Fire/atmosphere interactions
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This document discusses modeling wildfire behavior and surface-atmosphere interactions. It covers: 1. The challenges of modeling wildfires due to their multi-physics, multi-scale nature and complex interactions between surface fires and atmospheric conditions. 2. The author's PhD research which used data assimilation to reduce uncertainties in regional-scale wildfire spread modeling and multi-physics CFD simulations to study flame-scale processes. 3. The current state-of-the-art in coupled fire-atmosphere modeling including strategies for coupling models, accounting for atmospheric emissions, and offline simulation cases.
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Fire/atmosphere interactions
- 1. Towards more accurate predictions of wildfire behavior Modeling surface/atmosphere interactions Mélanie ROCHOUX, Ph.D. Postdoctoral fellow Meteorological Research Division Introductory seminar 13 June 2014 Environnement Canada Environment Canada
- 2. ①➀ INTRODUCTION: Regional-scale modeling viewpoint • Fire danger • Multi-physics multi-scale problem • Regional-scale modeling viewpoint ➁ Ph.D. RESEARCH: How to address modeling uncertainties? • Data assimilation at regional scale • Multi-physics simulation at flame scale ➂ STATE-OF-THE-ART: Fire/atmosphere coupling • Coupling strategy • Atmospheric emissions • Offline simulation case OUTLINE Introductory seminar 2 INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX
- 3. INTRODUCTION ● ● ● Fire danger at operational level • Global viewpoint: about 400 million hectares burnt every year ➙3 % of the Earth’s vegetation area © NASA Active fire map by MODIS over a 10-day period 9-18 August 2013 • Canadian Forest Fire Weather Index System • Fire Weather Index (FWI) ➙ numerical rating of fire potential intensity • Daily maps of fire weather • Main limitation ➙ meteorological index Canadian Wildland Fire Information System, NRCan INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX ➙ modis-fire.umd.edu/ 3
- 4. INTRODUCTION ● ● ● Fire danger at operational level Fine fuel moisture code (FFMC) Duff moisture code (DMC) Drought Code (DC) FUEL MOISTURE CODES FIRE WEATHER OBSERVATION S FIRE BEHAVIOR INDICES Air temperature and humidity, wind, 24-h rainfall Wind Air temperature and humidity, 24- h rainfall Air temperature, 24-h rainfall Initial spread index (ISI) Buildup index (BUI) Fire weather index (FWI) 4 INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX • Canadian Forest Fire Weather Index System • Fire Weather Index (FWI) ➙ numerical rating of fire potential intensity • Daily maps of fire weather • Main limitation ➙ meteorological index ➙ cwfis.cfs.nrcan.gc.ca/home
- 5. INTRODUCTION ● ● ● Fire danger at operational level Fine fuel moisture code (FFMC) Duff moisture code (DMC) Drought Code (DC) FUEL MOISTURE CODES FIRE WEATHER OBSERVATION S FIRE BEHAVIOR INDICES Air temperature and humidity, wind, 24-h rainfall Wind Air temperature and humidity, 24- h rainfall Air temperature, 24-h rainfall Initial spread index (ISI) Buildup index (BUI) Fire weather index (FWI) 5 INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX • Canadian Forest Fire Weather Index System • Fire Weather Index (FWI) ➙ numerical rating of fire potential intensity • Daily maps of fire weather • Main limitation ➙ meteorological index DMC: loosely compacted decomposing matter -nominal depth 7 cm DC: deep compact organic matter -nominal depth 18 cm FFMC: litter and other fine fuels -nominal depth 1.2 cm From Chelene Krezek-Hanes, Great Lakes Forestry Centre, Canadian Forest Service ➙ cwfis.cfs.nrcan.gc.ca/home
- 6. INTRODUCTION ● ● ● Multi-physics multi-scale problem 2009 Black Saturday bushfires ▶ 450 000 ha (1/3 of the annual burnt area in Australia) ▶ 173 people died ▶ strong fire/atmosphere coupling 300 km © NASA Fire/Surface ➙ Vegetation ➙ Topography Fire/Atmosphere ➙ Dynamics ➙ Chemistry Turbulence Gases & Aerosols Wind Biomass combustion Surface- to-canopy • Complexity of wildfire behavior • Wide range of length-scale (from mm to km) • Poorly-defined biomass fuels • Atmospheric external forcing • Climate change (megafires) ➙ CHALLENGE: How to accurately represent surface/atmosphere interactions in wildfires? 6 INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX
- 7. INTRODUCTION ● ● ● Multi-physics multi-scale problem • Complexity of wildfire behavior • Wide range of length-scale (from mm to km) • Poorly-defined biomass fuels • Atmospheric external forcing • Climate change (megafires) ➙ CHALLENGE: How to accurately represent surface/atmosphere interactions in wildfires? Radiation Wind Flame Pyrolysis Heat/mass fluxes Terrain topography EMISSIONS PYROLYSI S COMBUSTION FLUID DYNAMICS HEAT TRANSFER ATMOSPHERIC PHYSICS 7 INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX
- 8. INTRODUCTION ● ● ● Regional-scale modeling viewpoint © FOREFIRE, Favone wildfire (30 ha)© FOREFIRE, Favone wildfire (30 ha) Regional-scale viewpoint FIRE FRONT Burnt area Fire front Unburnt vegetation TOPOGRA PHY Terrain slope BIOMASS FUEL Moisture content Packing ratio Layer thickness WEATHER Wind magnitude Wind direction Rate Of spread • Front-tracking simulator • Prediction of the location of the surface fire front on horizontal plane • Local evaluation of the ROS along the normal direction to the fire front ➙ ROTHERMEL [1] ➙ BALBI [2] • Examples of simulator ➙ FOREFIRE [3], asynchronous Lagrangian solver ➙ FIREFLY [4], level-set solver [1] Rothermel, USDA Forest Service (1972) [2] Balbi et al. Comb. Flame (2004) [3] Filippi et al. Proc. Comb. Inst. (2013) [4] Rochoux, Ph.D. Ecole Centrale Paris (2014) 8 INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX
- 9. ①➀ INTRODUCTION: Regional-scale modeling viewpoint • Fire danger • Multi-physics multi-scale problem • Regional-scale modeling viewpoint ➁ Ph.D. RESEARCH: How to address modeling uncertainties? • Data assimilation at regional scale • Multi-physics simulation at flame scale ➂ STATE-OF-THE-ART: Fire/atmosphere coupling • Coupling strategy • Atmospheric emissions • Offline simulation case OUTLINE Introductory seminar 9 INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX
- 10. PH.D. RESEARCH ● ● ● Modeling limitations INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX • ISSUE: How to accurately describe wildfire spread? 10 Rochoux M.C., Ph.D. Ecole Centrale Paris (2014) • OBJECTIVE: Quantify and reduce uncertainty in ROS modeling Data assimilation for REGIONAL-SCALE wildfire spread forecast Environmental conditions Fire front locationPhysics-based modeling FLAME-SCALE multi-physics CFD simulations
- 11. PH.D. RESEARCH ● ● ● Data assimilation for regional-scale forecast INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX 11 Environmental conditions Fire front location • Anisotropy in wildfire spread ➙ complex spatial correlations along the fireline • Highly non-linear observation operator ➙ complex relationship between ROS model parameters and model counterparts of observations Simulated front Observed front (x1 , y1 ) (x2 , y2 ) (x3 ,y3 ) (x4 , y4 ) (x1 O ,y1 O ) (x2 O ,y2 O ) Distance between fronts FIREFLY wildfire spread simulator Parameters Initial condition Boundary conditions Comparison Simulated fronts Observations
- 12. PH.D. RESEARCH ● ● ● Data assimilation for regional-scale forecast INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX 12 Environmental conditions Fire front location • Parameter estimation ➙ temporal variability of the errors in the ROS model parameters (mid- to long-term) ➙ reduced-cost approach (Polynomial Chaos) • State estimation ➙ persistence of the correction of the model initial condition (short-term) Simulated front Observed front (x1 , y1 ) (x2 , y2 ) (x3 ,y3 ) (x4 , y4 ) (x1 O ,y1 O ) (x2 O ,y2 O ) FIREFLY wildfire spread simulator Parameters Initial condition Boundary conditions Comparison Simulated fronts Observations Ensemble Kalman filter Parameter estimation State estimation Analysis
- 13. PH.D. RESEARCH ● ● ● Data assimilation for regional-scale forecast INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX 13 EnKF analysis of synthetic observations + of fire front FORECAST True location Ensemble members ANALYSIS True location Ensemble members observations Ensemble generation for state estimation ➙ Anisotropy in wildfire spread ➙ Selection of spatially-distributed biomass fuel properties and distinct wind conditions between the ensemble members. Approach relevant for incomplete observations due to: ➙ opacity of the thermal plume ➙ limited monitoring
- 14. PH.D. RESEARCH ● ● ● Data assimilation for regional-scale forecast INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX 14 Controlled grassland fire experiment x [m] y [m] Extraction of the 600 K iso-temperature at 14-s time intervals 1min32s50s 1min46s1min04s 1min28s Time FRONT Wind 1m/s
- 15. PH.D. RESEARCH ● ● ● Data assimilation for regional-scale forecast INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX 15 Controlled grassland fire experiment state parameter state parameter state parameter • STATE ESTIMATION: non-uniform correction of the fire front • PARAMETER ESTIMATION: mean correction along the fireline ANALYSIS PERFORMANCE ANALYSIS FORECAST
- 16. ①➀ INTRODUCTION: Regional-scale modeling viewpoint • Fire danger • Multi-physics multi-scale problem • Regional-scale modeling viewpoint ➁ Ph.D. RESEARCH: How to address modeling uncertainties? • Data assimilation at regional scale • Multi-physics simulation at flame scale ➂ STATE-OF-THE-ART: Fire/atmosphere coupling • Coupling strategy • Atmospheric emissions • Offline simulation case OUTLINE Introductory seminar 16 INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX
- 17. ➙ anridea.univ-corse.fr/ ➙ OBJECTIVE: develop a coupled fire-atmosphere simulation prototype Biomass thermal degradation VEGETATION SCALES Combustion processes Surface/atmosphe re interactions FLAME SCALE ATMOSPHERIC SCALES Atmospheric dynamics and emissions FIRE/ATMOSPHERE MODEL ● ● ● Coupling strategy 17 INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX
- 18. INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX FIRE/ATMOSPHERE MODEL ● ● ● Coupling strategy 18 • Lagrangian representation of the subgrid-scale fire front Atmospheric model grid size (∼ 50 m) VEGETATION • Terrain data • Distribution: using CORINE ESA database and forest inventory (BDForêt) ➙ Sensible heat flux ➙ Water vapor flux ➙ Radiant temperature ➙WIND •Interpolation at the front markers •assumed constant over one model time step •1-D boundary layer model (mid- grid)
- 19. INTRODUCTORY SEMINAR May 2014Mélanie ROCHOUX FIRE/ATMOSPHERE MODEL ● ● ● Coupling strategy 19 • Introduction of a burning matrix • Burning ratio Rb = ratio of the burning area over the atmospheric grid area, ranging from 0 (no fire) to 1 (all burning). • 1 value of burning ratio per atmospheric model grid box SURFACE FLUXES REQUIRE: • Nominal convection heat flux • Nominal water loading • Nominal flame temperature Tn (1000 K) • Soil temperature from the atmospheric model Ts ➙ Sensible heat flux ➙ Water vapor flux ➙ Radiant temperature FORMULATION OF THE EQUIVALENT RADIANT TEMPERATURE Te: Te 4 = (1 - Rb) Ts 4 + Rb Tn 4
- 20. INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX FIRE/ATMOSPHERE MODEL ● ● ● Coupling strategy 20 • Limitations in surface wildfire spread modeling • Physical modeling inaccuracies ➙ Heat transfer to vegetation ➙ Local and steady-state assumption (canyons) • Absence of modeling for fire/atmosphere interactions Favone wildfire (30 ha) FOREFIRE Coupled Observed Two-way fire/atmosphere coupling FOREFIRE/MESO-NH
- 21. INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX FIRE/ATMOSPHERE MODEL ● ● ● Atmospheric chemistry 21 • Emission sources • Emissions during the biomass thermal degradation (e.g. soot particles) • Incomplete combustion ➙ Sensible heat flux ➙ Water vapor flux ➙ Radiant temperature ➙ Gas species emission • Species emitted in the surface layer (injection model) and mixed by the turbulence scheme (mainly CO) • Distinction of flaming and smoldering modes of combustion in the injection model • Emission factor database still incomplete, in particular for Mediterranean ecosystems
- 22. INTRODUCTORY SEMINAR June 13, 2014Mélanie ROCHOUX FIRE/ATMOSPHERE MODEL ● ● ● Atmospheric chemistry 22 • Transport and chemistry in the smoke plume • No parameterization of the smoke injection height ➙ explicit calculation • ReLACS chemical kinetic scheme used in MÉSO-NH (no aerosol scheme) Fire/Surface ➙ Vegetation ➙ Topography Fire/Atmosphere ➙ Dynamics ➙ Chemistry Turbulence Gases & Aerosols Wind Case study : Lançon de Provence (2005), Strada et al. 2012
- 23. SOURCES ➙ High-resolution biomass fuel ➙ Combustion ➙ Emission models ATMOSPHERE ➙ Dynamics of the smoke plume ➙ Chemistry (aerosols) ➙ Feedbacks on fire Overview of fire research OBSERVATIONS ➙ Detection ➙ Monitoring
Hinweis der Redaktion
- Qu’est-ce qui fait que de grands feux peuvent se développer ? Du feu de surface au feu de cimes Formation d’un panache s’étendant sur plusieurs dizaines voire centaines de km Difficile de stopper un très grand feu tel les megafires(favorisés par l’occurrence de plus en plus forte d’évènements extrêmes) Pour éviter que les feux atteignent des dimensions qui les rendent incontrôlables, il faut pouvoir prévoir rapidement où le feu va se propager et ainsi optimiser la stratégie de terrain. Des prévisions fiables de propagation à l’échelle régionale seraient nécessaires, en terme de comportement du feu et aussi de changement de comportement sous l’effet du changement climatique.
- the generation of the stochastic ensemble must represent the anisotropy in wildfire spread. This anisotropy was implicitly introduced in the SE ap- proach by selecting spatially-distributed biomass fuel properties and distinct wind conditions between the different members in the ensemble. The SE approach was shown to be successful at retrieving at low computational cost (i.e., with a relatively small number of members in the ensemble) the actual shape of the fire front in cases with strong anisotropic propagation conditions. This approach was also found relevant for observations made with significant errors and/or cases in which the observations are incomplete (e.g., when only a section of the fireline is informed), in order to reconstruct a complete, reliable initial condition for FIREFLY restart.
- ISBA est trop "grossier" les données en entrée font des km en résolution, du coup pas possible et distribution spécifique. Le faire en HR c'est l'objet principal de l'ANR firecaster. Pour la caractérisation: données terrain (surface/volume... humidité estimée (= f(humidité de l'air après 1 h pour le vegetal mort)) Pour la distribution spatiale : BDForêt / corine http://inventaire-forestier.ign.fr/spip/spip.php?rubrique53 Modèle 1D de couche limite, vent mi-maille << approx pourrie et injustifiable mais meilleure que la fausse hauteur de flamme que l'on peut diagnostiquer, c'était un des objectifs (trop audacieux) de l'étude AVBP/Firestar d'avoir une vue du volume de gaz pour une meilleure estimation.
- Equivalent heat flux (W/m2) ➙ Energy over the hot gaseous column ➙ Multiplication of the nominal convection heat flux by the burning ratio Rb Water vapor mass flux (kg/m2/s) ➙ Multiplication of the nominal water loading by the burning ratio Rb Equivalent radiant temperature ➙ Nominal flame temperature Tn (1000 K) ➙ Soil temperature from the atmospheric model Ts (day temperature at ground level) ➙ Formulation of the radiant temperature Te (K): Te4 = (1 - Rb) Ts4 + Rb Tn4
- - No anthropogenic emissions considered - No aerosol scheme - All species are emitted in the first surface level in the model and mixed in the boundary layer by the turbulence scheme. There is no a-priori injection height. A passive tracer (referred to as fire aerosol-like tracer) has been introduced to mimic fire-produced PM10 aerosols. The fire aerosol-like tracer is initialized to zero and has a deposition velocity of 3 cm/s (Seung-Muk et al. 2006); it is only emitted above the fire. - The simulated smoke plume was trapped within the boundary layer (injection height between 0.9 and 1.2km), a common feature of Mediterranean fires that mostly release emissions into the atmospheric boundary layer. - The coupled model with simplified assumptions concerning emissions and initialization simulated an sharp increase of O3 precursors near the fire and a subsequent O3 depletion in the fire plume (over 40km) as well as a strong increase of a fire aerosol-like tracer at the proper timing compared to the observations. Production of O3 (over the sea) was simulated several kilometers downwind of the fire as already observed in field campaigns.
- ISBA est trop "grossier" les données en entrée font des km en résolution, du coup pas possible et distribution spécifique. Le faire en HR c'est l'objet principal de l'ANR firecaster. Pour la caractérisation: données terrain (surface/volume... humidité estimée (= f(humidité de l'air après 1 h pour le vegetal mort)) Pour la distribution spatiale : BDForêt / corine http://inventaire-forestier.ign.fr/spip/spip.php?rubrique53 Modèle 1D de couche limite, vent mi-maille << approx pourrie et injustifiable mais meilleure que la fausse hauteur de flamme que l'on peut diagnostiquer, c'était un des objectifs (trop audacieux) de l'étude AVBP/Firestar d'avoir une vue du volume de gaz pour une meilleure estimation.
- - No anthropogenic emissions considered - No aerosol scheme - All species are emitted in the first surface level in the model and mixed in the boundary layer by the turbulence scheme. There is no a-priori injection height. A passive tracer (referred to as fire aerosol-like tracer) has been introduced to mimic fire-produced PM10 aerosols. The fire aerosol-like tracer is initialized to zero and has a deposition velocity of 3 cm/s (Seung-Muk et al. 2006); it is only emitted above the fire. - The simulated smoke plume was trapped within the boundary layer (injection height between 0.9 and 1.2km), a common feature of Mediterranean fires that mostly release emissions into the atmospheric boundary layer. - The coupled model with simplified assumptions concerning emissions and initialization simulated an sharp increase of O3 precursors near the fire and a subsequent O3 depletion in the fire plume (over 40km) as well as a strong increase of a fire aerosol-like tracer at the proper timing compared to the observations. Production of O3 (over the sea) was simulated several kilometers downwind of the fire as already observed in field campaigns.