scholarly journals Space-based observational constraints for 1-D fire smoke plume-rise models

2012 ◽  
Vol 117 (D22) ◽  
pp. n/a-n/a ◽  
Author(s):  
Maria Val Martin ◽  
Ralph A. Kahn ◽  
Jennifer A. Logan ◽  
Ronan Paugam ◽  
Martin Wooster ◽  
...  
Keyword(s):  
Observational Constraints ◽  
Plume Rise ◽  
Smoke Plume ◽  
Fire Smoke

scholarly journals Important parameters for smoke plume rise simulation with Daysmoke

2010 ◽  
Vol 1 (4) ◽  
pp. 250-259 ◽  
Author(s):  
Yongqiang Liu ◽  
Gary L. Achtemeier ◽  
Scott L. Goodrick ◽  
William A. Jackson
Keyword(s):  
Plume Rise ◽  
Smoke Plume

scholarly journals Analysis of a warehouse fire smoke plume over Paris with an N<sub>2</sub> Raman lidar and an optical thickness matching algorithm

2018 ◽  
Vol 11 (12) ◽  
pp. 6525-6538 ◽  
Author(s):  
Xiaoxia Shang ◽  
Patrick Chazette ◽  
Julien Totems
Keyword(s):  
Optical Thickness ◽  
Monte Carlo Algorithm ◽  
Optical Parameters ◽  
Depolarization Ratio ◽  
Raman Lidar ◽  
Smoke Plume ◽  
Paris Area ◽  
Fire Smoke ◽  
Lidar Ratio ◽  
Warehouse Fire

Abstract. A smoke plume, coming from an accidental fire in a textile warehouse in the north of Paris, covered a significant part of the Paris area on 17 April 2015 and seriously impacted the visibility over the megalopolis. This exceptional event was sampled with an automatic N2 Raman lidar, which operated 15 km south of Paris. The industrial pollution episode was concomitant with the long-range transport of dust aerosols originated from the Sahara, and with the presence of an extended stratus cloud cover. The analysis of the ground-based lidar profiles therefore required the development of an original inversion algorithm, using a top-down aerosol optical thickness matching (TDAM) approach. This study is, to the best of our knowledge, the first lidar measurement of a fresh smoke plume, emitted only a few hours after an accidental warehouse fire. Vertical profiles of the aerosol extinction coefficient, depolarization ratio, and lidar ratio are derived to optically characterize the aerosols that form the plume. We found a lidar ratio close to 50±10 sr for this fire smoke aerosol layer. The particle depolarization ratio is low, ∼1±0.1 %, suggesting the presence of either small particles or spherical hydrated aerosols in that layer. A Monte Carlo algorithm was used to assess the uncertainties on the optical parameters and to evaluate the TDAM algorithm.

Validation of smoke plume rise models using ground-based Lidar

2014 ◽  
Author(s):  
V. Kovalev ◽  
S. Urbanski ◽  
A. Petkov ◽  
A. Scalise ◽  
C. Wold ◽  
...  
Keyword(s):  
Plume Rise ◽  
Smoke Plume ◽  
Ground Based Lidar

scholarly journals Optical thickness matching algorithm applied to the case study of an accidental fire smoke plume over the Paris area with N<sub>2</sub>-Raman lidar

2018 ◽  
Author(s):  
Xiaoxia Shang ◽  
Patrick Chazette ◽  
Julien Totems
Keyword(s):  
Optical Thickness ◽  
Monte Carlo Algorithm ◽  
Spherical Particles ◽  
Optical Parameters ◽  
Aerosol Layer ◽  
Raman Lidar ◽  
Smoke Plume ◽  
Paris Area ◽  
Fire Smoke ◽  
Lidar Ratio

Abstract. A smoke plume, coming from an accidental fire in a textile warehouse in the north of Paris, covered a significant part of the Paris area on 17 April 2015 and seriously impacted the visibility over the megalopolis. This exceptional event was sampled with an automatic N2-Raman lidar, which operated 15 km south of Paris. The industrial pollution episode was concomitant with a long-range transport of dust aerosols raised from Sahara, and with the presence of an extended stratus cloud cover. The analysis of the ground-based lidar profiles therefore required the development of an original inversion algorithm, using a top-down aerosol optical thickness matching (TDAM) approach. This study is, to the best of our knowledge, the first lidar measurement of an accidental fire smoke plume. Vertical profiles of the aerosol extinction coefficient, depolarization and lidar ratio are derived to optically characterize the aerosols that form the plume. We found a lidar ratio close to 50 ± 10 sr for this fire smoke aerosol layer. The particle depolarization ratio is low, ~ 1 ± 0.1 %, suggesting the presence of spherical particles and therefore highly hydrated aerosols in that layer. A Monte Carlo algorithm was used to assess the uncertainties on the optical parameters, and to evaluate the TDAM algorithm.

scholarly journals Capturing Plume Rise and Dispersion with a Coupled Large-Eddy Simulation: Case Study of a Prescribed Burn

Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 579
Author(s):  
Nadya Moisseeva ◽  
Roland Stull
Keyword(s):  
Large Eddy Simulation ◽  
Numerical Models ◽  
Real Life ◽  
Plume Rise ◽  
Atmospheric Conditions ◽  
Prescribed Burn ◽  
Smoke Plume ◽  
Fire Emissions ◽  
Eddy Simulation ◽  
Large Eddy

Current understanding of the buoyant rise and subsequent dispersion of smoke due to wildfires has been limited by the complexity of interactions between fire behavior and atmospheric conditions, as well as the uncertainty in model evaluation data. To assess the feasibility of using numerical models to address this knowledge gap, we designed a large-eddy simulation of a real-life prescribed burn using a coupled semi-emperical fire–atmosphere model. We used observational data to evaluate the simulated smoke plume, as well as to identify sources of model biases. The results suggest that the rise and dispersion of fire emissions are reasonably captured by the model, subject to accurate surface thermal forcing and relatively steady atmospheric conditions. Overall, encouraging model performance and the high level of detail offered by simulated data may help inform future smoke plume modeling work, plume-rise parameterizations and field experiment designs.

scholarly journals Modeling Smoke Plume-Rise and Dispersion from Southern United States Prescribed Burns with Daysmoke

Atmosphere ◽  
2011 ◽  
Vol 2 (3) ◽  
pp. 358-388 ◽  
Author(s):  
Gary L. Achtemeier ◽  
Scott A. Goodrick ◽  
Yongqiang Liu ◽  
Fernando Garcia-Menendez ◽  
Yongtao Hu ◽  
...  
Keyword(s):  
United States ◽  
Southern United States ◽  
Plume Rise ◽  
Prescribed Burns ◽  
Smoke Plume

scholarly journals Evaluation of wildland fire smoke plume dynamics and aerosol load using UV scanning lidar and fire–atmosphere modelling during the Mediterranean Letia 2010 experiment

2014 ◽  
Vol 14 (3) ◽  
pp. 509-523 ◽  
Author(s):  
V. Leroy-Cancellieri ◽  
P. Augustin ◽  
J. B. Filippi ◽  
C. Mari ◽  
M. Fourmentin ◽  
...  
Keyword(s):  
Wildland Fire ◽  
Mediterranean Area ◽  
Atmospheric Model ◽  
Vertical Position ◽  
Passive Tracer ◽  
Smoke Plume ◽  
Fire Propagation ◽  
Lidar Measurements ◽  
Fire Smoke ◽  
Scanning Lidar

Abstract. Vegetation fires emit large amount of gases and aerosols which are detrimental to human health. Smoke exposure near and downwind of fires depends on the fire propagation, the atmospheric circulations and the burnt vegetation. A better knowledge of the interaction between wildfire and atmosphere is a primary requirement to investigate fire smoke and particle transport. The purpose of this paper is to highlight the usefulness of an UV scanning lidar to characterise the fire smoke plume and consequently validate fire–atmosphere model simulations. An instrumented burn was conducted in a Mediterranean area typical of ones frequently subject to wildfire with low dense shrubs. Using lidar measurements positioned near the experimental site, fire smoke plume was thoroughly characterised by its optical properties, edge and dynamics. These parameters were obtained by combining methods based on lidar inversion technique, wavelet edge detection and a backscatter barycentre technique. The smoke plume displacement was determined using a digital video camera coupled with the lidar. The simulation was performed using a mesoscale atmospheric model in a large eddy simulation configuration (Meso-NH) coupled to a fire propagation physical model (ForeFire), taking into account the effect of wind, slope and fuel properties. A passive numerical scalar tracer was injected in the model at fire location to mimic the smoke plume. The simulated fire smoke plume width remained within the edge smoke plume obtained from lidar measurements. The maximum smoke injection derived from lidar backscatter coefficients and the simulated passive tracer was around 200 m. The vertical position of the simulated plume barycentre was systematically below the barycentre derived from the lidar backscatter coefficients due to the oversimplified properties of the passive tracer compared to real aerosol particles. Simulated speed and horizontal location of the plume compared well with the observations derived from the videography and lidar method, suggesting that fire convection and advection were correctly taken into account.

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