Next Article in Journal
The Photodecomposition of Selected Organic Micropollutants in the Presence of Chlorides
Previous Article in Journal
Laboratory Investigation of Flammability of Two Decking Slabs Used in the Wildland–Urban Interface
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Abstract

Modelling Present and Future Wildfire Risk with Use of a Fire Weather Index, Spatial Weather Generator and Regional Climate Models †

1
Institute of Atmospheric Physics CAS, 14100 Prague, Czech Republic
2
Global Change Research Institute CAS, 60300 Brno, Czech Republic
3
Institute of BioEconomy, National Research Council, 07100 Sassari, Italy
*
Author to whom correspondence should be addressed.
Presented at the Third International Conference on Fire Behavior and Risk, Sardinia, Italy, 3–6 May 2022.
Environ. Sci. Proc. 2022, 17(1), 130; https://doi.org/10.3390/environsciproc2022017130
Published: 22 September 2022
(This article belongs to the Proceedings of The Third International Conference on Fire Behavior and Risk)
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.
We use the spatial daily weather generator SPAGETTA (Dubrovsky et 2020, Theor. Appl. Climatol.) to produce a synthetic weather series representing present and future climates for Czechia (125 weather stations) and Sardinia (15 stations). FWI time series are constructed using both present-climate and future-climate weather series, and the changes in FWI characteristics due to climate change are assessed. The future climate weather series are produced with WG modified using the CC scenarios derived from a set of RCMs. In assessing the results, we focus on high FWI values, spatial extent of the area with high FWI values, and the duration of the periods with a high FWI. The results based on the WG-synthesized weather series are compared with those based on the RCM-simulated series.

Author Contributions

Conceptualization, M.D. and M.S.; methodology, M.D. and M.S.; software, M.D. and J.M.; validation, M.D., P.S. and P.Z.; data curation, M.D., M.S. and P.D.; writing—original draft preparation, M.D.; writing review and editing, all co-authors. All authors have read and agreed to the published version of the manuscript.

Funding

The present experiment was made within the frame of project 18-15958S funded by the Czech Science Foundation.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The present experiment was made within the frame of project 18-15958S (“Development of high-resolution spatial weather generator for use in present and future climate conditions”) supported by the Czech Science Foundation.

Conflicts of Interest

The authors declare no conflict of interest.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Dubrovsky, M.; Salis, M.; Stepanek, P.; Duce, P.; Zahradnicek, P.; Meitner, J.; Mozny, M. Modelling Present and Future Wildfire Risk with Use of a Fire Weather Index, Spatial Weather Generator and Regional Climate Models. Environ. Sci. Proc. 2022, 17, 130. https://doi.org/10.3390/environsciproc2022017130

AMA Style

Dubrovsky M, Salis M, Stepanek P, Duce P, Zahradnicek P, Meitner J, Mozny M. Modelling Present and Future Wildfire Risk with Use of a Fire Weather Index, Spatial Weather Generator and Regional Climate Models. Environmental Sciences Proceedings. 2022; 17(1):130. https://doi.org/10.3390/environsciproc2022017130

Chicago/Turabian Style

Dubrovsky, Martin, Michele Salis, Petr Stepanek, Pierpaolo Duce, Pavel Zahradnicek, Jan Meitner, and Martin Mozny. 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, no. 1: 130. https://doi.org/10.3390/environsciproc2022017130

APA Style

Dubrovsky, M., Salis, M., Stepanek, P., Duce, P., Zahradnicek, P., Meitner, J., & Mozny, M. (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. https://doi.org/10.3390/environsciproc2022017130

Article Metrics

Back to TopTop