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Type: Journal Article
Author(s): Martin Dubrovsky; Michele Salis; Petr Štěpánek; Pierpaolo Duce; Pavel Zahradníček; Jan Meitner; Martin Mozny
Publication Date: 2022

To construct time series for a Fire Weather Index (FWI), input weather series may come from various sources. Observed weather station data or gridded series interpolated from observations are commonly used to produce FWI series representing the present climate. FWI series representing the future may be based on RCM-simulated data or on series synthesized by a stochastic weather generator (WG). In the latter case, WG parameters are calibrated with observed weather data and modified using the climate change (CC) scenarios derived from GCM or RCM simulations. The application of a WG implies some advantages, including: (a) arbitrarily long series may be produced, allowing us to make a probabilistic assessment of CC impacts on the FWI. (b) only selected characteristics of the multi-variate multi-site weather series may be modified when modifying WG parameters before producing the weather series representing the modified climate (the complete CC scenario consists of changes in averages and standard deviations of weather variables, and changes in the temporal and spatial structure of weather series); this allows us to assess the sensitivity of the FWI to changes in individual statistical characteristics of the weather series.

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Citation: Dubrovsky, Martin; Salis, Michele; Štěpánek, Petr; Duce, Pierpaolo; Zahradnicek, Pavel; Meitner, Jan; Mozny, Martin. 2022. Modelling present and future wildfire risk with use of a fire weather index, spatial weather generator and regional climate models. Environmental Sciences Proceedings 17(1):130.

Cataloging Information

Topics:
Climate    Hazard and Risk    Models    Weather
Regions:
Keywords:
  • Czech Republic
  • FWI - Canadian Forest Fire Weather Index System
  • Sardinia
Record Last Modified:
Record Maintained By: FRAMES Staff (https://www.frames.gov/contact)
FRAMES Record Number: 66985