Data types - Revision history

Jmandel: /* References */

2019-02-02T02:50:03Z

References

← Older revision		Revision as of 02:50, 2 February 2019
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	* McKenzie, D., C.L. Raymond, L.-K.B. Kellogg, R.A. Norheim, A.G. Andreu, A.C. Bayard, K. E. Kopper, E. Elman, 2007. Canadian Journal of Forest Research. 37: 2421-2437.		* McKenzie, D., C.L. Raymond, L.-K.B. Kellogg, R.A. Norheim, A.G. Andreu, A.C. Bayard, K. E. Kopper, E. Elman, 2007. Canadian Journal of Forest Research. 37: 2421-2437.

			==See also==
			[https://www.youtube.com/watch?v=eulPPfwexaE JPSS video]

	[[Category:Data]]		[[Category:Data]]

Jmandel: wikified, feel free to rv

2010-07-11T02:42:26Z

wikified, feel free to rv

← Older revision		Revision as of 02:42, 11 July 2010
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	~~'''''•~~ Environmental factors~~'''''~~		==Environmental factors==

			===Weather===

	~~'''o Weather '''~~		*Surface data

			*Wind - All physically-based, empirical, or semi-empirical models of fire behavior will require an input of wind speed and direction for estimating fire rate of spread. The location of the wind measurement or model-derived quantity with respect to the fire line may vary.

	~~• Surface data~~		*Vertical profiles

	~~• Wind All physically-based~~, ~~empirical~~, ~~or semi-empirical~~ models of fire ~~behavior will require an input of wind speed and direction for estimating fire rate of spread~~. ~~The location~~ of the ~~wind measurement~~ or ~~model-derived quantity with respect to~~ the ~~fire line may vary~~.		*Because so much of atmospheric dynamics depends on the vertical structure of fields such as temperature, pressure, wind, and humidity, vertical profiles may be used to initialize the state of atmospheric models, assuming that this profile is representative of the fire environment. These may be obtained from atmospheric soundings (through the depth of the tropopause) or atmospheric profilers which emphasize the lowest levels of the atmosphere.

	~~• Vertical profiles~~		*3-dimensional atmospheric state

	~~• Because so much of atmospheric dynamics depends on the vertical structure of fields such as~~ temperature, pressure, wind, and ~~humidity, vertical profiles may be~~ used ~~to initialize~~ the state of ~~atmospheric models, assuming that this profile is representative of the fire environment~~. ~~These~~ may ~~be obtained~~ from ~~atmospheric soundings (through the depth~~ of ~~the tropopause) or atmospheric profilers which emphasize the lowest levels~~ of ~~the atmosphere~~.		*Air temperature, water vapor mixing ratio, air pressure, wind speed and direction – some of many variables used for initializing the three-dimensional state of a computational fluid dynamics model such as a weather model. Such physically consistent states may come from another computational fluid dynamics model or integrated analyses of many sources of data.

	~~• 3-dimensional atmospheric state~~		===Terrain===

	~~• Air temperature, water vapor mixing ratio, air pressure, wind speed and direction – some of many variables used for initializing the three~~-dimensional ~~state~~ of a ~~computational fluid dynamics model such as a weather~~ model. ~~Such physically consistent states may come from another computational fluid dynamics model or integrated analyses of many sources of data~~.		*A two-dimensional database of terrain elevation at a spatial resolution appropriate for the model. Users should take care that anomalies and errors have been removed.

			===Fuel===

	~~'''o Terrain~~ ~~'''~~		*Steady, extrinsic properties - This is complex because it is not simply the vegetation present but the part available for burning. In general, particularly kinematic model where relationships have been developed relating fire front rate of spread to fuel loads, it is meant to be the (fast burning) small-dimensioned components of a fuel complex that participate in the reactions in the fire front that carry the flaming front. More generally and particularly in dynamic models (i.e. ones where the forces of momentum created by heat release and air acceleration), it may include the larger fuel components. Reliable measurements of fuel are hard to come by, and may be based on hand measurements (which are limited by their representativeness), assignment of categorical fuel model classification (Anderson (1982), Scott and Burgan (2005), McKenzie et al. ) based on anticipated fire behavior, remotely sensed land surface data cross walked to a categorical fuel model classification system.

	~~• A two~~-~~dimensional database of terrain elevation at a spatial resolution appropriate for the model~~. ~~Users should take care that anomalies and errors have been removed.~~		*Fuel data is separated by vertical arrangement - ground fuel, surface fuel, and aerial (crown) fuel.

			*Transient properties. The fuel state (fuel moisture) of surface and aerial fuel may be diagnosed or predicted using information about the physical properties of the fuel and a trace of recent weather data including temperature, humidity, pressure, wind speed, precipitation, cloud cover, and solar radiation. While the smaller dead surface fuels respond over short term time scales to weather conditions, the live fuel moisture depends more on the health of the plant and therefore longer term conditions and stresses.

	~~'''o Fuel'''~~		==Fire data==

	~~• Steady, extrinsic properties - This is complex because it is~~ not ~~simply the vegetation present~~ but ~~the part available for burning. In general, particularly kinematic model where relationships have been developed relating fire front rate of spread to fuel loads, it is meant to~~ be ~~the (fast burning) small-dimensioned components of a fuel complex that participate in the reactions~~ in ~~the fire front that carry the flaming front~~. ~~More generally and particularly in dynamic~~ models ~~(i.e. ones where~~ the ~~forces~~ of ~~momentum created by heat release and air acceleration)~~, it may ~~include the larger fuel components. Reliable measurements~~ of ~~fuel are hard to come by~~, ~~and may be based on hand measurements (which are limited by their representativeness)~~, ~~assignment~~ of ~~categorical fuel model classification~~ (~~Anderson (1982~~)~~, Scott and Burgan (2005),~~ ~~McKenzie et al. ) based on anticipated~~ fire behavior, ~~remotely sensed land surface data cross walked to~~ a ~~categorical fuel model classification system~~.		===Time & location of ignition===
			* These are not routinely distributed in a digital form but may later be found in incident reports.
			*Currently, models begin at the time of ignition, which may be a point ignition, sequence of point ignitions, line ignition, or a line ignited over a period of time (as a person walking with a drip torch). It is recognized that differing ignition patterns may influence later fire behavior, thus models may include a wide variety of options here.

	~~• Fuel~~ data ~~is separated by vertical arrangement - ground fuel, surface fuel, and aerial (crown) fuel.~~		===Spatial data===

	~~• Transient properties. The fuel state (fuel moisture)~~ of ~~surface and aerial fuel may be diagnosed or predicted using information about~~ the ~~physical properties of~~ the ~~fuel and~~ a ~~trace of recent weather data including temperature~~, ~~humidity~~, ~~pressure~~, ~~wind speed~~, ~~precipitation, cloud cover, and solar radiation~~. ~~While~~ the ~~smaller dead surface fuels respond over short term time scales to weather conditions~~, the ~~live fuel moisture depends more on the health of the plant and therefore longer term conditions and stresses~~.		*Spatial data may include a two-dimensional map of the fire extent obtained by incident teams circling the fire with a GPS, aircraft-based imagery, unmanned aerospace vehicle, and (depending on the size and intensity of the fire and the satellite characteristics) satellite-based instruments, either polar-orbiting or geostationary. Fire remote sensing data often comes from instruments within the infrared range of the spectrum, since smoke frequently obscures the visible band.

			===Times series===

			*Times series of temperature produced by thermal sensors crossed by the fire.

	~~'''''• Fire data'''''~~		==References==

			* Anderson, H. E. 1982. ''Aids to determining fuel models for estimating fire behavior.'' USDA For. Serv. Gen. Tech. Rep. INT-122, 22p. lntermt. For. and Range Exp. Stn., Ogden, Utah 84401.
	~~'''o Time & location of ignition'''. These are not routinely distributed in a digital form but may later be found in incident reports.~~		* Scott, J. H. and R. E. Burgan. 2005. ''Standard fire behavior fuel models: a comprehensive set for use with Rothermel’s surface fire spread model.'' Gen. Tech. Rep. RMRS-GTR-153.Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 72 p.
			* McKenzie, D., C.L. Raymond, L.-K.B. Kellogg, R.A. Norheim, A.G. Andreu, A.C. Bayard, K. E. Kopper, E. Elman, 2007. Canadian Journal of Forest Research. 37: 2421-2437.
	• Currently, models begin at the time of ignition, which may be a point ignition, sequence of point ignitions, line ignition, or a line ignited over a period of time (as a person walking with a drip torch). It is recognized that differing ignition patterns may influence later fire behavior, thus models may include a wide variety of options here.


	'''o Spatial data''' may include a two-dimensional map of the fire extent obtained by incident teams circling the fire with a GPS, aircraft-based imagery, unmanned aerospace vehicle, and (depending on the size and intensity of the fire and the satellite characteristics) satellite-based instruments, either polar-orbiting or geostationary. Fire remote sensing data often comes from instruments within the infrared range of the spectrum, since smoke frequently obscures the visible band.


	~~'''o Times series''' of temperature produced by thermal sensors crossed by the fire.~~



	~~'''References'''~~

	Anderson, H. E. 1982. Aids to determining fuel models for estimating fire behavior. USDA For. Serv. Gen. Tech. Rep. INT-122, 22p. lntermt. For. and Range Exp. Stn., Ogden, Utah 84401.

	Scott, J. H. and R. E. Burgan. 2005. Standard fire behavior fuel models: a comprehensive set for use with Rothermel’s surface fire spread model. Gen. Tech. Rep. RMRS-GTR-153.Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 72 p.

	McKenzie, D., C.L. Raymond, L.-K.B. Kellogg, R.A. Norheim, A.G. Andreu, A.C. Bayard, K. E. Kopper, E. Elman, 2007. Canadian Journal of Forest Research. 37: 2421-2437.


	[[Category:Data]]		[[Category:Data]]

Janicec at 22:26, 9 July 2010

2010-07-09T22:26:23Z

← Older revision		Revision as of 22:26, 9 July 2010
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	• Because so much of atmospheric dynamics depends on the vertical structure of fields such as temperature, pressure, wind, and humidity, vertical profiles may be used to initialize the state of atmospheric models, assuming that this profile is representative of the fire environment. These may be obtained from atmospheric soundings (through the depth of the tropopause) or atmospheric profilers which emphasize the lowest levels of the atmosphere.		• Because so much of atmospheric dynamics depends on the vertical structure of fields such as temperature, pressure, wind, and humidity, vertical profiles may be used to initialize the state of atmospheric models, assuming that this profile is representative of the fire environment. These may be obtained from atmospheric soundings (through the depth of the tropopause) or atmospheric profilers which emphasize the lowest levels of the atmosphere.

	• 3-dimensional atmospheric state.		• 3-dimensional atmospheric state

	• Air temperature – ~~may be used as one~~ of many variables for initializing the three-dimensional state of a computational fluid dynamics model such as a weather model~~, along with air water vapor mixing ratio, air pressure, wind speed and direction~~. Such physically consistent states may come from another computational fluid dynamics model or integrated ~~analysis~~ of many sources of data.		• Air temperature, water vapor mixing ratio, air pressure, wind speed and direction – some of many variables used for initializing the three-dimensional state of a computational fluid dynamics model such as a weather model. Such physically consistent states may come from another computational fluid dynamics model or integrated analyses of many sources of data.

Jmandel: rm old S&D contents

2010-07-08T06:46:09Z

rm old S&D contents

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 '''''•	Environmental factors'''''
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 McKenzie, D., C.L. Raymond, L.-K.B. Kellogg, R.A. Norheim, A.G. Andreu, A.C. Bayard, K. E. Kopper, E. Elman, 2007.  Canadian Journal of Forest Research. 37: 2421-2437.
 [[Category:Data]]

Jmandel: moved Software & Data to Data types: mv to own page with a more descriptive title

2010-07-08T06:44:40Z

moved Software & Data to Data types: mv to own page with a more descriptive title

← Older revision	Revision as of 06:44, 8 July 2010
(No difference)

Jmandel: category

2010-07-04T04:59:44Z

Janicec at 22:53, 3 July 2010

2010-07-03T22:53:12Z

← Older revision		Revision as of 22:53, 3 July 2010
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			== '''Data Types''' ==



			'''''• Environmental factors'''''


			'''o Weather '''


			• Surface data

			• Wind All physically-based, empirical, or semi-empirical models of fire behavior will require an input of wind speed and direction for estimating fire rate of spread. The location of the wind measurement or model-derived quantity with respect to the fire line may vary.

			• Vertical profiles

			• Because so much of atmospheric dynamics depends on the vertical structure of fields such as temperature, pressure, wind, and humidity, vertical profiles may be used to initialize the state of atmospheric models, assuming that this profile is representative of the fire environment. These may be obtained from atmospheric soundings (through the depth of the tropopause) or atmospheric profilers which emphasize the lowest levels of the atmosphere.

			• 3-dimensional atmospheric state.

			• Air temperature – may be used as one of many variables for initializing the three-dimensional state of a computational fluid dynamics model such as a weather model, along with air water vapor mixing ratio, air pressure, wind speed and direction. Such physically consistent states may come from another computational fluid dynamics model or integrated analysis of many sources of data.


			'''o Terrain '''

			• A two-dimensional database of terrain elevation at a spatial resolution appropriate for the model. Users should take care that anomalies and errors have been removed.


			'''o Fuel'''

			• Steady, extrinsic properties - This is complex because it is not simply the vegetation present but the part available for burning. In general, particularly kinematic model where relationships have been developed relating fire front rate of spread to fuel loads, it is meant to be the (fast burning) small-dimensioned components of a fuel complex that participate in the reactions in the fire front that carry the flaming front. More generally and particularly in dynamic models (i.e. ones where the forces of momentum created by heat release and air acceleration), it may include the larger fuel components. Reliable measurements of fuel are hard to come by, and may be based on hand measurements (which are limited by their representativeness), assignment of categorical fuel model classification (Anderson (1982), Scott and Burgan (2005), McKenzie et al. ) based on anticipated fire behavior, remotely sensed land surface data cross walked to a categorical fuel model classification system.

			• Fuel data is separated by vertical arrangement - ground fuel, surface fuel, and aerial (crown) fuel.

			• Transient properties. The fuel state (fuel moisture) of surface and aerial fuel may be diagnosed or predicted using information about the physical properties of the fuel and a trace of recent weather data including temperature, humidity, pressure, wind speed, precipitation, cloud cover, and solar radiation. While the smaller dead surface fuels respond over short term time scales to weather conditions, the live fuel moisture depends more on the health of the plant and therefore longer term conditions and stresses.



			'''''• Fire data'''''


			'''o Time & location of ignition'''. These are not routinely distributed in a digital form but may later be found in incident reports.

			• Currently, models begin at the time of ignition, which may be a point ignition, sequence of point ignitions, line ignition, or a line ignited over a period of time (as a person walking with a drip torch). It is recognized that differing ignition patterns may influence later fire behavior, thus models may include a wide variety of options here.


			'''o Spatial data''' may include a two-dimensional map of the fire extent obtained by incident teams circling the fire with a GPS, aircraft-based imagery, unmanned aerospace vehicle, and (depending on the size and intensity of the fire and the satellite characteristics) satellite-based instruments, either polar-orbiting or geostationary. Fire remote sensing data often comes from instruments within the infrared range of the spectrum, since smoke frequently obscures the visible band.


			'''o Times series''' of temperature produced by thermal sensors crossed by the fire.



			'''References'''

			Anderson, H. E. 1982. Aids to determining fuel models for estimating fire behavior. USDA For. Serv. Gen. Tech. Rep. INT-122, 22p. lntermt. For. and Range Exp. Stn., Ogden, Utah 84401.

			Scott, J. H. and R. E. Burgan. 2005. Standard fire behavior fuel models: a comprehensive set for use with Rothermel’s surface fire spread model. Gen. Tech. Rep. RMRS-GTR-153.Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 72 p.

			McKenzie, D., C.L. Raymond, L.-K.B. Kellogg, R.A. Norheim, A.G. Andreu, A.C. Bayard, K. E. Kopper, E. Elman, 2007. Canadian Journal of Forest Research. 37: 2421-2437.





	* [[List of software]]		* [[List of software]]
	* [[List of data]]		* [[List of data]]

Jmandel at 19:16, 29 May 2010

2010-05-29T19:16:18Z

← Older revision	Revision as of 19:16, 29 May 2010
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		* [[List of software]]
		* [[List of data]]

Jmandel: Blanked the page

2010-05-29T19:15:32Z

Blanked the page

← Older revision		Revision as of 19:15, 29 May 2010
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	~~==Software==~~

	*[[WRF-Fire]]
	*[[VisTrails]]

	~~== Data ==~~

	*[[Fire Flux Dataset]]

	~~== [[List of howtos\|How To's]] ==~~

	* [[How to get WRF-Fire]]
	* [[How to run WRF-Fire]]
	* [[How to convert data for Geogrid]]
	* [[How to run WRF-Fire with real data]]
	* [[How to run the Supercomputing 2009 WRF-Fire/Vistrails demo]]

	~~==Documentation==~~

	*[[WRF-Fire documentation]]

	~~== See also==~~

	* [[List of software]]
	* [[List of data]]
	* [[List of WRF-Fire pages]]
	* [[List of howtos]]
	* [[List of documentation]]

	~~[[Category:Software]]~~
	~~[[Category:Data]]~~

Jmandel: /* See also */

2010-04-03T17:42:36Z

← Older revision		Revision as of 04:59, 4 July 2010
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			==See also==

	* [[List of software]]		* [[List of software]]
	* [[List of data]]		* [[List of data]]

			[[Category:Data]]

← Older revision		Revision as of 17:42, 3 April 2010
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	* [[List of software]]		* [[List of software]]
	* [[List of data]]		* [[List of data]]
	* List of [[WRF-Fire pages]]		* [[List of WRF-Fire pages]]
	* [[List of howtos]]		* [[List of howtos]]
	* [[List of documentation]]		* [[List of documentation]]