@article{digiuseppePotentialPredictabilityFire2016,
  title = {The Potential Predictability of Fire Danger Provided by Numerical Weather Prediction},
  author = {Di Giuseppe, Francesca and Pappenberger, Florian and Wetterhall, Fredrik and Krzeminski, Blazej and Camia, Andrea and Libertà, Giorgio and San Miguel, Jesus},
  date = {2016-08},
  journaltitle = {Journal of Applied Meteorology and Climatology},
  volume = {55},
  pages = {2469--2491},
  issn = {1558-8432},
  doi = {10.1175/jamc-d-15-0297.1},
  url = {http://mfkp.org/INRMM/article/14110878},
  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 US 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 (ECMWF) forecasting system at 25 km resolution. The global system's potential predictability is assessed using re-analysis fields as weather forcings. The Global Fire Emissions Database (GFED4) provides 11 years 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 non observed 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 on a global scale than the random forecast to detect large fires. The performance peaks in the boreal forests, in the Mediterranean, the Amazon rain-forests and southeast Asia. The skill-scores were then aggregated at country level to reveal which nations could potentiallty benefit from the system information in aid of decision making and fire control support. Overall we found that fire danger modelling based on weather forecasts, can provide reasonable predictability over large parts of the global landmass.},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14110878,~to-add-doi-URL,fire-fuel,fire-weather-index,global-scale,land-cover,mcarthur-mark-5,meteorology,model-comparison,national-fire-danger-rating-system,precipitation,risk-assessment,slope,vegetation,wildfires},
  number = {11}
}

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The daily predictions of fire danger conditions are based on the US 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 (ECMWF) forecasting system at 25 km resolution. The global system's potential predictability is assessed using re-analysis fields as weather forcings. The Global Fire Emissions Database (GFED4) provides 11 years 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 non observed 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 on a global scale than the random forecast to detect large fires. The performance peaks in the boreal forests, in the Mediterranean, the Amazon rain-forests and southeast Asia. The skill-scores were then aggregated at country level to reveal which nations could potentiallty benefit from the system information in aid of decision making and fire control support. Overall we found that fire danger modelling based on weather forecasts, can provide reasonable predictability over large parts of the global landmass.","keywords":"*imported-from-citeulike-INRMM,~INRMM-MiD:c-14110878,~to-add-doi-URL,fire-fuel,fire-weather-index,global-scale,land-cover,mcarthur-mark-5,meteorology,model-comparison,national-fire-danger-rating-system,precipitation,risk-assessment,slope,vegetation,wildfires","number":"11","bibtex":"@article{digiuseppePotentialPredictabilityFire2016,\n title = {The Potential Predictability of Fire Danger Provided by Numerical Weather Prediction},\n author = {Di Giuseppe, Francesca and Pappenberger, Florian and Wetterhall, Fredrik and Krzeminski, Blazej and Camia, Andrea and Libertà, Giorgio and San Miguel, Jesus},\n date = {2016-08},\n journaltitle = {Journal of Applied Meteorology and Climatology},\n volume = {55},\n pages = {2469--2491},\n issn = {1558-8432},\n doi = {10.1175/jamc-d-15-0297.1},\n url = {http://mfkp.org/INRMM/article/14110878},\n 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 US 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 (ECMWF) forecasting system at 25 km resolution. The global system's potential predictability is assessed using re-analysis fields as weather forcings. The Global Fire Emissions Database (GFED4) provides 11 years 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 non observed 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 on a global scale than the random forecast to detect large fires. The performance peaks in the boreal forests, in the Mediterranean, the Amazon rain-forests and southeast Asia. The skill-scores were then aggregated at country level to reveal which nations could potentiallty benefit from the system information in aid of decision making and fire control support. Overall we found that fire danger modelling based on weather forecasts, can provide reasonable predictability over large parts of the global landmass.},\n keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14110878,~to-add-doi-URL,fire-fuel,fire-weather-index,global-scale,land-cover,mcarthur-mark-5,meteorology,model-comparison,national-fire-danger-rating-system,precipitation,risk-assessment,slope,vegetation,wildfires},\n number = {11}\n}\n\n","author_short":["Di Giuseppe, F.","Pappenberger, F.","Wetterhall, F.","Krzeminski, B.","Camia, A.","Libertà, G.","San Miguel, J."],"key":"digiuseppePotentialPredictabilityFire2016","id":"digiuseppePotentialPredictabilityFire2016","bibbaseid":"digiuseppe-pappenberger-wetterhall-krzeminski-camia-libert-sanmiguel-thepotentialpredictabilityoffiredangerprovidedbynumericalweatherprediction","role":"author","urls":{"Paper":"http://mfkp.org/INRMM/article/14110878"},"keyword":["*imported-from-citeulike-INRMM","~INRMM-MiD:c-14110878","~to-add-doi-URL","fire-fuel","fire-weather-index","global-scale","land-cover","mcarthur-mark-5","meteorology","model-comparison","national-fire-danger-rating-system","precipitation","risk-assessment","slope","vegetation","wildfires"],"downloads":0},"bibtype":"article","biburl":"https://tmpfiles.org/dl/58794/INRMM.bib","creationDate":"2020-07-02T22:41:05.386Z","downloads":0,"keywords":["*imported-from-citeulike-inrmm","~inrmm-mid:c-14110878","~to-add-doi-url","fire-fuel","fire-weather-index","global-scale","land-cover","mcarthur-mark-5","meteorology","model-comparison","national-fire-danger-rating-system","precipitation","risk-assessment","slope","vegetation","wildfires"],"search_terms":["potential","predictability","fire","danger","provided","numerical","weather","prediction","di giuseppe","pappenberger","wetterhall","krzeminski","camia","libertà","san miguel"],"title":"The Potential Predictability of Fire Danger Provided by Numerical Weather Prediction","year":null,"dataSources":["DXuKbcZTirdigFKPF"]}