Fire spread and plume modelling

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Fire spread and plume modelling J.B.Filippi- F.Bosseur / Céline Mari Laboratoire Sciences pour l environnement Laboratoire d Aérologie University of Corsica / CNRS University of Toulouse / CNRS 1/21

Multiscale processes Global impacts Fire-atmosphere interactions Fire behavior Flame scale 2/21

Injection height: under or above ABL? a sub-grid scale process d e - Plume-in-grid models (application to fire?) - Statistical models (Sofiev et al., 2012) - Physical models (1D): 1D PRM model (Freitas et al., 2010) EDMF (Rio et al., 2010) Model Grid cell 3/21

Fire physics Energy balance Fire behavior: relation between consumption, radiation and convection 4/21 Wooster M., King's College

Fire spread model ForeFire: Semi-physical fire spread model to calculate the fire rate of spread. RoS: Analytical formulation where wind and slope effects are explicitly accounted Rothermel's like model: fire behavior is described by the propagation velocity of the fire front Fire front = tilted radiant panel which heats the vegetation in front of it pyrolitic step Advance of the fire front = front tracking algorithm (set of markers, fixed burning duration) 5/21 (Balbi et al., 2009; Filippi et al., 2009)

Toward an on-line coupled fire-atmosphere model Burning area Radiative temperature Heat/vapor fluxes Chemical fluxes Elevation Fuel Humidity Forefire Wind 6/21

Toward an on-line coupled fire-atmosphere model Burning area Radiative temperature Heat/vapor fluxes Chemical fluxes Elevation Fuel Humidity Forefire Meso-NH/LES Wind 7/21

Fire spread model online API Try it : http://forefire.univ-corse.fr C++ code with numpy interface https://github.com/forefireapi/firefront 8/21

Fire spread model online API Try it : http://forefire.univ-corse.fr C++ code with numpy interface https://github.com/forefireapi/firefront 9/21

A mesoscale meteorological model Meso-NH Meso-NH dynamics: - Non-hydrostatic: acceleration of vertical wind suitable down to metric grid meshes - The continuity equation contains the sound waves. Pertinent if Mach V/c > 1 but not in meteorology! need to be filtered anelastic (removes acoustic waves analytically) uncompressible (mean density varies little) Meso-NH physics http://mesonh.aero.obsmip.fr/ Part of the model that deal with adiabatic processes, water state changes, subgrid processes, surface interaction, chemistry,... 10/21

The surface model SURFEX http://mesonh.aero.obsmip.fr/ The surface model SURFEX for representing the ground atmosphere interactions by considering different surface types: 11/21

The surface model SURFEX - receives atmospheric forcing - solves the evolution of the surface - send back to the atmosphere the turbulent fluxes: sensible and latent heat fluxes 12/21

Fuel (surface) data : 2 m resolution (roads, houses) High resolution coupling Sub-grid surface fluxes integration, combustion fluxes models (5m) to atmospheric resolution (50m) 13/21

Challenges in the fire-atmosphere coupling Physical impact of the fire into the atmospheric model: - The model must be able to simulate the fire effects at high resolution (10 to 50 m) - The upward radiative flux which depends on Ts at the fourth power. Surface temperature is classically around 300 K. In fires it is ~ 1000 K Upward radiative flux is 100 times larger than usual!! - The turbulent heat flux: It usually reaches 200-1000 W/m2. In fire the heat flux reaches 500 000 to 1 000 000 W/m2 Upward sensible heat flux is 1000 times larger than usual!! 14/21

Is fire propagation rate sensitive to the fire-atmosphere coupling? Example: The Favone fire (25ha) x = y = z =50m Domain size: 2.5 km x 2.5 km x 1.5 km Duration: 4 hours Homogeneous mediterranean schrubs Passive tracer to mimic the smoke plume Fire contour: Non-coupled simulation Observation Coupled simulation 15/21

Fire-atmosphere-chemistry coupled simulation high resolution simulation preserves the strong concentrations of NOx in the smoke plume (no instantaneous dilution of NOx in large grid cell) ozone titration 16/21

Chemical aging of polluted plumes: the ozone story O 3 + NO Downwind O 3 production Close to the fire O 3 depletion 17/21 Jost et al., 2003; Trentmann et al., 2003; Masson et al., 2006

The AULLENE 2009 fire 3500 ha 900 proc 24 millions of grid points 18/21

Outlooks Weather-fire behavior model coupled with online atmospheric chemistry - large Euro-Med fires - test chemistry & aerosols smoke radiative forcing - assess fuel properties (humidity, density, vegetation type, emission factors ) at high resolution 19/21

Plume verification 20/21

21/21 Questions. Goal of such models: simulate very local intense micro-meteorological effects and pollution of wildfire for firefighters: on-demand crisis model. Why we need IBBI : Dataset of well studied fire events of use for emissions. Find some other use of fire propagation model for simulation of combustion dynamics. Find and include a better air pollution oriented chemistry model and verify it against observation data you may have. What we may do with IBBI : May help sub-mesh parameterization of global model by performing reference simulation of large wildfires (wich ones?). Use of High-Resolution models for parameterization of injection height? By model reduction? Study local impact of fire over pollution. Fire spread forecast. Current projects: 1 km 6h freq fuel model based on SURFEX with subgrid extrapolation (50m). Platform for prognostic fire size risk distribution based on large ensembles.

Young smoke plume: aircraft, drones, ground lidar / FTIR spectrometer, in-situ obs. The ideal experiment? Aged smoke plume: aircraft, airborne lidar / FTIR spectrometer / satellite Not the same chemistry! 22/21 Sources: Emission factors, burnt area, fire power Fuel characteristics

23/21

The FireFlux experiment 24/21 (Clements et al., 2010)

Fortunately, Meso-NH proved able to simulate such extreme conditions without any need to modify the physical algorithms (coupling by fluxes) 25/21

The FireFlux experiment 26/21 (Filippi et al., 2013)

The FireFlux experiment 27/21 (Filippi et al., 2013)

Transport and mixing of smoke plume: the LETIA 2010 experiment (Corsica) 28/21

A comparison between lidar and model 29/21

A comparison between lidar and model ForeFire/Meso-NH model set-up: 2 nested grids x = y =10m x = y= 40m Homogeneous fuel Heat flux: 155kW/m2 30/21

Trajectory and injection height Cancellieri et al., in NHESS 2013 31/21 Injection height explicitly resolved (3D turbulence scheme)

Chemical emissions from fires in the Euro-Med region: Emission factors Global estimates for temperate or extratropical forests (Andreae and Merlet, 2001; Agaki et al., 2011) Mediterranean vegetation type: resinuous, schrubland, eucalyptus, deciduous No detailed VOCs. (Miranda et al., 2004) Combustion chamber strong variation in the CO/CO2 ratio between kermes oak (<1), rosemary (1), cypress (3), eucalyptus (9). toward emission factors models (fuel composition, structure and burning conditions) 32/21 Burning in Corte! 2012

Chemical aging of polluted plumes: subgrid-scale chemistry Low resolution models will overestimate ozone production due to concentrated (sub-grid scale) sources! 33/21 O3 production O3 depletion Low resolution High resolution

Wildland-urban interface fires: signatures on air pollution The Lançon 2005 fire (600ha): O 3 depletion in Marseille AQ stations Smoke plumes at the surface 34/21 (Strada et al., 2012)

Application to Volcanoes Piton de la fournaise With P.Tulet, J. Durand Surface Fluxes over Lava, heat and C02 35/21

Volcanoes Piton de la fournaise With P.Tulet, J. Durand LaCy 36/21

Lava spread model Try it online : http://forefire.univ-corse.fr/lava 37/21

Fire and air pollution: from local to global scale 80 km x 80 km 50 m x 50 m 10 km x 10 km IBBI - Sources (dynamical emission factors, burnt area, ) - Plume dynamics (injection height: explicit vs. parameterized) - Subgrid-scale chemistry (ozone regime,...) 38/21

Sydney 17 october 39/21 (Modis 17/10/2013., 2012)

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Fire impact on air pollution: The Greek fires 2007 44/21 Turquety et al., 2009

From lidar signal to aerosol mass concentration Lidar backscattering radiation intensity by aerosols To derive aerosol mass concentrations from lidar signal: need for additional co-located simultaneous measurements (aerosols size distribution or mass concentration) Corte 2012 CO/CO2 BC ELPI (aerosol size distribution), particle counter, Nephelometer, aethalometer 45/21

GESTOSA field experiments of fire spread in shrub vegetation including smoke observation (Portugal: 1998, 1999, 2000, 2001 and 2002) NOx, CO, particulate matter (PM2.5, PM10), SO2, VOC 46/21 EU legislation Miranda et al. (2005)