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ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Global Fire Danger Masks at 1° Resolution: Delineating Infrequent Fires and Trend Inconsistencies

Authors: Turco, Marco; Moreno-Torreira, Alberto;

Global Fire Danger Masks at 1° Resolution: Delineating Infrequent Fires and Trend Inconsistencies

Abstract

This repository contains two complementary NetCDF datasets that support the analyses presented in our arXiv preprint:https://arxiv.org/abs/2503.01818 They provide global fire danger masks at a 1° spatial resolution, specifically tailored to wildfire danger assessments based on the Fire Weather Index (FWI). File 1: Mask of Infrequent Fires (1° Resolution) Contents: This file contains a spatial mask identifying regions with infrequent fire activity. Grid cells are marked based on criteria defined in the study (e.g., high proportions of bare areas, water, snow/ice, or sparse vegetation), thereby excluding areas unlikely to experience regular burning. Purpose: It serves as a baseline dataset to delineate areas where extreme fire weather events are less frequent, ensuring that subsequent analyses focus on regions of active fire dynamics. File 2: Mask with Trend Inconsistencies (1° Resolution) Contents: Building on the first file, this dataset incorporates additional masking to highlight regions where the trends in FWI—calculated using daily approximations—are not preserved when compared to the baseline noon-specific FWI (i.e., using the C1 combination as detailed in the preprint). Purpose: This file is particularly useful for identifying areas where daily meteorological approximations may introduce significant biases in the projected trends of extreme fire weather. Researchers can use this mask to better interpret the reliability of fire danger projections and to refine methodological approaches in climate change studies.

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Keywords

Wildfire danger, Climate Change and Wildfire Dynamics, Fire Weather Index (FWI), Daily meteorological approximations, Climate change, Atmospheric Science and Meteorology, Infrequent fires mask

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citations
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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