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7 - Wind and Canopies

Published online by Cambridge University Press:  16 June 2022

Kevin Speer
Affiliation:
Florida State University
Scott Goodrick
Affiliation:
US Forest Service
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Summary

This chapter aims to summarize current knowledge regarding the fluid dynamics of wind in canopies and to emphasize aspects that are the most relevant in the context of forest fires. We describe the main characteristics of wind flows in the lower part of the boundary layer, starting from the main features in homogeneous canopies, including velocity and turbulence profiles and characteristics of turbulent structures. Then we address two specific cases of heterogeneous canopies, the clearing-to-forest and the forest-to-clearing transitions, which have been extensively studied. The next section is dedicated to wind flow modeling and how such modeling is used in fire models. Finally, special focus is placed on wind measurement in the context of fire experiments. In this chapter, the feedbacks of fire on wind, as well as atmospheric stability, are not addressed. More information on these topics can be found in Chapters 4 and 8, respectively.

Type
Chapter
Information
Wildland Fire Dynamics
Fire Effects and Behavior from a Fluid Dynamics Perspective
, pp. 183 - 208
Publisher: Cambridge University Press
Print publication year: 2022

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References

Albini, FA (1985) A model for fire spread in wildland fuels by-radiation. Combustion Science and Technology 42(5–6), 229258.CrossRefGoogle Scholar
Albini, FA, Baughman, RG (1979) Intermountain Forest and Range Experiment Station (Ogden, Utah) (1979) “Estimating windspeeds for predicting wildland fire behavior.” Research report, Intermountain Forest and Range Experiment Station, Forest Service, U.S. Dept. of Agriculture: Ogden, UT.Google Scholar
Andrews, PL (1986) BEHAVE: Fire behavior prediction and fuel modeling system-BURN Subsystem, part 1 (No. INT-GTR-194). Research Report, U.S. Department of Agriculture, Forest Service, Intermountain Research Station, Ogden, UT.CrossRefGoogle Scholar
Andrews, PL (2012) Modeling wind adjustment factor and midflame wind speed for Rothermel’s surface fire spread model. Ft. Collins, CO: United States Department of Agriculture/Forest Service, Rocky Mountain Research Station.CrossRefGoogle Scholar
Baines, PG (1990) Physical mechanisms for the propagation of surface fires. Mathematical and Computer Modelling 13(12), 8394.Google Scholar
Béland, M, Widlowski, J-L, Fournier, RA, Côté, J-F, Verstraete, MM (2011) Estimating leaf area distribution in savanna trees from terrestrial LiDAR measurements. Agricultural and Forest Meteorology 151(9), 12521266.CrossRefGoogle Scholar
Cassagne, N, Pimont, F, Dupuy, J-L, Linn, RR, Mårell, A, Oliveri, C, Rigolot, E (2011) Using a fire propagation model to assess the efficiency of prescribed burning in reducing the fire hazard. Ecological Modelling 222(8), 15021514.Google Scholar
Catchpole, WR, Catchpole, EA, Butler, BW, Rothermel, RC, Morris, GA, Latham, DJ (1998) Rate of spread of free-burning fires in woody fuels in a wind tunnel. Combustion Science and Technology 131(1–6), 137.CrossRefGoogle Scholar
Cheney, NP, Gould, JS, Catchpole, WR (1998) Prediction of fire spread in grasslands. International Journal of Wildland Fire 8(1), 113.CrossRefGoogle Scholar
Cionco, RM (1965) A mathematical model for air flow in a vegetative canopy. Journal of Applied Meteorology 4, 517522.2.0.CO;2>CrossRefGoogle Scholar
Cruz, MG, Alexander, ME (2013) Uncertainty associated with model predictions of surface and crown fire rates of spread. Environmental Modelling & Software 47, 1628.CrossRefGoogle Scholar
Cruz, MG, Alexander, ME, Wakimoto, RH (2005) Development and testing of models for predicting crown fire rate of spread in conifer forest stands. Canadian Journal of Forest Research 35(7), 16261639.CrossRefGoogle Scholar
Deardorff, JW (1980) Stratocumulus-capped mixed layers derived from a three-dimensional model. Boundary-Layer Meteorology 18(4), 495527.Google Scholar
Dupont, S, Bonnefond, J-M, Irvine, MR, Lamaud, E, Brunet, Y (2011) Long-distance edge effects in a pine forest with a deep and sparse trunk space: In situ and numerical experiments. Agricultural and Forest Meteorology 151(3), 328344.Google Scholar
Dupont, S, Brunet, Y (2008) Edge flow and canopy structure: A large-eddy simulation study. Boundary-Layer Meteorology 126(1), 5171.CrossRefGoogle Scholar
Dupont, S, Brunet, Y (2009) Coherent structures in canopy edge flow: A large-eddy simulation study. Journal of Fluid Mechanics 630, 93128.CrossRefGoogle Scholar
Dupont, S, Gosselin, F, Py, C, De Langre, E, Hemon, P, Brunet, Y (2010) Modelling waving crops using large-eddy simulation: comparison with experiments and a linear stability analysis. Journal of Fluid Mechanics 652, 544.Google Scholar
Dupuy, J-L, Pimont, F, Linn, R, Clements, C (2014) FIRETEC evaluation against the FireFlux experiment: preliminary results. In: Viegas, DX, ed., Advances in Forest Fire Research. Coimbra: Imprensa da Universidade de Coimbra, pp. 261274.Google Scholar
Finnigan, J (2000) Turbulence in plant canopies. Annual Review of Fluid Mechanics 32(1), 519571.CrossRefGoogle Scholar
Fischer, WC, Hardy, CE (1976) Fire–weather observers’ handbook. Agricultural Handbook, vol. 494. Washington, DC: USDA Forest Service.Google Scholar
Foudhil, H, Brunet, Y, Caltagirone, JP (2005) A fine-scale k-e model for atmospheric flow over heterogeneous landscapes. Environmental Fluid Mechanics 5(3), 247265.CrossRefGoogle Scholar
Frangieh, N, Morvan, D, Meradji, S, Accary, G, Bessonov, O (2018) Numerical simulation of grassland fires behavior using an implicit physical multiphase model. Fire Safety Journal 102, 3747.CrossRefGoogle Scholar
Gao, W, Shaw, RH, Paw, UKT (1989) Observation of organised structures in turbulent flow within and above a forest canopy. Boundary-Layer Meteorology 47(1), 349377.CrossRefGoogle Scholar
Hernandez, C, Keribin, C, Drobinski, P, Turquety, S (2015) Statistical modelling of wildfire size and intensity: A step toward meteorological forecasting of summer extreme fire risk. Annales Geophysicae 33(12), 14951506.Google Scholar
Holton, JR, Hakim, GJ (2012) An Introduction to Dynamic Meteorology, 5th ed. Amsterdam: Academic Press.Google Scholar
Kaimal, JC, Finnigan, JJ (1994) Atmospheric Boundary Layer Flows: Their Structure and Measurement. New York: Oxford University Press.Google Scholar
Katul, G (1998) An investigation of higher-order closure models for a forested canopy. Boundary-Layer Meteorology 89(1), 4774.Google Scholar
Kiefer, MT, Zhong, S, Heilman, WE, Charney, JJ, Bian, X (2013) Evaluation of an ARPS-based canopy flow modeling system for use in future operational smoke prediction efforts: ARPS-CANOPY EVALUATION. Journal of Geophysical Research: Atmospheres 118(12), 61756188.Google Scholar
Lee, X (2000) Air motion within and above forest vegetation in non-ideal conditions. Forest Ecology and Management 135(1–3), 318.Google Scholar
Li, Z, Lin, JD, Miller, DR (1990) Air flow over and through a forest edge: A steady state numerical simulation. Boundary Layer and Meteorology 51(1), 179197.CrossRefGoogle Scholar
Linn, R, Anderson, K, Winterkamp, J, Brooks, A, Wotton, M, Dupuy, J-L, Pimont, F, Edminster, C (2012) Incorporating field wind data into FIRETEC simulations of the International Crown Fire Modeling Experiment (ICFME): Preliminary lessons learned. Canadian Journal of Forest Research 42(5), 879898.Google Scholar
Linn, RR, Cunningham, P (2005) Numerical simulations of grass fires using a coupled atmosphere–fire model: Basic fire behavior and dependence on wind speed. Journal of Geophysical Research 110(D13), D13107.CrossRefGoogle Scholar
Liu, J, Chen, JM, Black, TA, Novak, MD (1996) E-e modelling of turbulent air flow downwind of a model forest edge. Boundary-Layer Meteorology 77(1), 2144.Google Scholar
Lu, C-H, Fitzjarrald, DR (1994) Seasonal and diurnal variations of coherent structures over a deciduous forest. Boundary-Layer Meteorology 69(1–2), 4369.CrossRefGoogle Scholar
Massman, WJ, Forthofer, JM, Finney, MA (2017) An improved canopy wind model for predicting wind adjustment factors and wildland fire behavior. Canadian Journal of Forest Research 47(5), 594603.Google Scholar
Moon, K, Duff, TJ, Tolhurst, KG (2019) Sub-canopy forest winds: understanding wind profiles for fire behaviour simulation. Fire Safety Journal 105, 320329.CrossRefGoogle Scholar
Morvan, D, Dupuy, JL (2001) Modeling of fire spread through a forest fuel bed using a multiphase formulation. Combustion and Flame 127(1), 19811994.CrossRefGoogle Scholar
Mueller, E, Mell, W, Simeoni, A (2014) Large eddy simulation of forest canopy flow for wildland fire modeling. Canadian Journal of Forest Research 44(12), 15341544.CrossRefGoogle Scholar
Parsons, RA, Linn, RR, Pimont, F, Hoffman, C, Sauer, J, Winterkamp, J, Sieg, CH, Jolly, WM (2017) Numerical investigation of aggregated fuel spatial pattern impacts on fire behavior. Land 6(2), 43.CrossRefGoogle Scholar
Parsons, RA, Pimont, F, Wells, L, Cohn, G, Jolly, WM, de Coligny, F, Rigolot, E, Dupuy, J-L, Mell, W, Linn, RR (2018) Modeling thinning effects on fire behavior with STANDFIRE. Annals of Forest Science 75(1), 110.Google Scholar
Patton, EG (1997) Large-Eddy Simulation of Turbulent Flow above and within a Plant Canopy. PhD Dissertation. University of California, Davis, CA.Google Scholar
Patton, EG, Shaw, RH, Judd, MJ, Raupach, MR (1998) Large-eddy simulation of windbreak flow. Boundary-Layer Meteorology 87(2), 275307.Google Scholar
Pimont, F (2008) Modélisation physique de la propagation des feux de forêts: effets des caractéristiques physiques du combustible et de son hétérogénéité. PhD Dissertation. Université d’Aix-Marseille II.Google Scholar
Pimont, F, Dupuy, J-L, Linn, RR (2014) Fire effects on the physical environment in the WUI using FIRETEC. In: Viegas, DX, ed., Advances in Forest Fire Research. Coimbra: Imprensa da Universidade de Coimbra, pp. 749758.Google Scholar
Pimont, F, Dupuy, J-L, Linn, RR, Dupont, S (2009) Validation of FIRETEC wind-flows over a canopy and a fuel-break. International Journal of Wildland Fire 18(7), 775.CrossRefGoogle Scholar
Pimont, F, Dupuy, J-L, Linn, RR, Dupont, S (2011) Impacts of tree canopy structure on wind flows and fire propagation simulated with FIRETEC. Annals of Forest Science 68(3), 523530.Google Scholar
Pimont, F, Dupuy, J-L, Linn, RR, Parsons, R (2018) Wind measurement accuracy in fire experiments. In: Viegas, DX, ed., Advances in Forest Fire Research. Coimbra: Imprensa da Universidade de Coimbra, pp. 716724.Google Scholar
Pimont, F, Dupuy, J-L, Linn, RR, Parsons, R, Martin-StPaul, N (2017) Representativeness of wind measurements in fire experiments: Lessons learned from large-eddy simulations in a homogeneous forest. Agricultural and Forest Meteorology 232, 479488.Google Scholar
Pimont, F, Dupuy, J-L, Linn, RR, Sauer, JA, Muñoz-Esparza, D (2020) Pressure-gradient forcing methods for large-eddy simulations of flows in the lower atmospheric boundary layerAtmosphere 11(12), 1343.Google Scholar
Pimont, F, Dupuy, J-L, Rigolot, E, Prat, V, Piboule, A (2015) Estimating leaf bulk density distribution in a tree canopy using terrestrial LiDAR and a straightforward calibration procedure. Remote Sensing 7(6), 79958018.CrossRefGoogle Scholar
Pimont, F, Parsons, R, Rigolot, E, de Coligny, F, Dupuy, J-L, Dreyfus, P, Linn, RR (2016) Modeling fuels and fire effects in 3D: Model description and applications. Environmental Modelling & Software 80, 225244.Google Scholar
Pimont, F, Ruffault, J, Martin-StPaul, NK, Dupuy, J-L (2019) Why is the effect of live fuel moisture content on fire rate of spread underestimated in field experiments in shrublands? International Journal of Wildland Fire 28(2), 127.Google Scholar
Poggi, D, Porporato, A, Ridolfi, L, Albertson, JD, Katul, GG (2004) The effect of vegetation density on canopy sub-layer turbulence. Boundary-Layer Meteorology 111(3), 565587.Google Scholar
Pope, SB (2000) Turbulent Flows. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Raupach, MR (1994) Simplified expressions for vegetation roughness length and zero-plane displacement as functions of canopy height and area index. Boundary-Layer Meteorology 71, 211216.Google Scholar
Raupach, MR (1995) Corrigenda. Boundary-Layer Meteorology 76(1–2), 303304.Google Scholar
Raupach, MR, Finnigan, JJ, Brunei, Y (1996) Coherent eddies and turbulence in vegetation canopies: The mixing-layer analogy. Boundary-Layer Meteorology 78, 351382.Google Scholar
Rothermel, RC (1972) A Mathematical Model for Predicting Fire Spread in Wildland Fuels. Research Paper INT-115. Ogden, UT: U.S. Department of Agriculture, Intermountain Forest and Range Experiment Station.Google Scholar
Shaw, RH, Brunet, Y, Finnigan, JJ, Raupach, MR (1995) A wind tunnel study of air flow in waving wheat: Two-point velocity statistics. Boundary-Layer Meteorology 76(4), 349376.Google Scholar
Shaw, RH, Patton, EG (2003) Canopy element influences on resolved- and subgrid-scale energy within a large-eddy simulation. Agricultural and Forest Meteorology 115(1–2), 517.Google Scholar
Shaw, RH, Schumann, U (1992) Large-eddy simulation of turbulent flow above and within a forest. Boundary-Layer Meteorology 61(1–2), 4764.Google Scholar
Smith, F, Carson, D, Oliver, H (1972) Mean wind-direction shear through a forest canopy. Boundary-Layer Meteorology 3(2), 178190.Google Scholar
Stull, RB (1988) An Introduction to Boundary Layer Meteorology. Fordrecht, The Netherlands: Kluwer Academic Publishers:Google Scholar
Su, H-B, Shaw, RH, Paw, KT, Moeng, C-H, Sullivan, PP (1998) Turbulent statistics of neutrally stratified flow within and above a sparse forest from large-eddy simulation and field observations. Boundary-Layer Meteorology 88(3), 363397.Google Scholar
Sullivan, AL, Knight, IK (2001) Estimating error in wind speed measurements for experimental fires. Canadian Journal of Forest Research 31(3), 401409.Google Scholar
Taylor, SW, Wotton, BM, Alexander, ME, Dalrymple, GN (2004) Variation in wind and crown fire behaviour in a northern jack pine black spruce forest. Canadian Journal of Forest Research 34(8), 15611576.CrossRefGoogle Scholar
Tieszen, SR (2001) On the fluid mechanics of fires. Annual Review of Fluid Mechanics 33(1), 6792.Google Scholar
Turner, MG, Romme, WH (1994) Landscape dynamics in crown fire ecosystems. Landscape Ecology 9(1), 5977.Google Scholar
Van der Hoven, I (1957) Power spectrum of horizontal wind speed in the frequency range from 0.0007 to 900 cycles per hour. Journal of Meteorology 14(2), 160164.Google Scholar
Van Wagner, CE (1977) Conditions for the start and spread of crown fire. Canadian Journal of Forest Research 7(1), 2334.Google Scholar

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