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 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

Lagrangian simulation of smoke plume from fire and validation using ground-based lidar and aircraft measurements

2019 ◽  
Vol 213 ◽  
pp. 659-674 ◽  
Author(s):  
Enrico Ferrero ◽  
Stefano Alessandrini ◽  
Bret Anderson ◽  
Elena Tomasi ◽  
Pedro Jimenez ◽  
...  
Keyword(s):  
Aircraft Measurements ◽  
Smoke Plume ◽  
Lagrangian Simulation ◽  
Ground Based Lidar

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

Line Plume Approximation on Atrium Smoke Filling With Thermal Stratified Environment

2003 ◽  
Vol 125 (2) ◽  
pp. 289-300 ◽  
Author(s):  
J. Li ◽  
W. K. Chow
Keyword(s):  
Plume Rise ◽  
Upward Motion ◽  
Smoke Plume ◽  
Air Density ◽  
Smoke Filling ◽  
Balcony Spill Plume

Upward motion of a balcony spill plume in an atrium with a thermal stratified layer will be simulated. This is aimed at answering the question on whether a smoke plume can move up an atrium to reach the ceiling. The gradient of air density in the atrium is taken as a constant negative value. The plume motion under this condition is compared with the case without a thermal stratified layer. It is noted that the effect of stratification is not obvious in regions near to the fire. But for the upper region of the plume, the effect is significant. In this way, the plume might not be able to reach the ceiling of an atrium with a hot enough thermal stratified layer. The maximum plume rise under this condition will also be calculated.

scholarly journals Technical Note: Sensitivity of 1-D smoke plume rise models to the inclusion of environmental wind drag

2009 ◽  
Vol 9 (4) ◽  
pp. 14713-14733 ◽  
Author(s):  
S. R. Freitas ◽  
K. M. Longo ◽  
J. Trentmann ◽  
D. Latham
Keyword(s):  
Amazon Basin ◽  
Ambient Air ◽  
Atmospheric Model ◽  
Technical Note ◽  
Atmospheric Environment ◽  
Horizontal Wind ◽  
Plume Rise ◽  
Additional Increase ◽  
Smoke Plume ◽  
D Model

Abstract. We revisit the parameterization of the vertical transport of hot gases and particles emitted from biomass burning, described in Freitas et al. (2007), to include the effects of environmental wind on transport and dilution of the smoke plume at the cloud scale. Typically, the final vertical height that the smoke plumes reach is controlled by the thermodynamic stability of the atmospheric environment and the surface heat flux released by the fire. However, the presence of a strong horizontal wind can enhance the lateral entrainment and induce additional drag, particularly for small fires, impacting the smoke injection height. This process is quantitatively represented by introducing an additional entrainment term to account for organized inflow of a mass of cooler and drier ambient air into the plume and its drag by momentum transfer. An extended set of equations including the horizontal motion of the plume and the additional increase of the plume radius is solved to explicitly simulate the time evolution of the plume rise with the additional mass and momentum. One-dimensional (1-D) model results are presented for two deforestation fires in the Amazon basin with sizes of 10 and 50 ha under calm and windy atmospheric environments. The results are compared to corresponding simulations generated by the complex non-hydrostatic three dimensional (3-D) Active Tracer High resolution Atmospheric Model (ATHAM). We show that the 1-D model results compare well with the full 3-D simulations. The 1-D model may thus be used in field situations where extensive computing facilities are not available, especially under conditions for which several optional cases must be studied.

scholarly journals Development and optimization of a wildfire plume rise model based on remote sensing data inputs – Part 2

2015 ◽  
Vol 15 (6) ◽  
pp. 9815-9895 ◽  
Author(s):  
R. Paugam ◽  
M. Wooster ◽  
J. Atherton ◽  
S. R. Freitas ◽  
M. G. Schultz ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Atmospheric Chemistry ◽  
Atmospheric Stability ◽  
Quality Criteria ◽  
Landscape Scale ◽  
Training Dataset ◽  
Plume Rise ◽  
Plume Height ◽  
Smoke Plume ◽  
The Impact

Abstract. Biomass burning is one of a relatively few natural processes that can inject globally significant quantities of gases and aerosols into the atmosphere at altitudes well above the planetary boundary layer, in some cases at heights in excess of 10 km. The "injection height" of biomass burning emissions is therefore an important parameter to understand when considering the characteristics of the smoke plumes emanating from landscape scale fires, and in particular when attempting to model their atmospheric transport. Here we further extend the formulations used within a popular 1D plume rise model, widely used for the estimation of landscape scale fire smoke plume injection height, and develop and optimise the model both so that it can run with an increased set of remotely sensed observations. The model is well suited for application in atmospheric Chemistry Transport Models (CTMs) aimed at understanding smoke plume downstream impacts, and whilst a number of wildfire emission inventories are available for use in such CTMs, few include information on plume injection height. Since CTM resolutions are typically too spatially coarse to capture the vertical transport induced by the heat released from landscape scale fires, approaches to estimate the emissions injection height are typically based on parametrizations. Our extensions of the existing 1D plume rise model takes into account the impact of atmospheric stability and latent heat on the plume up-draft, driving it with new information on active fire area and fire radiative power (FRP) retrieved from MODIS satellite Earth Observation (EO) data, alongside ECMWF atmospheric profile information. We extend the model by adding an equation for mass conservation and a new entrainment scheme, and optimise the values of the newly added parameters based on comparison to injection heights derived from smoke plume height retrievals made using the MISR EO sensor. Our parameter optimisation procedure is based on a twofold approach using sequentially a Simulating Annealing algorithm and a Markov chain Monte Carlo uncertainty test, and to try to ensure the appropriate convergence on suitable parameter values we use a training dataset consisting of only fires where a number of specific quality criteria are met, including local ambient wind shear limits derived from the ECMWF and MISR data, and "steady state" plumes and fires showing only relatively small changes between consecutive MODIS observations. Using our optimised plume rise model (PRMv2) with information from all MODIS-detected active fires detected in 2003 over North America, with outputs gridded to a 0.1° horizontal and 500 m vertical resolution mesh, we are able to derive wildfire injection height distributions whose maxima extend to the type of higher altitudes seen in actual observation-based wildfire plume datasets than are those derived either via the original plume model or any other parametrization tested herein. We also find our model to be the only one tested that more correctly simulates the very high plume (6 to 8 km a.s.l.), created by a large fire in Alberta (Canada) on the 17 August 2003, though even our approach does not reach the stratosphere as the real plume is expected to have done. Our results lead us to believe that our PRMv2 approach to modelling the injection height of wildfire plumes is a strong candidate for inclusion into CTMs aiming to represent this process, but we note that significant advances in the spatio-temporal resolutions of the data required to feed the model will also very likely bring key improvements in our ability to more accurately represent such phenomena, and that there remain challenges to the detailed validation of such simulations due to the relative sparseness of plume height observations and their currently rather limited temporal coverage which are not necessarily well matched to when fires are most active (MISR being confined to morning observations for example).

scholarly journals A Regression Model for Smoke Plume Rise of Prescribed Fires Using Meteorological Conditions

2014 ◽  
Vol 53 (8) ◽  
pp. 1961-1975 ◽  
Author(s):  
Yongqiang Liu
Keyword(s):  
Air Quality ◽  
Regression Model ◽  
Surface Wind ◽  
Weather Research And Forecasting ◽  
Prescribed Fires ◽  
Plume Rise ◽  
Prescribed Burn ◽  
Prescribed Burns ◽  
Smoke Plume ◽  
Practical Tool

AbstractSmoke plume rise is an important factor for smoke transport and air quality impact modeling. This study provides a practical tool for estimating plume rise of prescribed fires. A regression model was developed on the basis of observed smoke plume rise for 20 prescribed fires in the southeastern United States. The independent variables include surface wind, air temperature, fuel moisture, and atmospheric planetary boundary layer (PBL) height. The first three variables were obtained from the Remote Automatic Weather Stations, most of which are installed in locations where they can monitor local fire danger and are easily accessed by fire managers. The PBL height was simulated with the Weather Research and Forecasting Model. The confidence and validation analyses indicate that the regression model is significant at the 95% confidence level and able to predict hourly values and the average smoke plume rise during a burn, respectively. The prediction of the average smoke plume rise shows larger skills. The model also shows improved skills over two extensively used empirical models for the prescribed burn cases examined in this study, suggesting that it may have the potential to improve smoke plume rise and air quality modeling for prescribed burns. The regression model, however, tends to underestimate large plume rise values and overestimate small ones. A suite of alternative regression models was also provided, one of which can be used when no PBL information is available.

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