Articles | Volume 15, issue 9
https://doi.org/10.5194/nhess-15-2037-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-15-2037-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Multi-variable bias correction: application of forest fire risk in present and future climate in Sweden
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
M. Gardelin
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
J. Olsson
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
T. Bosshard
Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
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35 citations as recorded by crossref.
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- Projected changes in forest fire season, the number of fires, and burnt area in Fennoscandia by 2100 O. Kinnunen et al. 10.5194/bg-21-4739-2024
- Physical characteristics of the thermal impact of an emergency fire V. Tumanov et al. 10.1088/1742-6596/1614/1/012074
- Climate indices for the tailoring of climate information – A systematic literature review of Swedish forestry and agriculture L. Wiréhn 10.1016/j.crm.2021.100370
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- Downscaling fire weather extremes from historical and projected climate models P. Jain et al. 10.1007/s10584-020-02865-5
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- Direct and component-wise bias correction of multi-variate climate indices: the percentile adjustment function diagnostic tool A. Casanueva et al. 10.1007/s10584-018-2167-5
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1 citations as recorded by crossref.
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Latest update: 20 Nov 2024
Short summary
A distribution-based scaling approach was developed and proven useful as a post-process to correct systematic biases in climate modelling outputs (i.e. precipitation, temperature, relative humidity and wind speed) to facilitate the utilisation of climate projections in forest fire risk studies. The result showed reduction of bias in forcing data and an improved description of fire-risk-related indices. Concerning the future climate, southern Sweden is likely to become a more fire-prone region.
A distribution-based scaling approach was developed and proven useful as a post-process to...
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