scholarly journals Validation of coupled atmosphere-fire behavior models

1998 ◽  
Author(s):  
J.E. Bossert ◽  
J.M. Reisner ◽  
R.R. Linn ◽  
J.L. Winterkamp ◽  
R. Schaub ◽  
...  
Keyword(s):  
Fire Behavior ◽  
Behavior Models

scholarly journals 100 Years of Progress in Applied Meteorology. Part III: Additional Applications

2019 ◽  
Vol 59 ◽  
pp. 24.1-24.35 ◽  
Author(s):  
Sue Ellen Haupt ◽  
Branko Kosović ◽  
Scott W. McIntosh ◽  
Fei Chen ◽  
Kathleen Miller ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Food Security ◽  
Fire Behavior ◽  
Climate Information ◽  
Security Sector ◽  
Environmental System ◽  
Applied Meteorology ◽  
Agriculture And Food ◽  
Behavior Models

AbstractApplied meteorology is an important and rapidly growing field. This chapter concludes the three-chapter series of this monograph describing how meteorological information can be used to serve society’s needs while at the same time advancing our understanding of the basics of the science. This chapter continues along the lines of Part II of this series by discussing ways that meteorological and climate information can help to improve the output of the agriculture and food-security sector. It also discusses how agriculture alters climate and its long-term implications. It finally pulls together several of the applications discussed by treating the food–energy–water nexus. The remaining topics of this chapter are those that are advancing rapidly with more opportunities for observation and needs for prediction. The study of space weather is advancing our understanding of how the barrage of particles from other planetary bodies in the solar system impacts Earth’s atmosphere. Our ability to predict wildland fires by coupling atmospheric and fire-behavior models is beginning to impact decision-support systems for firefighters. Last, we examine how artificial intelligence is changing the way we predict, emulate, and optimize our meteorological variables and its potential to amplify our capabilities. Many of these advances are directly due to the rapid increase in observational data and computer power. The applications reviewed in this series of chapters are not comprehensive, but they will whet the reader’s appetite for learning more about how meteorology can make a concrete impact on the world’s population by enhancing access to resources, preserving the environment, and feeding back into a better understanding how the pieces of the environmental system interact.

Extrapolation Problems in Modeling Fire Effects at Large Spatial Scales: a Review

1996 ◽  
Vol 6 (4) ◽  
pp. 165 ◽  
Author(s):  
D Mckenzie ◽  
DL Peterson ◽  
E Alvarado
Keyword(s):  
Vegetation Change ◽  
Spatial Scales ◽  
Fire Behavior ◽  
Fire Effects ◽  
Ecological Effects ◽  
Challenging Problem ◽  
Landscape Disturbance ◽  
Level Data ◽  
Behavior Models ◽  
Single Approach

Models of vegetation change in response to global warming need to incorporate the effects of disturbance at broad spatial scales. Process-based predictive models, whether for fire behavior or fire effects on vegetation, assume homogeneity of crucial inputs over the spatial scale to which they are applied. Landscape disturbance models predict final burning patterns, but either do not model mechanistic behavior and explicit spread rates, or require large amounts of data to initialize simulations and predict ecological effects. Empirical data on the ecological effects of fire are not generally available at these scales, and conclusions are often extrapolated upward from stand-level data. Three methods for extrapolating ecological effects of fire across spatial scales and the sources of error associated with each were identified: (1) extrapolating fire behavior models directly to larger spatial scales; (2) integrating fire behavior and fire effects models with successional models at the stand level, then extrapolating upward; and (3) aggregating model inputs to the scale of interest. Extreme fire events present a challenging problem for modelers, regardless of which extrapolation method is employed. No single approach to modeling fire effects is inherently superior; modeling objectives and the characteristics of specific systems will determine the best strategy for each situation.

Using Simulated 3D Surface Fuelbeds and Terrestrial Laser Scan Data to Develop Inputs to Fire Behavior Models

2016 ◽  
Vol 42 (5) ◽  
pp. 443-459 ◽  
Author(s):  
Eric Rowell ◽  
E. Louise Loudermilk ◽  
Carl Seielstad ◽  
Joseph J. O’Brien
Keyword(s):  
Fire Behavior ◽  
3D Surface ◽  
Scan Data ◽  
Behavior Models

scholarly journals Integrating Fire Behavior Models and Geospatial Analysis for Wildland Fire Risk Assessment and Fuel Management Planning

2011 ◽  
Vol 2011 ◽  
pp. 1-19 ◽  
Author(s):  
Alan A. Ager ◽  
Nicole M. Vaillant ◽  
Mark A. Finney
Keyword(s):  
Risk Assessment ◽  
Wildland Fire ◽  
Fire Behavior ◽  
Fire Risk ◽  
Integrated System ◽  
Fuel Management ◽  
Management Planning ◽  
Fire Risk Assessment ◽  
Behavior Models ◽  
Wildland Fire Risk

Wildland fire risk assessment and fuel management planning on federal lands in the US are complex problems that require state-of-the-art fire behavior modeling and intensive geospatial analyses. Fuel management is a particularly complicated process where the benefits and potential impacts of fuel treatments must be demonstrated in the context of land management goals and public expectations. A number of fire behavior metrics, including fire spread, intensity, likelihood, and ecological risk must be analyzed for multiple treatment alternatives. The effect of treatments on wildfire impacts must be considered at multiple scales. The process is complicated by the lack of data integration among fire behavior models, and weak linkages to geographic information systems, corporate data, and desktop office software. This paper describes our efforts to build a streamlined fuel management planning and risk assessment framework, and an integrated system of tools for designing and testing fuel treatment programs on fire-prone wildlands.

Development of an advanced one-dimensional stem heating model for application in surface fires

2004 ◽  
Vol 34 (1) ◽  
pp. 20-30 ◽  
Author(s):  
Joshua L Jones ◽  
Brent W Webb ◽  
Dan Jimenez ◽  
James Reardon ◽  
Bret Butler
Keyword(s):  
Boundary Condition ◽  
Fire Behavior ◽  
Time Profile ◽  
Conduction Model ◽  
Prescribed Burns ◽  
One Dimensional ◽  
Mortality Models ◽  
Cell Mortality ◽  
Heating Model ◽  
Behavior Models

A new one-dimensional heat conduction model for predicting stem heating during fires is presented. The model makes use of moisture- and temperature-dependent thermal properties for layers of bark and wood. The thermal aspects of the processes of bark swelling, desiccation, and devolatilization are treated in an approximate fashion. An energy balance reveals that simulation with a heat flux input boundary condition requires that these phenomena be accounted for. Previous models have used temperature–time boundary conditions, which prevents them from being used in conjunction with fire behavior models. This model uses a flux–time profile for its boundary condition, making it possible to eventually couple it to fire behavior models. The model was developed and validated with laboratory experiments on Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) samples. It is intended that this model be used in conjunction with fire behavior and cell mortality models to make predictions of stem heating related mortality before prescribed burns.

Physical characteristics of shrub and conifer fuels for fire behavior models

2017 ◽  
Author(s):  
Jonathan R. Gallacher ◽  
Thomas H. Fletcher ◽  
Victoria Lansinger ◽  
Sydney Hansen ◽  
Taylor Ellsworth ◽  
...  
Keyword(s):  
Fire Behavior ◽  
Physical Characteristics ◽  
Behavior Models

Considerations for characterizing fuels as inputs for fire behavior models

2006 ◽  
Vol 227 (1-2) ◽  
pp. 102-114 ◽  
Author(s):  
Sonia A. Hall ◽  
Ingrid C. Burke
Keyword(s):  
Fire Behavior ◽  
Behavior Models

ANALYSIS OF EXPERIMENTAL DATA ON THE EFFECT OF BOTTOM VENTILATION CONDITIONS ON FIRE BEHAVIOR OVER A THERMALLY THIN NATURAL LATEX FOAM

2020 ◽  
Vol 51 (4) ◽  
pp. 359-376
Author(s):  
Dongmei Huang ◽  
Qi Yuan ◽  
Yu Wang ◽  
YiWei Hu ◽  
Yongliang Chen ◽  
...  
Keyword(s):  
Experimental Data ◽  
Fire Behavior ◽  
Ventilation Conditions
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