Editorial Type:
Article
Article Type:
Research Article

The Potential Predictability of Fire Danger Provided by Numerical Weather Prediction

Francesca Di Giuseppe European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

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Florian Pappenberger European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

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Fredrik Wetterhall European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

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Blazej Krzeminski European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

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Andrea Camia Joint Research Centre, Ispra, Italy

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Giorgio Libertá Joint Research Centre, Ispra, Italy

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Jesus San Miguel Joint Research Centre, Ispra, Italy

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Print Publication:
01 Nov 2016
DOI:
https://doi.org/10.1175/JAMC-D-15-0297.1
Page(s):
2469–2491
Restricted access

Abstract

A 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.

Denotes Open Access content.

Corresponding author address: Francesca Di Giuseppe, ECMWF, Shinfield Park, Reading RG2 9AX, United Kingdom. E-mail: digiuseppe@ecmwf.int

Abstract

A 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.

Denotes Open Access content.

Corresponding author address: Francesca Di Giuseppe, ECMWF, Shinfield Park, Reading RG2 9AX, United Kingdom. E-mail: digiuseppe@ecmwf.int
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Journal of Applied Meteorology and Climatology

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