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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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State of Wildfires 2024/25 – ConFLAME Driver Assessment - Northeastern Amizonia/Pantanal-Chiquitano

Authors: Ferreira Barbosa, Maria Lucia; Kelley, Douglas; Hartley, Andrew; Spuler, Fiona; Wessel, Jakob; Ciavarella, Andrew; McNorton, Joe; +3 Authors

State of Wildfires 2024/25 – ConFLAME Driver Assessment - Northeastern Amizonia/Pantanal-Chiquitano

Abstract

This repository contains ConFLAME driver assessment outputs for Northeastern Amizonia and Pantanal-Chiquitano regions, as used in the State of Wildfires 2024/25 report.It provides the model ouputs required to explore the contribution of individual drivers (fuel, moisture, weather, wind, ignitions, suppression) to burned area (BA) in 2024/25, along with all intermediate data required for reproducing the reported results. Contents Core directories: figs – Automatically generated evaluation figures and selected plots from the driver assessment runs. time_series – Burned area (BA) time series for all driver assessment experiments.Structure: >/>/>/>/>/>.csv Model ID: _21-frac_points_0.5 Experiment: baseline- – Baseline driver assessment run for this region Range: mean – Regional mean burned area pc-0.95 – Burned area for the top 5% of BA grid cells Members or Percentiles: members – Time series for each ensemble member from the sampled posterior percentiles – Precomputed percentile ranges (e.g., 5th–95th) across members Metric: absolute – Burned area in km² (or equivalent units) climatology – Long-term monthly mean BA anomaly – Deviation from climatology for that month ratio – BA divided by climatology Variables:These files are explicitly named to indicate the driver tested and whether the BA is simulated (Evaluate), the standard limitation (Standard_[N]), or the increase in BA due to control (Potential_climatology[N]): Control.csv Evaluate.csv standard-Fuel.csv standard-Moisture.csv standard-Weather.csv standard-Wind.csv standard-Ignition.csv standard-Suppression.csv potential_climatology-Fuel.csv potential_climatology-Moisture.csv potential_climatology-Weather.csv potential_climatology-Wind.csv potential_climatology-Ignition.csv potential_climatology-Suppression.csv Grouping in the State of Wildfires report: Fuel & Moisture → Fuel Weather & Wind → Weather Ignitions & Suppression → Ignitions/Human samples – Full spatial posterior samples for each driver and control experiment.Structure: >/>/>/sample-predXXX.nc Model ID: _21-frac_points_0.5 Experiment: baseline- Variables: Evaluate – Simulated BA Standard_[N] – Standard limitation for driver N, Where N is: 0: Fuel 1: Moisture 2: Weather 3: Wind 4: Ignitions 5: Suppression Potential_climatology[N] – Increase in BA from removal of limitation N(N mapping as above) Pairing: Samples are paired across variables within the same optimisation run (i.e., sample-predX.nc for Evaluate corresponds to the same ensemble member as sample-predX.nc for Standard_[N]). Note: A separate repository exists for Congo Basin/Southern California State of Wildfires 2024/25 regions here:

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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).
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