Articles | Volume 23, issue 1
https://doi.org/10.5194/nhess-23-65-2023
https://doi.org/10.5194/nhess-23-65-2023
Research article
 | 
12 Jan 2023
Research article |  | 12 Jan 2023

A data-driven model for Fennoscandian wildfire danger

Sigrid Jørgensen Bakke, Niko Wanders, Karin van der Wiel, and Lena Merete Tallaksen

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Cited articles

Aalto, J. and Venäläinen, A.: Climate change and forest management affect forest fire risk in Fennoscandia, Tech. Rep. 2021:3, Ilmatieteen laitos – Finnish Meteorological Institute, ISBN 978-952-336-135-5, 2021. a, b
Abatzoglou, J. T. and Kolden, C. A.: Relationships between climate and macroscale area burned in the western United States, Int. J. Wildland Fire, 22, 1003–1020, https://doi.org/10.1071/WF13019, 2013. a
Abatzoglou, J. T., Williams, A. P., and Barbero, R.: Global emergence of anthropogenic climate change in fire weather indices, Geophys. Res. Lett., 46, 326–336, https://doi.org/10.1029/2018GL080959, 2019. a
Aldersley, A., Murray, S. J., and Cornell, S. E.: Global and regional analysis of climate and human drivers of wildfire, Sci. Total Environ., 409, 3472–3481, https://doi.org/10.1016/j.scitotenv.2011.05.032, 2011. a, b, c, d
Andela, N., Morton, D. C., Giglio, L., Chen, Y., Van der Werf, G. R., Kasibhatla, P. S., DeFries, R. S., Collatz, G. J., Hantson, S., Kloster, S., Bachelet, D., Forrest, M., Lasslop, G., Li, F., Mangeon, S., Melton, J. R., Yue, C., and Randerson, J. T.: A human-driven decline in global burned area, Science, 356, 1356–1362, https://doi.org/10.1126/science.aal4108, 2017. a
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Short summary
In this study, we developed a machine learning model to identify dominant controls of wildfire in Fennoscandia and produce monthly fire danger probability maps. The dominant control was shallow-soil water anomaly, followed by air temperature and deep soil water. The model proved skilful with a similar performance as the existing Canadian Forest Fire Weather Index (FWI). We highlight the benefit of using data-driven models jointly with other fire models to improve fire monitoring and prediction.
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