
This dataset contains the Canadian Forest Fire Weather Index (FWI) calculated from six downscaled and bias-corrected CMIP6 model outputs. The models included are: ACCESS-CM2 (Ziehn et al. 2020) CanESM5 (Swart et al. 2019) CNRM-ESM2-1 (Séférian et al. 2019) EC-EARTH3 (EC-Earth Consortium 2019) MPI-ESM1-2-HR (von Storch et al. 2017) MRI-ESM2-0 (Yukimoto et al. 2019) The dataset encompasses four Shared Socio-economic Pathway (SSP) projections: SSP1-2.6 SSP2-4.5 SSP3-7.0 SSP5-8.5 Each model output has been downscaled to a resolution of 0.0703135°, corresponding to approximately 9km×9km grids before the FWI calculation. The data covers Europe spatially and temporally spans from 1950 to 2080, offering comprehensive insights into past, present, and future fire weather conditions. This dataset supports the manuscript titled "The fire weather in Europe: large-scale trends towards higher danger" by Hetzer et al., currently under review in ERL. Detailed instructions for accessing the data can be found in the included README file. Note: Downloads are password protected. Please use "FWI_2024" for access. Funding: The authors acknowledge the financial support of the European Union’s Horizon 2020 research and innovation action for the FirEUrisk project under grant agreement ID: 101003890.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
