Calculating fire danger of cured grasslands in temperate climates – the elements of the Grassland Fire Index (GLFI)

Background Increasing extreme weather events due to climate change require updated environmental monitoring and prediction systems in Germany. Aim The Grassland Fire Index (GLFI), developed by the German Meteorological Service ~15 years ago for temperate climates, was revised to improve fire-danger...

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Veröffentlicht in:International journal of wildland fire 2023-07, Vol.32 (8), p.1212-1225
Hauptverfasser: Wittich, K.-P., Böttcher, C., Stammer, P., Herbst, M.
Format: Artikel
Sprache:eng
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Zusammenfassung:Background Increasing extreme weather events due to climate change require updated environmental monitoring and prediction systems in Germany. Aim The Grassland Fire Index (GLFI), developed by the German Meteorological Service ~15 years ago for temperate climates, was revised to improve fire-danger predictions during the fire season. Our paper gives insight into the new model version. Methods The former fire-behaviour core, i.e. Fosberg’s Fire Weather Index (FWI), is replaced by the standardised fire-reaction intensity, a different fuel-moisture of extinction term, and a replica of the fire-spread rate of the Canadian FFBP-System. A standardised ease-of-ignition index is added as a measure of ignition success. The fire module is supplied with diurnal dead-grass fuel-moisture calculations based on the water-budget and energy-balance concept. Key results The GLFI output is compared with diurnal fuel-moisture measurements and results of Wotton’s Grass-Fuel-Moisture model, Fosberg’s FWI, and Cheney’s rate of spread equation. The GLFI computes periods with a high fuel moisture more realistically, whereas it exceeds Cheney’s rate-of-fire spread systematically at lower wind speeds, which leads to higher danger ratings during calm-air conditions (as requested by users). Conclusions and Implications The GLFI estimates dead-fuel moisture and fire danger on open, horizontal topography according to the current scientific level. Model extensions are necessary to run the model on complex topography under varying greenness and occasional frost conditions.
ISSN:1049-8001
1448-5516
DOI:10.1071/WF22062