Search Results (49)

The 2020 wildfire season in the Western U.S. was historic in its intensity and impact on the land and atmosphere. This study aims to characterize satellite retrievals of carbon monoxide (CO), a tracer of combustion and signature of those fires, from two key satellite instruments: the Cross-track Infrared Sounder (CrIS) and the Tropospheric Monitoring Instrument (TROPOMI). We evaluate them during this event and assess their synergies. These two retrievals are matched temporally, as the host satellites are in tandem orbit and spatially by aggregating TROPOMI to the CrIS resolution. Both instruments show that the Western U.S. displayed significantly higher daily average CO columns compared to the Central and Eastern U.S. during the wildfires. TROPOMI showed up to a factor of two larger daily averages than CrIS during the most intense fire period, likely due to differences in the vertical sensitivity of the two instruments and representative of near-surface CO abundance near the fires. On the other hand, there was excellent agreement between the instruments in downwind free tropospheric plumes (scatter plot slopes of 0.96–0.99), consistent with their vertical sensitivities and indicative of mostly lofted smoke. Temporally, TROPOMI CO column peaks were delayed relative to the Fire Radiative Power (FRP), and CrIS peaks were delayed with respect to TROPOMI, particularly during the intense initial weeks of September, suggesting boundary layer buildup and ventilation. Satellite retrievals were evaluated using ground-based CO column estimates from the Network for the Detection of Atmospheric Composition Change (NDACC) and the Total Carbon Column Observing Network (TCCON), showing Normalized Mean Errors (NMEs) for CrIS and TROPOMI below 32% and 24%, respectively, when compared to all stations studied. While Normalized Mean Bias (NMB) was typically low (absolute value below 15%), there were larger negative biases at Pasadena, likely associated with sharp spatial gradients due to topography and proximity to a large city, which is consistent with previous research. In situ CO profiles from AirCore showed an elevated smoke plume for 15 September 2020, highlighted consistency between TROPOMI and CrIS CO columns for lofted plumes. This study demonstrates that both CrIS and TROPOMI provide complementary information on CO distribution. CrIS’s sensitivity in the middle and lower free troposphere, coupled with TROPOMI’s effectiveness at capturing total columns, offers a more comprehensive view of CO distribution during the wildfires than either retrieval alone. By combining data from both satellites as a ratio, more detailed information about the vertical location of the plumes can potentially be extracted. This approach can enhance air quality models, improve vertical estimation accuracy, and establish a new method for assessing lower tropospheric CO concentrations during significant wildfire events. Full article

This study investigates the physical interactions and between forest fires and the atmosphere, which often lead to conditions favourable to instability and the formation of pyrocumulus (PyCu). Using the coupled atmosphere–fire spread modelling framework, WRF-SFIRE, the Portuguese October 2017 Quiaios wildfire, in association with tropical cyclone Ophelia, was simulated. Fire spread was imposed via burnt area data, and the fire’s influence on the vertical and surface atmosphere was analysed. Simulated local atmospheric conditions were influenced by warm and dry air advection near the surface, and moist air in mid to high levels, displaying an inverted “V” profile in thermodynamic diagrams. These conditions created a near-neutrally unstable atmospheric layer in the first 3000 m, associated with a low-level jet above 1000 m. Results showed that vertical wind shear tilted the plume, resulting in an intermittent, high-based, shallow pyroconvection, in a zero convective available potential energy environment (CAPE). Lifted parcels from the fire lost their buoyancy shortly after condensation, and the presence of PyCu was governed by the energy output from the fire and its updrafts. Clouds formed above the lifted condensation level (LCL) as moisture fluxes from the surface and released from combustion were lifted along the fire plume. Clouds were primarily composed of liquid water (1 g/kg) with smaller traces of ice, graupel, and snow (up to 0.15 g/kg). The representation of pyroconvective dynamics via coupled models is the cornerstone of understanding the phenomena and field applications as the computation capability increases and provides firefighters with real time extreme fire conditions or predicting ahead of time. Full article

Accurate wildfire spread modeling critically depends on the representation of wind dynamics, which vary with terrain, land cover characteristics, and height above ground. Many fire spread models are often coupled with coarse atmospheric grids that cannot explicitly resolve the vertical variation of wind near flame heights. Rothermel’s fire spread model, a widely used parameterization, relies on midflame wind speed to calculate the fire rate of spread. In coupled fire atmosphere models such as the Community Fire Behavior Model (CFBM), users are required to specify the midflame height before running a fire spread simulation. This study evaluates the use of logarithmic interpolation wind adjustment factors (WAF) for improving midflame wind speed estimates, which are critical for the Rothermel model. We compare the fixed wind height approach that is currently used in CFBM with WAF-derived winds for unsheltered and sheltered surface fire spread. For the first time in this context, these simulations are validated against satellite and ground-based observations of fire perimeters. The results show that WAF implementation improves fire perimeter predictions for both grass and canopy fires while reducing the overestimation of fire spread. Moreover, this approach solely depends on the fuel bed depth and estimation of canopy density, enhancing operational efficiency by eliminating the need for users to specify a wind height for simulations. Full article

The spread of fires on the facades of high-rise buildings is highly influenced by atmospheric wind conditions, particularly in strong wind environments. A strong wind environment refers to the situation where the wind speed reaches level 6 or above, or the wind speed is between 10.8 m/s and 13.8 m/s. We conducted an in-depth study of the characteristics of flame spread on the facades of high-rise buildings under strong wind conditions. A nested coupling method based on WRF (Weather Research and Forecasting) and CFD (computational fluid dynamics) software (Ansys Fluent 2021) was used. The mesoscale meteorological simulation software WRF was utilized to obtain regional airflow variation data within a radius of 2 km around the high-rise building. Subsequently, these data were coupled with the CFD software (Ansys Fluent 2021) to simulate and obtain realistic wind field data within a 400 m range around the building. Finally, these realistic wind field data were used for FDS (Fire Dynamics Simulator) fire simulations and model experiments to accurately replicate building fire scenarios under strong wind conditions. The results indicate that using grid nesting for boundary condition division would help to improve the accuracy of fire spread characteristics on the facades of high-rise buildings under strong wind conditions. For a high-rise building, both headwinds and tailwinds promote vertical and horizontal flame spread, with a more significant impact on vertical flame spread speed. Side winds enhance horizontal flame spread but inhibit vertical flame spread. These findings provide a reference for the effective design of fire protection systems for the facades of high-rise buildings. Full article

Ensuring firefighter safety during oil tank fires is paramount, given the substantial risks posed by thermal radiation. This study employs both the Fire Dynamics Simulator (FDS) and Areal Locations of Hazardous Atmospheres (ALOHA) software to simulate a severe oil tank fire scenario at the Zhushan Branch Power Plant, where two heavy oil tanks and multiple light oil tanks are located. The simulation framework divides the combustion scenario into 22.4 million grids with a grid size of 0.5 m, allowing a fine-resolution assessment of thermal radiation. Assuming a worst-case scenario involving n-Heptane combustion, the FDS simulation calculates essential parameters, including temperature, velocity, and soot distribution fields, and suggests a minimum safe firefighting distance of 22 m (equivalent to one tank diameter, 1D) for those equipped with personal protective equipment when exposed to a 5 kW/m² heat flux. Meanwhile, ALOHA modeling extends the safety assessment, recommending a downwind safety distance of 62 m (approximately 2D) to establish a preliminary exclusion zone, crucial in early emergency response when data may be incomplete. Additionally, a grid sensitivity analysis was conducted to validate the accuracy of the numerical results. This study underscores the importance of coupling FDS and ALOHA outputs to develop a balanced, adaptive approach to firefighter safety, optimizing response protocols for high-risk environments. The results provide essential guidance for establishing safety zones, advancing standards within fire protection and emergency response, and supporting strategy development for large-scale oil and petrochemical storage facilities. Full article

This study provides insights into large fires in the Pantanal by analyzing the atmospheric conditions that influenced the rapid fire evolution between 13 and 14 November 2023, when fire fronts spread rapidly, leading to critical situations for firefighters. The observation-based analysis helped us to identify some characteristics of the fire’s evolution and the meteorological conditions in the region. Furthermore, two simulations were run with the Meso-NH model, which was configured with horizontal resolutions of 2.5 km and 5 km. The fire behavior, characterized by satellite observations, revealed periods with a sudden increase in active fire numbers. High temperatures and low relative humidity in the region characterized the fire weather conditions. The simulations confirmed the critical fire condition, showing the benefits of increasing the resolution of numerical models for the Pantanal region. The convection-resolving simulation at 2.5 km showed the repeated development of gust fronts in the late afternoon and early evening. This study highlights this dynamic that, coupled with intense surface wind gusts, was crucial for the intensification of the fire spread and unexpected behavior. This study is a first step toward better understanding fire dynamics in the Pantanal through atmospheric modeling, and it can support strategies for firefighting in the region. Full article

This study aimed to assess fire–atmosphere interactions using the fully coupled Meso-NH–ForeFire system. We focused on the Pedrógão Grande wildfire (28,914 ha), which occurred in June 2017 and was one of the deadliest and most damaging fires in Portugal’s history. Two simulations (control and fully coupled fire–atmosphere) were performed for three two-way nested domains configured with horizontal resolutions of 2 km, 0.4 km, and 0.08 km, respectively, in the atmospheric model Meso-NH. Fire propagation was modeled within the innermost domain with ForeFire, which solves the fire front with a 20 m resolution, producing the heat and vapor fluxes which are then injected into the atmospheric model. A simplified homogeneous fuel distribution was used in this case study. The fully coupled experiment helped us to characterize the smoke plume structure and identify two different regimes: (1) a wind-driven regime, with the smoke plume transported horizontally southward and in the lower troposphere, and (2) a plume-dominated regime, in which the simulated smoke plume extended vertically up to upper levels, favoring the formation of a pyro-cloud. The simulations were compared, and the results suggest that the change in the fire regime was caused by an outflow that affected the main fire front. Furthermore, the fully coupled simulation allowed us to explore the change in meteorology caused by an extreme fire, namely through the development of a pyro-cloud that also induced outflows that reached the surface. We show that the Meso-NH–ForeFire system may strongly contribute to an improved understanding of extreme wildfires events and associated weather phenomena. Full article

Fireproof sealing technology is widely used in industrial, commercial, and other public buildings, so the performance of fireproof sealing materials in high temperatures or fire environments must be taken into account as an important factor. Fireproof sealant is considered to be a highly effective adhesive for sealing and fireproofing purposes. To explore its thermal decomposition mechanism and estimate its pyrolysis behaviors, a series of thermogravimetric experiments from 10 K/min to 60 K/min coupled with Fourier transform infrared spectroscopy analysis technology were performed. The results indicated that the thermal decomposition of the fireproof sealant could be divided into three reactions: the degradation of ammonium polyphosphate, melamine, and acrylic acid. In addition, the pyrolysis behavior of the fireproof sealant was compared under two kinds of atmosphere (nitrogen and air). Furthermore, the initial kinetic parameters in the nitrogen atmosphere were calculated based on model-free methods including the Friedman, KAS, and Starink methods. The average activation energy of three reactions obtained by the three methods was 108.32 kJ/mol, 200.46 kJ/mol, and 177.10 kJ/mol, respectively, while these obtained parameters were hard to regenerate, the thermogravimetric curves were accurately based on the established pyrolysis reaction scheme, with the existence of clear deviations. Therefore, a global heuristic optimization algorithm, Shuffled Complex Evolution (SCE), was selected to optimize 14 parameters (including activation energies and the pre-exponential factors) and the optimized pyrolysis results agreed well with the experimental data, even at the extra heating rate, with the correlation coefficient for the mass loss and mass loss rate being reaching up to 0.9943 and 0.9019, respectively. The study indicated that the SCE algorithm showed an appropriate potential to estimate the pyrolysis behavior of an unknown thermogravimetric experiment group. Full article

Climate change is already significantly affecting the frequency of wildfires in most regions of the world, and the risk of wildfires is expected to amplify further with global warming. Accordingly, there is growing concern about the mechanisms and impacts of extreme fires. In this study, a coupling of the Weather Research and Forecasting model and the Rothermel Fire model (WRF-Fire) is employed to reproduce the spread of fire within the national boundary of inner Mongolia from 21 to 27 May 2009. Simulations were run with or without feedback from fire-to-atmosphere models, and the study focused on how the energy flux of simulated fires changes the local meteorological environment. The coupled simulation could reproduce the burned area well, and the wind speed was the dominant factor in the fire spread, with a maximum value no more than 6.4 m/s, when the terrain height changes little and the proportion of grassland is low. After the feedback, the propagation speed of the fire accelerated, accompanying the release of latent and sensible heat, and local circulation formed near the front of the fire, leading to a convergence and divergence zone in the downwind area. It is worth noting that during a period of more than 140 h of simulation, the area of the fire field increased by 17% from ignition time. Therefore, considering the fire–atmosphere interaction is necessary for accurately predicting fire behavior. Full article

The destructive Sir Ivan Dougherty fire burned 55,000 hectares around 250 km northwest of Sydney in New South Wales on 12 February 2017. Record hot temperatures were recorded in the area during the lead-in days and the fire conditions at the time were described as the ‘worst ever seen in NSW’. The observed weather conditions were hot, dry and very windy ahead of a synoptic frontal wind change during the afternoon. ‘Extreme’ to ‘catastrophic’ fire weather was predicted, and the potential for extreme fire behaviour was identified several days in advance. The Australian coupled fire–atmosphere model ACCESS-Fire has been run to explore the characteristics of the Sir Ivan fire. Several features resulting from fire–atmosphere interaction are produced in the simulations. Simulated heat flux along the fire perimeter shows increased intensity on the northern fire flank in response to gradual backing winds ahead of the main frontal wind change. Temporal and spatial variability in fire activity, seen as pulses in fire intensity and fireline wind speed, develop in response to boundary layer rolls in the wind fields. Deep moist convection consistent with the observed pyrocumulonimbus (pyroCb) cloud is simulated over the fire at around the time of the frontal wind change, and matches guidance from the ‘PyroCb Firepower Threshold’ tool, which showed transient favourable conditions. After the wind change, short-lived near-surface and elevated vortices suggest organised rotating features on the northern flank of the fire. The coupled model captures processes that cannot be produced in uncoupled fire predictions and that are not captured in current operational meteorological forecast products provided to Australian fire agencies. This paper links the features from coupled simulations to available observations and suggests pathways to embed the learnings in operational practice. Full article

Terrestrial LiDAR scans (TLS) offer a rich data source for high-fidelity vegetation characterization, addressing the limitations of traditional fuel sampling methods by capturing spatially explicit distributions that have a significant impact on fire behavior. However, large volumes of complex, high resolution data are difficult to use directly in wildland fire models. In this study, we introduce a novel method that employs a voxelization technique to convert high-resolution TLS data into fine-grained reference voxels, which are subsequently aggregated into lower-fidelity fuel cells for integration into physics-based fire models. This methodology aims to transform the complexity of TLS data into a format amenable for integration into wildland fire models, while retaining essential information about the spatial distribution of vegetation. We evaluate our approach by comparing a range of aggregate geometries in simulated burns to laboratory measurements. The results show insensitivity to fuel cell geometry at fine resolutions (2–8 cm), but we observe deviations in model behavior at the coarsest resolutions considered (16 cm). Our findings highlight the importance of capturing the fine scale spatial continuity present in heterogeneous tree canopies in order to accurately simulate fire behavior in coupled fire-atmosphere models. To the best of our knowledge, this is the first study to examine the use of TLS data to inform fuel inputs to a physics based model at a laboratory scale. Full article

Despite recent advances in both coupled fire modeling and measurement techniques to sample the fire environment, the fire–atmosphere coupling mechanisms that lead to fast propagating wildfires remain poorly understood. This knowledge gap adversely affects fire management when wildland fires propagate unexpectedly rapidly and shift direction due to the fire impacts on local wind conditions. In this work, we utilized observational data from the FireFlux2 prescribed burn and numerical simulations performed with a coupled fire–atmosphere model WRF-SFIRE to assess the small-scale impacts of fire on local micrometeorology under moderate wind conditions (10–12 m/s). The FireFlux2 prescribed burn provided a comprehensive observational dataset with in situ meteorological observations as well as IR measurements of fire progression. To directly quantify the effects of fire–atmosphere interactions, two WRF-SFIRE simulations were executed. One simulation was run in a two-way coupled mode in which the heat and moisture fluxes emitted from the fire were injected into the atmosphere, and the other simulation was performed in a one-way coupled mode for which the atmosphere was not affected by the fire. The difference between these two simulations was used to analyze and quantify the fire impacts on the atmospheric circulation at different sections of the fire front. The fire-released heat fluxes resulted in vertical velocities as high as 10.8 m/s at the highest measurement level (20 m above ground level) gradually diminishing with height and dropping to 7.9 m/s at 5.77 m. The fire-induced horizontal winds indicated the strongest fire-induced flow at the lowest measurement levels (as high as 3.3 m/s) gradually decreasing to less than 1 m/s at 20 m above ground level. The analysis of the simulated flow indicates significant differences between the fire-induced circulation at the fire head and on the flanks. The fire-induced circulation was much stronger near the fire head than at the flanks, where the fire did not produce particularly strong cross-fire flow and did not significantly change the lateral fire progression. However, at the head of the fire the fire-induced winds blowing across the front were the strongest and significantly accelerated fire progression. The two-way coupled simulation including the fire-induced winds produced 36.2% faster fire propagation than the one-way coupled run, and more realistically represented the fire progression. Full article

In this study, we focus on the effects of fuel bed representation and fire heat and smoke distribution in a coupled fire-atmosphere simulation platform for two landscape-scale fires: the 2018 Camp Fire and the 2021 Caldor Fire. The fuel bed representation in the coupled fire-atmosphere simulation platform WRF-Fire currently includes only surface fuels. Thus, we enhance the model by adding canopy fuel characteristics and heat release, for which a method to calculate the heat generated from canopy fuel consumption is developed and implemented in WRF-Fire. Furthermore, the current WRF-Fire heat and smoke distribution in the atmosphere is replaced with a heat-conserving Truncated Gaussian (TG) function and its effects are evaluated. The simulated fire perimeters of case studies are validated against semi-continuous, high-resolution fire perimeters derived from NEXRAD radar observations. Furthermore, simulated plumes of the two fire cases are compared to NEXRAD radar reflectivity observations, followed by buoyancy analysis using simulated temperature and vertical velocity fields. The results show that while the improved fuel bed and the TG heat release scheme have small effects on the simulated fire perimeters of the wind-driven Camp Fire, they affect the propagation direction of the plume-driven Caldor Fire, leading to better-matching fire perimeters with the observations. However, the improved fuel bed representation, together with the TG heat smoke release scheme, leads to a more realistic plume structure in comparison to the observations in both fires. The buoyancy analysis also depicts more realistic fire-induced temperature anomalies and atmospheric circulation when the fuel bed is improved. Full article

Understanding the relationship between fire behavior and the driving weather conditions is critical for fire management and long-term fire risk assessment. In this study, we focus on two wildfire events: the Split wildfire in Croatia and the Forcett–Dunalley wildfire in Tasmania, Australia. The antecedent weather in both events included extremely dry conditions and higher-than-average air temperatures in the months prior to the events. The synoptic patterns in both events consisted of a large surface pressure gradient, which generated strong wind, driving the fire’s spread. The Weather Research and Forecasting (WRF) model was utilized to simulate fire weather conditions during the development of the two events. In the innermost domain of WRF, resolution is 500 m with explicit moisture calculation only, and there are 66 vertical levels, with about 20 of them to resolve the boundary layer. The WRF simulations are well verified by station observations, including upper-level wind speeds. The convergence line pattern in the Tasmanian event, which was conducive to intense plume development, has been well simulated. Only a slight discrepancy was identified in the simulation of the coastal change in wind direction in the Croatian event. It is identified that in the Split case, bura wind was highly coupled with an upper-level trough, which induced subsidence of the upper-level dry and cold air to the surface, causing rapid drying of the fuel. During the Forcett–Dunalley fire, the atmosphere was unstable, which enabled deep pyrocumulonimbus development. In general, the development from ignition to the timing of the most extreme fire intensity in both events was largely determined by the evolution of the surface to upper-level meteorological drivers. While these extreme meteorological conditions would impact fire-fighting strategies such as aircraft operations, a model-based estimate of the high-risk areas is critical. Our findings would also benefit an estimate of the climatology of fire events with similar behavior and thus a long-term fire risk assessment. Full article

Fire-prone landscapes found throughout the world are increasingly managed with prescribed fire for a variety of objectives. These frequent low-intensity fires directly impact lower forest strata, and thus estimating surface fuels or understory vegetation is essential for planning, evaluating, and monitoring management strategies and studying fire behavior and effects. Traditional fuel estimation methods can be applied to stand-level and canopy fuel loading; however, local-scale understory biomass remains challenging because of complex within-stand heterogeneity and fast recovery post-fire. Previous studies have demonstrated how single location terrestrial laser scanning (TLS) can be used to estimate plot-level vegetation characteristics and the impacts of prescribed fire. To build upon this methodology, co-located single TLS scans and physical biomass measurements were used to generate linear models for predicting understory vegetation and fuel biomass, as well as consumption by fire in a southeastern U.S. pineland. A variable selection method was used to select the six most important TLS-derived structural metrics for each linear model, where the model fit ranged in R² from 0.61 to 0.74. This study highlights prospects for efficiently estimating vegetation and fuel characteristics that are relevant to prescribed burning via the integration of a single-scan TLS method that is adaptable by managers and relevant for coupled fire–atmosphere models. Full article