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Dataset . 2022
License: CC BY
Data sources: Datacite
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Dataset . 2022
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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https://doi.org/10.5281/zenodo...
Dataset . 2022
License: CC BY
Data sources: Sygma
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Data and code for "increasing aridity causes larger and more severe forest fires across Europe"

Authors: Marc Grünig;

Data and code for "increasing aridity causes larger and more severe forest fires across Europe"

Abstract

### Data and code for "increasing aridity causes larger and more severe forest fires across Europe" This repository holds code and data for the publication in GCB entitled: Increasing aridity causes larger and more severe forest fires across Europe (manuscript accepted) # scripts all scripts are in the folder "lib". In order to perform the full analysis, please follow through all scripts. we provide the results of some steps in order to reduce runtime for the user. we indicate this in the headings of the scripts. 1. in the first script we prepare the ERA5-Land data. The code for the download is provided. The user needs a CDS API for downloading. 2. the data from the ERA5-Land summer VPD is extracted for the fire complexes 3. calculation of the maximum fire size to total burned area relationship 4. the models are calibrated and compared. In this script the figure 3 and 4 are created 5. preparation of the future climate dataset. Again, the script for the download is provided but the user needs an API. 6. Extraction of the CMIP6 VPD. 7. Future climate analysis 8. Plotting of all figures that were not done in the previous scripts # data climate: we provide the climate grid. all other climate data can be downloaded following the instructions within the scripts. complexes: we provide the fire complexes of each country. This data contains all information needed for the analysis including year, size, severity and polygon information. The complexes are based on the data from Senf & Seidl, 2021 (https://doi.org/10.1038/s41893-020-00609-y) which can be downloaded here: https://doi.org/10.5281/zenodo.7080016 countries: we provide the shapefiles of each country and Europe that are needed for the analysis in this folder. ecoregions: Olson et al. terrestrial ecosystems should be downloaded from: https://www.arcgis.com/home/item.html?id=be0f9e21de7a4a61856dad78d1c79eae models: we provide all final models used for the analysis. results: we provide the results of the individual steps. This should help to reduce the runtime for the user. # additional information R version 3.6.3 (2020-02-29) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 18.04.5 LTS

Raw data from European forest disturbance maps (10.5281/zenodo.4570157)

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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).
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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.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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