Wildfire By Chi Chau and Matt McKnight
Problems • In 2000 alone, wildfires were responsible for an estimated $10 billion in damages • Firefighter safety • Loss of Biomass • Wildlife habitat • National Parks • Smoke, air pollution, fires destroy ground cover resulting in soil erosion and mudslides when it rains. • Long term effects on the environment • Global Warming • CO2 is produce when plants burn effect global warming
Nature of wildfires • Reduce fuel buildup and help prevent even bigger fires • Improve soils for healthier trees • Cycle of nature
Interesting facts • Fire and atmosphere influence each other significantly • Scientists have found that a wildfire’s shape starts out the same everywhere in the world
Modeling • Simulators have been around for half a century starting with simple solvers on simple hardware • The goal has always been to produce the most accurate predictions using the most current data. • It is obvious that atmospheric conditions are inextricably linked to wildfire behavior. • The atmospheric-wildfire model becomes the standard of simulation • As it turns out, changing heat from the fire feeds back to the atmosphere producing “fire winds”, while already occurring winds are feeding the fire.
Data • Fire location • Temperature • Direction of spread • Weather data • Wind • When will it RAIN?? • Fuel • Rate of burn • Topological information • Elevation • Slope • Aerial photography • Map Information • Towns • Roads • Forested/Non Forested lines
Atmospheric Modeling • “The Fifth-Generation NCAR / Penn State Mesoscale Model (MM5) is the latest in a series that developed from a mesoscale model used by Anthes at Penn State in the early 70's that was later documented by Anthes and Warner (1978). Since that time, it has undergone many changes designed to broaden its usage. These include • a multiple-nest capability, • nonhydrostatic dynamics, which allows the model to be used at a few-kilometer scale • multitasking capability on shared- and distributed-memory machines • a four-dimensional data-assimilation capability, and • more physics options. “
Wind and Slope • As wind feeds a fire, the fire creates wind of it’s own. These winds can be very high speed (20 – 30 m/s) • Burning embers • A Fire’s flanks might split and burn separately • The Fire moves uphill much faster than downhill • Changes in wind and slope affect the behavior of your model
Wildfire model in action • Here is the model shows a fire’s shape and behavior
What does the model show? • Assume the model is on a perfectly flat land, the arrows at the bottom of the box represent the wind, blowing from left to right.
Fire model cont • Next, let’s say the fire suddenly ignites for whatever reason. The fire quickly takes on the shape of a triangle and the hottest spot is its head. Due to the wind (remember the arrow represent the wind) blowing from left to right it push the fire forward. The fire’s sides are parallel to the wind. The flames creep slowly against the wind.
Wildfire model cont • The combustion of tress and grasses releases intense heat and quickly warms the atmosphere. Since the hot air rises, forming powerful updraft winds. More air is drawn into the fire from all directions.
Wildfire model cont • Watch out! • After certain time, the fire leaps forward into new fuels and the fire’s path is widened. • At this point, the wildfire is changing weather that is already there • As known as phenomenon wildfire weather. • Good for BBQ !
How is the model useful? • Computer model help us understand interesting and erratic fire behaviors. • Help us evaluate the threats and benefits of wildfires
Linking fire and atmosphere model • Coupled Atmosphere-Fire Model by Clark
Coupled Atmosphere-Fire Model • Winds play a critical role in fire spread, so by combining Atmosphere and Fire model it gives us a good prediction. • “Forest fires (wildfire) are very complex phenomena … Interactions between forest fires and airflow are highly nonlinear, unstable and their radiation and combustion properties are not fully understood” said Clark.
Atmosphere-Fire model cont • The model helps to explain a commonly observed trait of wind-driven fires, the growth of fingers of flame, space about a kilometer apart which form the main fire line. • Previous research (w/o the model) proposed that he fingering was due to variations in either the fire’s fuel or the local geography. • But, the model suggests that when winds are weak, a fire line several km or more in length inherently unstable and very likely to break up into fingers.
Massive computing • Using OpenMP or multigrid we can make the solver very fast as well as running multiple independent simulations on single nodes • Now many users at different areas of the fire have access to individual decision-making tools.
Continued • Smoke can obscure ‘naked-eye’ observations but can be overcome by infrared sensitive video • Aerial photography can bring accurate information from rough terrain that might be inaccessible. • Autonomous detectors • When they stop transmitting, you’ve found the fireline. • Can also contain other sensors
References http://box.mmm.ucar.edu/fire/model/model_whyc.html http://www.mmm.ucar.edu/mm5/overview.html http://www-math.cudenver.edu/~jmandel/fires/Fires-Kluwer.pdf http://www.ucar.edu/educ_outreach/wildfire/model.htm http://box.mmm.ucar.edu/fire/model/model_home.html http://www.scd.ucar.edu/info/SC96/FIRE/FireExhibit.html