical algorithms, and software structure of a model consisting of the Weather Research and Forecasting (WRF) model, coupled with the fire-spread model (SFIRE) module. In every time step, the fire model inputs the surface wind, which drives the fire, and outputs the heat flux from the fire into the atmosphere, which in turn influences the atmosphere. SFIRE is implemented by the level set method, which allows a submesh representation of the burning region and a flexible implementation of various kinds of ignition. The coupled model is capable of running on a cluster faster than real time even with fine resolution in dekameters. It is available as a part of the Open Wildland Fire Modeling (OpenWFM) environment at http://openwfm.org, which contains also utilities for visualization, diagnostics, and data processing, including an extended version of the WRF Preprocessing System (WPS). The SFIRE code with a subset of the features is distributed with WRF 3.3 as WRF-Fire.
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Mandel, J., S. Amram, J. D. Beezley, G. Kelman, A. K. Kochanski, V. Y. Kondratenko, B. H. Lynn, B. Regev, and M. Vejmelka. "Recent advances and applications of WRF–SFIRE." Natural Hazards and Earth System Sciences 14, no. 10 (October 31, 2014): 2829–45. http://dx.doi.org/10.5194/nhess-14-2829-2014.
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Abstract. Coupled atmosphere–fire models can now generate forecasts in real time, owing to recent advances in computational capabilities. WRF–SFIRE consists of the Weather Research and Forecasting (WRF) model coupled with the fire-spread model SFIRE. This paper presents new developments, which were introduced as a response to the needs of the community interested in operational testing of WRF–SFIRE. These developments include a fuel-moisture model and a fuel-moisture-data-assimilation system based on the Remote Automated Weather Stations (RAWS) observations, allowing for fire simulations across landscapes and time scales of varying fuel-moisture conditions. The paper also describes the implementation of a coupling with the atmospheric chemistry and aerosol schemes in WRF–Chem, which allows for a simulation of smoke dispersion and effects of fires on air quality. There is also a data-assimilation method, which provides the capability of starting the fire simulations from an observed fire perimeter, instead of an ignition point. Finally, an example of operational deployment in Israel, utilizing some of the new visualization and data-management tools, is presented.
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Kochanski, Adam K., Mary Ann Jenkins, Kara Yedinak, Jan Mandel, Jonathan Beezley, and Brian Lamb. "Toward an integrated system for fire, smoke and air quality simulations." International Journal of Wildland Fire 25, no. 5 (2016): 534. http://dx.doi.org/10.1071/wf14074.
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In this study, WRF-Sfire is coupled with WRF-Chem to construct WRFSC, an integrated forecast system for wildfire behaviour and smoke prediction. WRF-Sfire directly predicts wildfire spread, plume and plume-top heights, providing comprehensive meteorology and fire emissions to chemical transport model WRF-Chem, eliminating the need for an external plume-rise model. Evaluation of WRFSC was based on comparisons between available observations of fire perimeter and fire intensity, smoke spread, PM2.5 (particulate matter less than 2.5 μm in diameter), NO and ozone concentrations, and plume-top heights with the results of two WRFSC simulations, a 48-h simulation of the 2007 Witch–Guejito Santa Ana fires and a 96-h WRF-Sfire simulation with passive tracers of the 2012 Barker Canyon fire. The study found overall good agreement between forecast and observed local- and long-range fire spread and smoke transport for the Witch–Guejito fire. However, ozone, PM2.5 and NO concentrations were generally underestimated and peaks mistimed in the simulations. This study found overall good agreement between simulated and observed plume-top heights, with slight underestimation by the simulations. Two promising results were the agreement between plume-top heights for the Barker Canyon fire and faster than real-time execution, making WRFSC a possible operational tool.
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Kochanski, A. K., M. A. Jenkins, J. Mandel, J. D. Beezley, C. B. Clements, and S. Krueger. "Evaluation of WRF-SFIRE performance with field observations from the FireFlux experiment." Geoscientific Model Development Discussions 6, no. 1 (January 18, 2013): 121–69. http://dx.doi.org/10.5194/gmdd-6-121-2013.
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Abstract. This study uses in-situ measurements collected during the FireFlux field experiment to evaluate and improve the performance of coupled atmosphere-fire model WRF-SFIRE. The simulation of the experimental burn shows that WRF-SFIRE is capable of providing realistic head fire rate-of-spread and the vertical temperature structure of the fire plume, and, up to 10 m above ground level, fire-induced surface flow and vertical velocities within the plume. The model captured the changes in wind speed and direction before, during, and after fire front passage, along with arrival times of wind speed, temperature, and updraft maximae, at the two instrumented flux towers used in FireFlux. The model overestimated vertical velocities and underestimated horizontal wind speeds measured at tower heights above the 10 m, and it is hypothesized that the limited model resolution over estimated the fire front depth, leading to too high a heat release and, subsequently, too strong an updraft. However, on the whole, WRF-SFIRE fire plume behavior is consistent with the interpretation of FireFlux observations. The study suggests optimal experimental pre-planning, design, and execution of future field campaigns that are needed for further coupled atmosphere-fire model development and evaluation.
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Mallia, Derek V., Adam K. Kochanski, Shawn P. Urbanski, Jan Mandel, Angel Farguell, and Steven K. Krueger. "Incorporating a Canopy Parameterization within a Coupled Fire-Atmosphere Model to Improve a Smoke Simulation for a Prescribed Burn." Atmosphere 11, no. 8 (August 7, 2020): 832. http://dx.doi.org/10.3390/atmos11080832.
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Forecasting fire growth, plume rise and smoke impacts on air quality remains a challenging task. Wildland fires dynamically interact with the atmosphere, which can impact fire behavior, plume rises, and smoke dispersion. For understory fires, the fire propagation is driven by winds attenuated by the forest canopy. However, most numerical weather prediction models providing meteorological forcing for fire models are unable to resolve canopy winds. In this study, an improved canopy model parameterization was implemented within a coupled fire-atmosphere model (WRF-SFIRE) to simulate a prescribed burn within a forested plot. Simulations with and without a canopy wind model were generated to determine the sensitivity of fire growth, plume rise, and smoke dispersion to canopy effects on near-surface wind flow. Results presented here found strong linkages between the simulated fire rate of spread, heat release and smoke plume evolution. The standard WRF-SFIRE configuration, which uses a logarithmic interpolation to estimate sub-canopy winds, overestimated wind speeds (by a factor 2), fire growth rates and plume rise heights. WRF-SFIRE simulations that implemented a canopy model based on a non-dimensional wind profile, saw significant improvements in sub-canopy winds, fire growth rates and smoke dispersion when evaluated with observations.
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Mandel, J., S. Amram, J. D. Beezley, G. Kelman, A. K. Kochanski, V. Y. Kondratenko, B. H. Lynn, B. Regev, and M. Vejmelka. "New features in WRF-SFIRE and the wildfire forecasting and danger system in Israel." Natural Hazards and Earth System Sciences Discussions 2, no. 2 (February 24, 2014): 1759–97. http://dx.doi.org/10.5194/nhessd-2-1759-2014.
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Abstract. Recent advances in computational capabilities of computer clusters made operational deployments of coupled atmosphere-fire models feasible, as the weather and fire spread forecast can be nowadays generated faster than real time. This paper presents new developments in the coupled WRF-SFIRE model and related software in past two years, being a response to the needs of the community interested in operational testing of WRF-SFIRE. We describe a new concept of the fireline intensity intended to better inform about the local fire front properties and fire danger. We present a fuel moisture model and a fuel moisture data assimilation system based on the Remote Automated Weather Stations (RAWS) observations, allowing for fire simulations across landscapes and time scales of varying fuel moisture conditions. The paper also describes the implementation of a coupling with the atmospheric chemistry and aerosol schemes in WRF-Chem allowing for simulation of smoke dispersion and effects of fires on air quality, as well as a data assimilation method allowing for starting the fire simulations from an observed fire perimeters instead of ignition points. Finally, an example of an operational deployment and new visualization and the data management tools are presented.
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Kochanski, Adam, Aimé Fournier, and Jan Mandel. "Experimental Design of a Prescribed Burn Instrumentation." Atmosphere 9, no. 8 (July 29, 2018): 296. http://dx.doi.org/10.3390/atmos9080296.
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Observational data collected during experiments, such as the planned Fire and Smoke Model Evaluation Experiment (FASMEE), are critical for evaluating and transitioning coupled fire-atmosphere models like WRF-SFIRE and WRF-SFIRE-CHEM into operational use. Historical meteorological data, representing typical weather conditions for the anticipated burn locations and times, have been processed to initialize and run a set of simulations representing the planned experimental burns. Based on an analysis of these numerical simulations, this paper provides recommendations on the experimental setup such as size and duration of the burns, and optimal sensor placement. New techniques are developed to initialize coupled fire-atmosphere simulations with weather conditions typical of the planned burn locations and times. The variation and sensitivity analysis of the simulation design to model parameters performed by repeated Latin Hypercube Sampling is used to assess the locations of the sensors. The simulations provide the locations for the measurements that maximize the expected variation of the sensor outputs with varying the model parameters.
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Peace, M., L. McCaw, J. Kepert, G. Mills, and T. Mattner. "WRF and SFIRE simulations of the Layman fuel reduction burn." Australian Meteorological and Oceanographic Journal 65, no. 3/4 (December 2015): 302–17. http://dx.doi.org/10.22499/2.6503.002.
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Peace, Mika, Trent Mattner, Graham Mills, Jeffrey Kepert, and Lachlan McCaw. "Coupled Fire–Atmosphere Simulations of the Rocky River Fire Using WRF-SFIRE." Journal of Applied Meteorology and Climatology 55, no. 5 (May 2016): 1151–68. http://dx.doi.org/10.1175/jamc-d-15-0157.1.
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AbstractThe coupled atmosphere–fire spread model “WRF-SFIRE” has been used to simulate a fire where extreme fire behavior was observed. Tall flames and a dense convective smoke column were features of the fire as it burned rapidly up the Rocky River gully on Kangaroo Island, South Australia. WRF-SFIRE simulations of the event show a number of interesting dynamical processes resulting from fire–atmosphere feedback, including the following: fire spread was sensitive to small changes in mean wind direction; fire perimeter was affected by wind convergence resulting from interactions between the fire, atmosphere, and local topography; and the fire plume mixed high-momentum air from above a strong subsidence inversion. At 1-min intervals, output from the simulations showed fire spread exhibiting fast and slow pulses. These pulses occurred coincident with the passage of mesoscale convective (Rayleigh–Bénard) cells in the planetary boundary layer. Simulations show that feedback between the fire and atmosphere may have contributed to the observed extreme fire behavior. The findings raise questions as to the appropriate information to include in meteorological forecasts for fires as well as future use of coupled and uncoupled fire simulation models in both operational and research settings.
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Herr, Vincent, Adam K. Kochanski, Van V. Miller, Rich McCrea, Dan O'Brien, and Jan Mandel. "A method for estimating the socioeconomic impact of Earth observations in wildland fire suppression decisions." International Journal of Wildland Fire 29, no. 3 (2020): 282. http://dx.doi.org/10.1071/wf18237.
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A method for estimating the socioeconomic impact of Earth observations is proposed and deployed. The core of the method is the analysis of outcomes of hypothetical fire suppression scenarios generated using a coupled atmosphere–fire behaviour model, based on decisions made by an experienced wildfire incident management team with and without the benefits of MODIS (Moderate Resolution Imaging Spectroradiometer) satellite observations and the WRF-SFIRE wildfire behaviour simulation system. The scenarios were based on New Mexico’s 2011 Las Conchas fire. For each scenario, fire break line location decisions served as inputs to the model, generating fire progression outcomes. Fire model output was integrated with a property database containing thousands of coordinates and property values and other asset values to estimate the total losses associated with each scenario. An attempt to estimate the socioeconomic impact of satellite and modelling data used during the decision-making process was made. We analysed the impact of Earth observations and include considerations for estimating other socioeconomic impacts.
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Moisseeva, Nadya, and Roland Stull. "Wildfire smoke-plume rise: a simple energy balance parameterization." Atmospheric Chemistry and Physics 21, no. 3 (February 2, 2021): 1407–25. http://dx.doi.org/10.5194/acp-21-1407-2021.
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Abstract. The buoyant rise and the resultant vertical distribution of wildfire smoke in the atmosphere have a strong influence on downwind pollutant concentrations at the surface. The amount of smoke injected vs. height is a key input into chemical transport models and smoke modelling frameworks. Due to scarcity of model evaluation data as well as the inherent complexity of wildfire plume dynamics, smoke injection height predictions have large uncertainties. In this work we use the coupled fire–atmosphere model WRF-SFIRE configured in large-eddy simulation (LES) mode to develop a synthetic plume dataset. Using this numerical data, we demonstrate that crosswind integrated smoke injection height for a fire of arbitrary shape and intensity can be modelled with a simple energy balance. We introduce two forms of updraft velocity scales that exhibit a linear dimensionless relationship with the plume vertical penetration distance through daytime convective boundary layers. Lastly, we use LES and prescribed burn data to constrain and evaluate the model. Our results suggest that the proposed simple parameterization of mean plume rise as a function of vertical velocity scale offers reasonable accuracy (30 m errors) at little computational cost.
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Lagouvardos, K., V. Kotroni, T. M. Giannaros, and S. Dafis. "Meteorological Conditions Conducive to the Rapid Spread of the Deadly Wildfire in Eastern Attica, Greece." Bulletin of the American Meteorological Society 100, no. 11 (November 2019): 2137–45. http://dx.doi.org/10.1175/bams-d-18-0231.1.
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AbstractOn 23 July 2018, Attica, Greece, was impacted by a major wildfire that took place in a wildland–urban interface area and exhibited extreme fire behavior, characterized by a very high rate of spread. One-hundred civilian fatalities were registered, establishing this wildfire as the second-deadliest weather-related natural disaster in Greece, following the heat wave of July 1987. On the day of the deadly wildfire, a very strong westerly flow was blowing for more than 10 h over Attica. Wind gusts up to 30–34 m s−1 occurred over the mountainous areas of Attica, with 20–25 m s−1 in the city of Athens and surrounding suburban areas. This strong westerly flow interacted with the local topography and acted as downslope flow over the eastern part of Attica, with temperatures rising up to 39°C and relative humidity dropping to 19% prior to the onset of the wildfire. These weather elements are widely acknowledged as the major contributing factors to extreme fire behavior. WRF-SFIRE correctly predicted the spatiotemporal distribution of the fire spread and demonstrated its utility for fire spread warning purposes.
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Vejmelka, Martin, Adam K. Kochanski, and Jan Mandel. "Data assimilation of dead fuel moisture observations from remote automated weather stations." International Journal of Wildland Fire 25, no. 5 (2016): 558. http://dx.doi.org/10.1071/wf14085.
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Fuel moisture has a major influence on the behaviour of wildland fires and is an important underlying factor in fire risk assessment. We propose a method to assimilate dead fuel moisture content (FMC) observations from remote automated weather stations (RAWS) into a time lag fuel moisture model. RAWS are spatially sparse and a mechanism is needed to estimate fuel moisture content at locations potentially distant from observational stations. This is arranged using a trend surface model (TSM), which allows us to account for the effects of topography and atmospheric state on the spatial variability of FMC. At each location of interest, the TSM provides a pseudo-observation, which is assimilated via Kalman filtering. The method is tested with the time lag fuel moisture model in the coupled weather-fire code WRF–SFIRE on 10-h FMC observations from Colorado RAWS in 2013. Using leave-one-out testing we show that the TSM compares favourably with inverse squared distance interpolation as used in the Wildland Fire Assessment System. Finally, we demonstrate that the data assimilation method is able to improve on FMC estimates in unobserved fuel classes.
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Trucchia, Andrea, Vera Egorova, Anton Butenko, Inderpreet Kaur, and Gianni Pagnini. "RandomFront 2.3: a physical parameterisation of fire spotting for operational fire spread models – implementation in WRF-SFIRE and response analysis with LSFire+." Geoscientific Model Development 12, no. 1 (January 3, 2019): 69–87. http://dx.doi.org/10.5194/gmd-12-69-2019.
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Abstract. Fire spotting is often responsible for dangerous flare-ups in wildfires and causes secondary ignitions isolated from the primary fire zone, which lead to perilous situations. The main aim of the present research is to provide a versatile probabilistic model for fire spotting that is suitable for implementation as a post-processing scheme at each time step in any of the existing operational large-scale wildfire propagation models, without calling for any major changes in the original framework. In particular, a complete physical parameterisation of fire spotting is presented and the corresponding updated model RandomFront 2.3 is implemented in a coupled fire–atmosphere model: WRF-SFIRE. A test case is simulated and discussed. Moreover, the results from different simulations with a simple model based on the level set method, namely LSFire+, highlight the response of the parameterisation to varying fire intensities, wind conditions and different firebrand radii. The contribution of the firebrands to increasing the fire perimeter varies according to different concurrent conditions, and the simulations show results in agreement with the physical processes. Among the many rigorous approaches available in the literature to model firebrand transport and distribution, the approach presented here proves to be simple yet versatile for application to operational large-scale fire spread models.
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Peace, Mika, Trent Mattner, Graham Mills, Jeffrey Kepert, and Lachlan McCaw. "Fire-Modified Meteorology in a Coupled Fire–Atmosphere Model." Journal of Applied Meteorology and Climatology 54, no. 3 (March 2015): 704–20. http://dx.doi.org/10.1175/jamc-d-14-0063.1.
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AbstractThe coupled fire–atmosphere model consisting of the Weather and Forecasting (WRF) Model coupled with the fire-spread model (SFIRE) module has been used to simulate a bushfire at D’Estrees Bay on Kangaroo Island, South Australia, in December 2007. Initial conditions for the simulations were provided by two global analyses: the GFS operational analysis and ERA-Interim. For each NWP initialization, the simulations were run with and without feedback from the fire to the atmospheric model. The focus of this study was examining how the energy fluxes from the simulated fire modified the local meteorological environment. With feedback enabled, the propagation speed of the sea-breeze frontal line was faster and vertical motion in the frontal zone was enhanced. For one of the initial conditions with feedback on, a vortex developed adjacent to the head fire and remained present for over 5 h of simulation time. The vortex was not present without fire–atmosphere feedback. The results show that the energy fluxes released by a fire can effect significant changes on the surrounding mesoscale atmosphere. This has implications for the appropriate use of weather parameters extracted from NWP and used in prediction for fire operations. These meteorological modifications also have implications for anticipating likely fire behavior.
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Kochanski, Adam K., Farren Herron-Thorpe, Derek V. Mallia, Jan Mandel, and Joseph K. Vaughan. "Integration of a Coupled Fire-Atmosphere Model Into a Regional Air Quality Forecasting System for Wildfire Events." Frontiers in Forests and Global Change 4 (November 10, 2021). http://dx.doi.org/10.3389/ffgc.2021.728726.
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The objective of this study was to assess feasibility of integrating a coupled fire-atmosphere model within an air-quality forecast system to create a multiscale air-quality modeling framework designed to simulate wildfire smoke. For this study, a coupled fire-atmosphere model, WRF-SFIRE, was integrated, one-way, with the AIRPACT air-quality modeling system. WRF-SFIRE resolved local meteorology, fire growth, the fire plume rise, and smoke dispersion, and provided AIRPACT with fire inputs. The WRF-SFIRE-forecasted fire area and the explicitly resolved vertical smoke distribution replaced the parameterized BlueSky fire inputs used by AIRPACT. The WRF-SFIRE/AIRPACT integrated framework was successfully tested for two separate wildfire events (2015 Cougar Creek and 2016 Pioneer fires). The execution time for the WRF-SFIRE simulations was <3 h for a 48 h-long forecast, suggesting that integrating coupled fire-atmosphere simulations within the daily AIRPACT cycle is feasible. While the WRF-SFIRE forecasts realistically captured fire growth 2 days in advance, the largest improvements in the air quality simulations were associated with the wildfire plume rise. WRF-SFIRE-estimated plume tops were within 300-m of satellite-estimated plume top heights for both case studies analyzed in this study. Air quality simulations produced by AIRPACT with and without WRF-SFIRE inputs were evaluated with nearby PM2.5 measurement sites to assess the performance of our multiscale smoke modeling framework. The largest improvements when coupling WRF-SFIRE with AIRPACT were observed for the Cougar Creek Fire where model errors were reduced by ∼50%. For the second case (Pioneer fire), the most notable change with WRF-SFIRE coupling was that the probability of detection increased from 16 to 52%.
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Kale, Manish P., Asima Mishra, Satish Pardeshi, Suddhasheel Ghosh, D. S. Pai, and Parth Sarathi Roy. "Forecasting wildfires in major forest types of India." Frontiers in Forests and Global Change 5 (October 25, 2022). http://dx.doi.org/10.3389/ffgc.2022.882685.
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Severity of wildfires witnessed in different parts of the world in the recent times has posed a significant challenge to fire control authorities. Even when the different fire early warning systems have been developed to provide the quickest warnings about the possible wildfire location, severity, and danger, often it is difficult to deploy the resources quickly to contain the wildfire at a short notice. Response time is further delayed when the terrain is complex. Early warning systems based on physics-based models, such as WRF-FIRE/SFIRE, are computationally intensive and require high performance computing resources and significant data related to fuel properties and climate to generate forecasts at short intervals of time (i.e., hourly basis). It is therefore that when the objective is to develop monthly and yearly forecasts, time series models seem to be useful as they require lesser computation power and limited data (as compared to physics-based models). Long duration forecasts are useful in preparing an efficient fire management plan for optimal deployment of resources in the event of forest fire. The present research is aimed at forecasting the number of fires in different forest types of India on a monthly basis using “Autoregressive Integrated Moving Average” time series models (both univariate and with regressors) at 25 km × 25 km spatial resolution (grid) and developing the fire susceptibility maps using Geographical Information System. The performance of models was validated based on the autocorrelation function (ACF), partial ACF, cumulative periodogram, and Portmanteau (L-Jung Box) test. Both the univariate- and regressor-based models performed equally well; however, the univariate model was preferred due to parsimony. The R software package was used to run and test the model. The forecasted active fire counts were tested against the original 3 years monthly forecasts from 2015 to 2017. The variation in coefficient of determination from 0.94 (for year 1 forecast) to 0.64 (when all the 3-year forecasts were considered together) was observed for tropical dry deciduous forests. These values varied from 0.98 to 0.89 for tropical moist deciduous forest and from 0.97 to 0.88 for the tropical evergreen forests. The forecasted active fire counts were used to estimate the future forest fire frequency ratio, which has been used as an indicator of forest fire susceptibility.