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ProbFire: a probabilistic fire early warning system for Indonesia

Recurrent extreme landscape fire episodes associated with drought events in Indonesia pose severe environmental, societal and economic threats. The ability to predict severe fire episodes months in advance would enable relevant agencies and communities to more effectively initiate fire-preventative...

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Published in:Natural hazards and earth system sciences 2022-02, Vol.22 (2), p.303-322
Main Authors: Nikonovas, Tadas, Spessa, Allan, Doerr, Stefan H, Clay, Gareth D, Mezbahuddin, Symon
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creator Nikonovas, Tadas
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description Recurrent extreme landscape fire episodes associated with drought events in Indonesia pose severe environmental, societal and economic threats. The ability to predict severe fire episodes months in advance would enable relevant agencies and communities to more effectively initiate fire-preventative measures and mitigate fire impacts. While dynamic seasonal climate predictions are increasingly skilful at predicting fire-favourable conditions months in advance in Indonesia, there is little evidence that such information is widely used yet by decision makers.
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identifier ISSN: 1684-9981
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subjects Analysis
Climate
Climate prediction
Climatic changes
Climatology
Datasets
Drought
Droughts
Early warning systems
Economic benefits
El Nino
Fires
Forecasting
Forest fires
Indonesia
Lead time
Mathematical models
Multilayer perceptrons
Peatlands
Precipitation
Prediction models
Predictions
Probability theory
Regions
Seasonal forecasting
Statistical analysis
Temperature
Warning systems
Weather forecasting
title ProbFire: a probabilistic fire early warning system for Indonesia
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