Forecasting the 10-hour timelag fuel moisture

by Michael A Fosberg

Publisher: Dept. of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station in Fort Collins, Colo

Written in English
Published: Pages: 10 Downloads: 819
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Subjects:

  • Wood -- Moisture

Edition Notes

StatementMichael A. Fosberg
SeriesUSDA Forest Service research paper RM -- 187
ContributionsRocky Mountain Forest and Range Experiment Station (Fort Collins, Colo.), United States. Forest Service
The Physical Object
Pagination10 p. :
Number of Pages10
ID Numbers
Open LibraryOL13602356M

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Forecasting the 10-hour timelag fuel moisture by Michael A Fosberg Download PDF EPUB FB2

Forecasting the hour timelag fuel moisture. Fort Collins, Colo.: Rocky Mountain Forest and Range Experiment Station, Forest Service, U.S. Dept. of Agriculture, (OCoLC) Forecasting the hour timelag fuel moisture (USDA Forest Service research paper RM) [Michael A Fosberg] on *FREE* Forecasting the 10-hour timelag fuel moisture book on qualifying : Michael A Fosberg.

A procedure for forecasting the hour timelag fuel moisture was developed from the theory of diffusion in wood. Studies of fuel moisture processes relating meteorological variables, as an external force, to moisture exchange processes in wood are combined here to provide a forecasting aid for the hour timelag fuel moisture.

Tables developed for field use were validated. Forecasting the hour timelag fuel moisture / Michael A. Fosberg. Derivation of the 1- and hour timelag fuel moisture calculations for fire-danger rating. Fort Collins, Colo.: Rocky Mountain Forest and Range Experiment Station, Forest Service, U.S.

Dept. of. The hour timelag fuel moisture is computed from mean daily temperatures and humidities and precipitation duration. Comparison of calculated and ob­ served fuel moistures showed good agreement.

Techniques to determine the seasonal starting value of the hour timelag fuel moisture are based on monthly climatological summaries. TheCited by: Buy Forecasting the hour timelag fuel moisture (USDA Forest Service research paper RM) by Michael A Fosberg (ISBN:) from Amazon's Book Store. Everyday low prices and free delivery on eligible : Michael A Fosberg.

We use cookies to offer you a better experience, personalize content, tailor advertising, provide social media features, and better understand the use of our services. Sponsor a Book. Moisture works Search for books with subject Moisture.

Search. Forecasting the hour timelag fuel moisture Michael A Fosberg Read. Publishing History This is a chart to show the publishing history of editions of works about this subject.

Along the X axis is time, and on the y axis is the count of editions published. For purposes of fire behavior modeling, dead fuels are divided into four “timelag” categories: 1-hour, hour, hour, and hour fuels. The shorter the timelag, the more responsive the fuel is to changing weather conditions.

Describes the evaluation of seven scales and meters used to determine the moisture content in hour fuel moisture sticks, (four connnected ponderosa pine dowels) that are used to estimate the moisture in hour dead fuels.

For optimal prescribed burning conditions, the moisture content of the hour fuel sticks should be from 8 to 17 percent. Dead fuel moisture responds solely to ambient environmental conditions and is critical in determining fire potential.

Dead fuel moistures are classed by timelag. A fuel's timelag is proportional to its diameter and is loosely defined as the time it takes a fuel particle to reach 2/3's of its way to. Dead fuel moisture is controlled solely by exposure to environmental conditions and is critical in determining fire potential.

Dead fuel moistures are classed by timelag. A fuel’s timelag is the time necessary for a fuel particle of a particular size to reach 63% of equilibrium between its initial moisture content and its current environment.

In Spring, loose-density areas of cm showed a dangerous level in fuel moisture after 6 days from rainfall, and in the case of cm or higher, it showed 50% or higher fuel moisture even. Forecasting the hour timelag fuel moisture Michael A Fosberg Read. Read. Read. Read. Read. Publishing History This is a chart to show the when this publisher published books.

Along the X axis is time, and on the y axis is the count of editions published. Accessible book, Ponderosa pine, Forest management. 10 Hour Fuel Moisture Map. Back To Fire Info. Weather Home About & Contact Guest Book. Current Time UTC PM Pacific PM Mountain PM Central PM Eastern.

Forecast provided by the National Weather Service. This weather data is. Forecast Burning Index Percentile. Forecast Hour FM Percentiles. Observed hour FM Percentiles. Nearly 40% of New Jersey land is considered forest, while about The forecast is made up of fire weather zones climatologically grouped by counties or zones throughout the forecast as well as an 8 to 14 day Outlook are also included.

10HR 10 hour timelag fuel moisture in percent valid at 13 LST (or trend + or -). moisture. The X is a function of the daily change in the hour timelag fuel moisture, and the average temperature.

Its purpose is to better relate the response of the live herbaceous fuel moisture model to the hour timelag fuel moisture value. The X value is designed to decrease at the same rate as the hour timelag fuelFile Size: 6MB.

An equilibrium in moisture content occurs when the net exchange of moisture between the fuel and the atmosphere is zero under constant temperature and relative humidity for an indefinite period of time [].M e varies more or less linearly with air temperature and sigmoidally with relative humidity.

It also depends on the direction of approach; it is higher in the direction of desorption than Cited by: 1. This banner text can have markup. web; books; video; audio; software; images; Toggle navigation. Caption titleDistributed to depository libraries in microfiche"July "Bibliography: p.

Wood -- Moisture. See also what's at your library, or elsewhere. Broader terms: Wood; Building materials -- Moisture; Moisture; Narrower term: Wood -- Moisture -- Measurement; Use.

Understanding the linkage between accumulated fuel dryness and temporal fire occurrence risk is key for improving decision-making in forest fire management, especially under growing conditions of vegetation stress associated with climate change.

This study addresses the development of models to predict the number of day observed Moderate-Resolution Imaging Spectroradiometer (MODIS) active Cited by: 3.

Hour Fuel Moisture (hr FM) represents the modeled moisture content in dead fuels in the 3 to 8 inch diameter class and the layer of the forest floor about four inches below the surface. The hr FM value is based on a running 7-day computed average using length of day, daily temperature and relative humidity extremes (maximum and.

A small company that manufactures special-order wood furniture has kept its employees busy on a 40 hour work schedule for the past two years. The company just received the largest contract in its history from a Saudi Arabian company, opening offices in the area.

All entries should be numeric and may be decimal if needed. Enter time values as hours; 6 minutes is 1/10 hour. Enter fuel values in gallons. The answers are returned as calculated values, based on your entries. Be sure to take into consideration highway winds, terrain, weather conditions, load, wait time and fuel for a margin of safety when.

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All books are in clear copy here, and all files are secure so don't worry about it. trol. Fuel moisture sticks that respond to weather changes like hour fuels are available. With a good set of scales and proper placement of the sticks, acceptable fuel moisture estimates can be obtained just before ignition.

These values will differ slightly from actual fine-fuel moistures, but are fairly represen-tative of most southern. Browsing subject area: Forest fires -- Oregon (Exclude extended shelves) You can also browse an alphabetical list from this subject or from.Paper on Forest fires.Design Derivation of a Shortwave Infrared Water Stress Index from MODIS near-and Shortwave Infrared Data in a Semiarid Environment, Remote Sensing of Environment, 87, pp.

– Fosberg, M. A., Deeming, J. E.,Derivation of the 1-and Hour Timelag Fuel Moisture Calculations for Fire-Danger Rating, Note RM, USDA Forest Service.