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Supplementary Dataset
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TITLEGlobal and regional trends and drivers of fire under climate change
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AUTHORS
Matthew W. Jones, John T. Abatzoglou, Sander Veraverbeke, Niels Andela, Gitta Lasslop, Matthias Forkel, Adam J. P. Smith, Chantelle Burton, Richard A. Betts, Guido R. van der Werf, Stephen Sitch, Josep G. Canadell, Cristina Santín, Crystal Kolden, Stefan H. Doerr, Corinne Le Quéré
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CONTACTmatthew.w.jones@uea.ac.uk
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STATUSPublished
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JOURNALReviews of Geophysics
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REFERENCEMatthew W. Jones, John T. Abatzoglou, Sander Veraverbeke, Niels Andela, Gitta Lasslop, Matthias Forkel, Adam J. P. Smith, Chantelle Burton, Richard A. Betts, Guido R. van der Werf, Stephen Sitch, Josep G. Canadell, Cristina Santín, Crystal Kolden, Stefan H. Doerr, Corinne Le Quéré (2022) Global and regional trends and drivers of fire under climate change, Reviews of Geophysics
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Worksheet NameContent List
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1. BA by RegionMean, trend, relative change and significance of trends in observed annual BA for each region, based on analysis of MODIS MCD64A1 BA data (2001-2019).
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Multi-model median annual BA for each region in the baseline period (1901-1930), and change in annual BA in 1990-2019 relative to the baseline period, as modelled by six FireMIP models. Multi-model agreement on the sign and significance of changes (% of FireMIP models in agreement) are also reported.
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2. FWI by RegionMean, trend, relative change and significance of trends in observed FWSL and FWI95d for each region, based on ERA5 data (1979-2019).
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Multi-model mean FWSL and FWI95d for each region in the baseline period (1860-1910), , and changes in FWSL and FWI95d relative to the baseline period for each region, based on CMIP5 data. Changes in FWSL and FWI95d are calculated for the modern (1990-2019) period and four temperature intervals 1.5°C, 2.0°C, 3.0°C, 4.0°C (see worksheet 4 for the model-specific period of each interval).
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Multi-model agreement on the sign and significance of changes at each temperature increment (% of CMIP5 models in agreement).
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Temperature increment at which FWSL and FWI95d are modelled to emerge above baseline variability according to the signal-to-noise criterion.
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3. Correlations by RegionCorrelations between monthly total BA and monthly average FWI in each region, based on MODIS BA and ERA5 data (2001-2019).
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Correlations between total BA in the annual fire season and average FWI in the annual fire season for each region, based on MODIS BA and ERA5 data (2001-2019). Each year’s fire season includes the fewest number of months in which BA amounts to >=80% of annual BA.
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Correlations between climatological monthly BA and climatological monthly lightning activity for each region, based on MODIS BA (2001-2019) and OTD-LIS data (tropics, 1998-2010; extratropics, 1995-2000).
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Spatial correlations between mean annual BA and population density, calculated at a spatial resolution of 2.5° based on the spatial variability seen across 100 constituent cells (0.25°) and subsequently averaged within regions. 
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Spatial correlations between mean annual BA and biomass density in tree, non-tree and all vegetation, calculated at a spatial resolution of 2.5° based on the spatial variability seen across 100 constituent cells (0.25°) and subsequently averaged within regions. 
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4. Model DetailsList of CMIP5 models included in the modelled FWSL and FWI95d analyses and the time periods used to assess changes in these metrics at 1.5°C, 2.0°C, 3.0°C, 4.0°C.
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List of FireMIP models included in the modelled BA analyses.
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