Application of the Nelson model to four timelag fuel classes using Oklahoma field observations: model evaluation and comparison with National Fire Danger Rating System algorithms

2007 ◽  
Vol 16 (2) ◽  
pp. 204 ◽  
Author(s):  
J. D. Carlson ◽  
Larry S. Bradshaw ◽  
Ralph M. Nelson ◽  
Randall R. Bensch ◽  
Rafal Jabrzemski
Keyword(s):  
Fire Danger ◽  
Rating System ◽  
Field Observations ◽  
Fuel Moisture ◽  
Next Generation ◽  
Nelson Model ◽  
Weather Information ◽  
Weather Observations ◽  
Fire Danger Rating System ◽  
Better Than

The application of a next-generation dead-fuel moisture model, the ‘Nelson model’, to four timelag fuel classes using an extensive 21-month dataset of dead-fuel moisture observations is described. Developed by Ralph Nelson in the 1990s, the Nelson model is a dead-fuel moisture model designed to take advantage of frequent automated weather observations. Originally developed for 10-h fuels, the model is adaptable to other fuel size classes through modification of the model’s fuel stick parameters. The algorithms for dead-fuel moisture in the National Fire Danger Rating System (NFDRS), on the other hand, were originally developed in the 1970s, utilise once-a-day weather information, and were designed to estimate dead-fuel moisture for mid-afternoon conditions. Including all field observations over the 21-month period, the Nelson model showed improvement over NFDRS for each size fuel size class, with r2 values ranging from 0.51 (1000-h fuels) to 0.79 (10-h fuels). However, for observed fuel moisture at or below 30%, the NFDRS performed better than the Nelson model for 1-h fuels and was about the same accuracy as the Nelson for 10-h fuels. The Nelson model is targeted for inclusion in the next-generation NFDRS.

scholarly journals Prototipe Sistem Peringatan Dini Kebakaran Hutan Berbasis Parameter Cuaca

Wahana Fisika ◽  
2017 ◽  
Vol 2 (2) ◽  
pp. 65
Author(s):  
Hapsoro Agung Nugroho ◽  
Chinthya Margaretta S
Keyword(s):  
Wind Speed ◽  
Early Warning ◽  
Forest Fires ◽  
Fire Danger ◽  
World Meteorological Organization ◽  
Rating System ◽  
Weather Data ◽  
Fuel Moisture ◽  
Fire Danger Rating System ◽  
Sd Card

Sistem peringatan dini kebakaran hutan memiliki peranan penting untuk mengendalikan secara dini kerusakan hutan. Badan Meteorologi Klimatologi dan Geofisika mempunyai tugas pokok, salah satunya yaitu memberikan peringatan dini kebakaran hutan menggunakan metode Fire Danger Rating System (FDRS) dimana data parameter cuaca sebagai masukan, masih terbatas pada lokasi tertentu. Penelitian ini merancang dan membangun prototipe yang menghasilkan skala Fine Fuel Moisture Code (FFMC) sebagai tingkat kemudahan terjadinya kebakaran di suatu lokasi. Perancangan prototipe ini menggunakan mikrokontroler ATMega328, sensor suhu dan kelembaban udara DHT22, penakar hujan jenis tipping bucket, sensor arah dan kecepatan angin JL_FS2, dan micro SD Card sebagai penyimpan data. Hasil kalibrasi sensor menunjukkan adanya selisih nilai sensor yang telah memenuhi nilai toleransi dari World Meteorological Organization (WMO). Pengujian setiap sensor menghasilkan nilai standar deviasi kurang dari 2.5 dengan rata- rata selisih pada sensor suhu +0.5oC, kelembaban relatif +6%, dan kecepatan angin +2 m/s. Setiap data yang diolah dapat ditampilkan dan disimpan secara otomatis oleh sistem. Sistem menampilkan secara realtime dan memberikan informasi peringatan dini kebakaran hutan. Kata Kunci   :  Kebakaran Hutan; FDRS; FFMC; Tipping BucketForest fire early warning system has an important role for the control of early damage to the forest. Indonesia Agency of Meteorology Climatology and Geophysics had a duty, one that is giving early warning forest fires using the method of Fire Danger Rating System (FDRS) where weather data as the input parameters, are still limited on site certain. The study design and build a prototype that generates scale Fine Fuel Moisture Code (FFMC) as the level of ease the onset of fire in any given location. This prototype design using the ATMega328 microcontroller, sensor temperature and humidity DHT22, tipping bucket type of rain gauge, direction and wind speed sensor JL_FS2, and micro SD Card as the data storage. The results showed a difference in sensor calibration value of sensor meets the tolerance values of the World Meteorological Organization (WMO). Test each sensor shows a value less than 2.5 standard deviation by the average difference in temperature sensors + 0.5 oC, + 6% relative humidity, and wind speed + 2 m/s. Data can be displayed and stored automatically by the system. The system displays in realtime and provide early warning information forest fires.           Keywords  :  Forest Fire; FDRS; FFMC; Tipping Bucket

Preliminary study on the validation of ECMWF with the ground-based data for the Indonesia Fire Danger Rating System (Ina-FDRS)

2021 ◽  
Author(s):  
Reni Sulistyowati ◽  
Fanny Meliani ◽  
Marina C. G. Frederik ◽  
Rizki Amaliyah ◽  
Zilda Dona Okta Permata ◽  
...  
Keyword(s):  
Fire Danger ◽  
Rating System ◽  
Preliminary Study ◽  
Fire Danger Rating System

The Oklahoma Fire Danger Model: An operational tool for mesoscale fire danger rating in Oklahoma

2002 ◽  
Vol 11 (4) ◽  
pp. 183 ◽  
Author(s):  
J. D. Carlson ◽  
Robert E. Burgan ◽  
David M. Engle ◽  
Justin R. Greenfield
Keyword(s):  
Wildland Fire ◽  
Weather Conditions ◽  
Fire Danger ◽  
Rating System ◽  
Weather Data ◽  
Fuel Load ◽  
Usda Forest Service ◽  
University Of Oklahoma ◽  
Oklahoma Mesonet ◽  
Fire Danger Rating System

This paper describes the Oklahoma Fire Danger Model, an operational fire danger rating system for the state of Oklahoma (USA) developed through joint efforts of Oklahoma State University, the University of Oklahoma, and the Fire Sciences Laboratory of the USDA Forest Service in Missoula, Montana. The model is an adaptation of the National Fire Danger Rating System (NFDRS) to Oklahoma, but more importantly, represents the first time anywhere that NFDRS has been implemented operationally using hourly weather data from a spatially dense automated weather station network (the Oklahoma Mesonet). Weekly AVHRR satellite imagery is also utilized for live fuel moisture and fuel load calculations. The result is a near-real-time mesoscale fire danger rating system to 1-km resolution whose output is readily available on the World Wide Web (http://agweather.mesonet.ou.edu/models/fire). Examples of output from 25 February 1998 are presented.The Oklahoma Fire Danger Model, in conjunction with other fire-related operational tools, has proven useful to the wildland fire management community in Oklahoma, for both wildfire anticipation and suppression and for prescribed fire activities. Instead of once-per-day NFDRS information at two to three sites, the fire manager now has statewide fire danger information available at 1-km resolution at up to hourly intervals, enabling a quicker response to changing fire weather conditions across the entire state.

A Method to Initialize the Keetch-Byram Drought Index

1993 ◽  
Vol 8 (4) ◽  
pp. 109-115 ◽  
Author(s):  
Robert E. Burgan
Keyword(s):  
Drought Index ◽  
Fire Danger ◽  
Rating System ◽  
Dead Vegetation ◽  
Fire Danger Rating System

Abstract The 1988 National Fire Danger Rating System implements the Keetch-Byram Drought Index. This index is output both as an estimator of drought in its own right and is used to modify fire danger calculations to account for deep drying of dead vegetation and duff. A method initializes this index for those fire danger rating stations that do not run the National Fire Danger Rating System all year long. West J. Appl. For. 8(4)109-115.

Reanalysis of ECMWF data for updating the Fire Weather Index for the Indonesia Fire Danger Rating System (InaFDRS)

2021 ◽  
Author(s):  
Andri Purwandani ◽  
Marina C. G. Frederik ◽  
Reni Sulistyowati ◽  
Lena Sumargana ◽  
Fanny Meliani ◽  
...  
Keyword(s):  
Fire Danger ◽  
Rating System ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Fire Danger Rating System

The Potential Predictability of Fire Danger Provided by Numerical Weather Prediction

2016 ◽  
Vol 55 (11) ◽  
pp. 2469-2491 ◽  
Author(s):  
Francesca Di Giuseppe ◽  
Florian Pappenberger ◽  
Fredrik Wetterhall ◽  
Blazej Krzeminski ◽  
Andrea Camia ◽  
...  
Keyword(s):  
Weather Prediction ◽  
Forest Service ◽  
Fire Danger ◽  
Rating System ◽  
Validation Dataset ◽  
Potential Predictability ◽  
Fire Weather Index ◽  
Weather Forecasts ◽  
Fire Emissions ◽  
Fire Danger Rating System

AbstractA global fire danger rating system driven by atmospheric model forcing has been developed with the aim of providing early warning information to civil protection authorities. The daily predictions of fire danger conditions are based on the U.S. Forest Service National Fire-Danger Rating System (NFDRS), the Canadian Forest Service Fire Weather Index Rating System (FWI), and the Australian McArthur (Mark 5) rating systems. Weather forcings are provided in real time by the European Centre for Medium-Range Weather Forecasts forecasting system at 25-km resolution. The global system’s potential predictability is assessed using reanalysis fields as weather forcings. The Global Fire Emissions Database (GFED4) provides 11 yr of observed burned areas from satellite measurements and is used as a validation dataset. The fire indices implemented are good predictors to highlight dangerous conditions. High values are correlated with observed fire, and low values correspond to nonobserved events. A more quantitative skill evaluation was performed using the extremal dependency index, which is a skill score specifically designed for rare events. It revealed that the three indices were more skillful than the random forecast to detect large fires on a global scale. The performance peaks in the boreal forests, the Mediterranean region, the Amazon rain forests, and Southeast Asia. The skill scores were then aggregated at the country level to reveal which nations could potentially benefit from the system information to aid decision-making and fire control support. Overall it was found that fire danger modeling based on weather forecasts can provide reasonable predictability over large parts of the global landmass.

scholarly journals Science, technology, and human factors in fire danger rating: the Canadian experience.

2006 ◽  
Vol 15 (1) ◽  
pp. 121 ◽  
Author(s):  
Stephen W. Taylor ◽  
Martin E. Alexander
Keyword(s):  
Forest Fire ◽  
Fire Management ◽  
Fire Danger ◽  
Rating System ◽  
Successful Implementation ◽  
Fire Weather ◽  
Fire Danger Rating System ◽  
Forest Fire Danger ◽  
In Fire ◽  
And Training

The present paper reviews the development of the Canadian Forest Fire Danger Rating System (CFFDRS) and its implementation in Canada and elsewhere, and suggests how this experience can be applied in developing fire danger rating systems in other forest or wildland environments. Experience with the CFFDRS suggests that four key scientific, technological, and human elements need to be developed and integrated in a national forest fire danger rating system. First among these is a sustained program of scientific research to develop a system based on relationships between fire weather, fuels, and topography, and fire occurrence, behavior, and impact appropriate to the fire environment. Development of a reliable technical infrastructure to gather, process, and archive fire weather data and to disseminate fire weather forecasts, fire danger information, and fire behavior predictions within operational agencies is also important. Technology transfer and training in the use of fire danger information in fire operations are necessary, as are cooperation and communication between fire management agencies to share resources and set common standards for information, resources, and training. These elements must be appropriate to the needs and capabilities of fire managers, and must evolve as fire management objectives change. Fire danger systems are a form of media; system developers should be careful not to overemphasize scientific and technological elements at the expense of human and institutional factors. Effective fire danger systems are readily assimilated by and influence the organizational culture, which in turn influences the development of new technologies. Most importantly, common vision and a sense of common cause among fire scientists and fire managers are needed for successful implementation of a fire danger rating system.

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