Journal article

A lightning-caused wildfire ignition forecasting model for operational use

Nicholas Read, Thomas J Duff, Peter G Taylor

Agricultural and Forest Meteorology | Elsevier | Published : 2018

Abstract

Lightning-caused wildfires are responsible for substantial losses of lives and property worldwide. Convective storms can create large numbers of ignitions that can overwhelm suppression efforts. Both long- and short-term risk planning could benefit from daily, spatially-explicit forecasts of lightning ignitions. We fitted a logistic regression generalised additive model to lightning-caused ignitions in the state of Victoria, Australia. We proposed a new method for model selection that complemented existing methods and further reduced the number of variables in the model with minimal change to predictive power. We introduced an approach for deconstructing ignition forecasts into contributions..

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Grants

Awarded by Australian Research Council (ARC)


Funding Acknowledgements

Nicholas Read acknowledges the support of the Bushfire and Natural Hazards Cooperative Research Centre for funding through the project 'Probability of Fire Ignition and Escalation'. Tom J. Duff acknowledges the support of the Department of Environment, Land, Water and Planning as part of the integrated Forest and Ecosystem Research (iFER) program. Peter G. Taylor would like to acknowledge the support of the Australian Research Council (ARC) through Laureate Fellowship FL130100039 and the ARC Centre of Excellence for the Mathematical and Statistical Frontiers (ACEMS). He would also like to thank The Bushfire and Natural Hazards Cooperative Research Centre for funding through the project 'Probability of Fire Ignition and Escalation'. We would like to recognise the constructive comments of our reviewers that helped improved our work.