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Main Collaborators: Janice Coen, NCAR Morwenna Griffiths,Monash Mary Ann Jenkins,York Don Latham, USFS Don Middleton,NC

Coupled Fire-Atmosphere Research Observations and Modeling. by Terry L. Clark/UBC. Main Collaborators: Janice Coen, NCAR Morwenna Griffiths,Monash Mary Ann Jenkins,York Don Latham, USFS Don Middleton,NCAR David Packham, BoM Larry Radke,NCAR/RI Michael Reeder,Monash Roland Stull, UBC.

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Main Collaborators: Janice Coen, NCAR Morwenna Griffiths,Monash Mary Ann Jenkins,York Don Latham, USFS Don Middleton,NC

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  1. Coupled Fire-Atmosphere Research Observations and Modeling by Terry L. Clark/UBC Main Collaborators: Janice Coen, NCAR Morwenna Griffiths,Monash Mary Ann Jenkins,York Don Latham, USFS Don Middleton,NCAR David Packham, BoM Larry Radke,NCAR/RI Michael Reeder,Monash Roland Stull, UBC

  2. OUTLINE • Observations using IR Imagery • -overview of IR camera and analysis techniques • -some prescribed and wild fire field experiments • Model • -Description of dynamic code • -Description of early NCAR fire code • -some results • -Description of current WFIS fire code • -some results

  3. OBSERVATIONS AND InfraRed Image ANALYSIS

  4. Onion sage brush fire in Owensvalley, Ca 1985 courtesy of C. George

  5. Street Patterns observed in Fires Photo courtesy Brenner -observed in Florida

  6. OBSERVATIONS • Infrared Camera • Inframetrics PM380 • 3 to 5 mm • 256 by 256 array • Sterling cooler • 16 deg lens gives 1.4 mrad resolution per pixel

  7. Image Flow Analysis Applications • Understand fire behavior • Calculate combustion zone winds and their statistics • Use derived data to validate numerical models

  8. Image Flow Analysis Assumptions • IR camera sees incandescent soot particles • Motion is on a distorted two-dimensional surface • Local features can be followed for short periods • We can fit data to simple types of motions, i.e. translation, rotation, dilation and shear ..

  9. Image Registration • 1. Reduce image resolution (e.g. 7:1 in x and 5:1 in y) • 2. Align image using IR intensity center of mass • 3. Refine alignment using correlation analysis • = S (fn+1(x + Dx, y +Dy) - fn(x,y))2 Minimize L to estimate Dxand Dy. 4. Extract linear trends in Dx (t) and Dy(t). • 5. Registered IR images: • - used in image flow analysis to estimate winds within the combustion zone

  10. Image Flow Analysis Gradient Approach (Helmholtz theorem): Two-dimensional motions can be represented as the sum of six components. Translation .. Rotation Uniform expansion And two shear componentswhich most researchers ignore.

  11. Robust Statistics Using the two components of translation, we obtain the matrix equation which we solve at each pixel for u and w. If |u2 + w2| > S2 then we flag that pixel as an outlier and avoid considering it in future calculations. Typically, S= 20 to 40 m/s.

  12. Least Squares Minimization After identifying outliers we sum over a patch of data as We typically use 7 by 7 pixels. Outlier points are not included in any of the summations. This simplest approach requires the inversion of a second order matrix to estimate u and w. .

  13. International Crown Fire Modelling Exp • Canadian and US Forest Services • Near Fort Providence NWT Canada • Prescribed crown fires • 150 by 150 m plots • June – July 1997 • Tower based IR • measurements • Plot 6–9 July 1997 Cameras on 50ft tower

  14. Workshop at the Site

  15. Plot 5 Fire Whirl

  16. Plot 6 Ignition

  17. Plot 6 at 2:08

  18. Plot 6 at 2:09

  19. Plot 6 at 2:10

  20. Plot 6 at 2:10 plus

  21. Plot 6 at 2:11

  22. Turbulent Burst Sequence

  23. Video: Plot 6 Visual

  24. Derived Winds for file=7004

  25. Fig 10a Clark et al. 1999, JAM

  26. Wild Fire Experiment • NCAR • Sept 1998, Montana, Colorado and California • Infrared Camera mounted on NSF/NCAR C-130 • Wildfires were the target of opportunity • First case was in Glacier National Park -Challenge Fire Complex 4 Sept 98 -100 m long hairpin vortex observed with IR -fire about 2 km away from camera

  27. IR Imagery from C-130FOD - Part II Finger shot out about 100 m in 1-2 sec Indications of burning fuel after finger retreats Hairpin or Turbulent Burst

  28. Video: IR Observations over Glacier National Park - 4 Sept 1998

  29. Northern Territory Grass Fire Experiment- Australia • Spear grass burns 40 km South of Darwin • Kerosene grass burns near Batchelor • Used 19 m high cherry-picker as platform • Platform motion requires apparent motion treatment

  30. Cherry Picker

  31. Fuel Type - Australian Spear Grass (Sorgum_Intrans)

  32. Litchfield Kerosene Grass (19 m up)

  33. Video: IR Data Hughes plot 3 Camera @ 200 m from fire giving @ 30 cm pixels

  34. Video: Unprocessed Images Plot-3a Hughes Airfield

  35. Video: Fire Winds using least squareswith registration

  36. Velocity Statistics – Least Squares

  37. MODELING

  38. Numerical Model • 3D Non-hydrostatic 2nd order finite-differences • Terrain following - geo-spherical coordinates • Vertical and horizontal grid refinement – 2-way interaction • Vertically stretched grids with grid refinement • - Clark (1977,JCP), Clark-Farley(1984,JAS), • Clark-Hall(1991,JCP; 1996,JAM) • Boundary-Initial conditions from NWP • Bulk parameterizations of rain/ice processes -Kessler (rain), Murray-Koenig (ice) and much more recent approaches under development.

  39. Coordinates Horizontal Coordinates Vertically Stretched Coordinates

  40. Multi-Processing Approach Message Passing Interface (MPI) software is used for multi-processing.

  41. Model Configuration for 3 LayersNVRT=0 (no tiling) Single Processor framework N=3 N=2 N=1

  42. Multi-Processing Configuration for 3 LayersNVRT=1(with tiling)Layer 1 details Multi-processor Framework Four sub-domains per layer MCPU=4 Green= lmx1,lmx2 lmy1,lmy2 N=3 N=4 Blue=mi2mo N=1 N=2

  43. Grid Refinement Using 5 Domains Example from Clark et al. 2000, JAS Grid size ranges from 26 km to 200 m (4:1 4:1 4:1 2:1) CO

  44. DOMAIN 5 OROGRAPHY Example from Clark et al. 2000, JAS

  45. Wildfire Modeling

  46. Rational for Wildfire Modeling • Wildfire propagation physics is poorly understood • FS spread models use empirical fits from • Low intensity small fires • Laboratory fire tunnels • Neither can hope to represent the vast parameter space of intense fires • Understanding fire behavior involves • Combustion winds interacting with the fire and ambient flow • Fire-atmosphere heat exchange • Fire-fuel heat exchange • Chemical release and transport by the convection • Some Applications of Coupled Fire-Atmosphere Models • Study burn paradigms • Understand fire related sources/sinks to atmospheric budgets • Develop suppression techniques • Like the NWP problem, fires are too non-linear to predict using empirically derived rule based techniques, i.e. there is no empirical fit to a severe nonlinear event.

  47. NCAR FIRE CODE -Physical treatment of fire at a very ‘first cut’ level, i.e. useful for preliminary evaluation.

  48. Fire Atmosphere Coupling The sensible and latent heat fluxes were added to the vertical diffusion terms as: Where Fs and Fiare the heat and moisture inputs from the fire. Fs can reach values up to 1-3 MW m-2. . Where as and al are extinction lengths for the sensible and latent heat fluxes.

  49. Spread Rate Treatment BEHAVE formulation fs is the slope coefficient is the wind coefficient is the wind normal to the fire front R0 depends on fuel type and moisture content. A BURNUP type curve is used to describe the rate of mass loss for each fuel cell. • Strong need for improved spread rate • parametrizations appropriate for coupled • fire-atmosphere models

  50. Fire Line Propagation Scheme • Contour advection scheme • Avoids assuming shape such as ellipse • We want the physics to determine shape

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