State of Wildfires 2024/25 – ConFLAME Driver Assessment - Congo Basin/Southern California

This repository contains ConFLAME driver assessment outputs for Congo Basin and Southern California 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: <<model_id>>/<<experiment>>/<<range>>/<<members or percentiles>>/<<metric>>/<<variable>>.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: <<model_id>>/<<experiment>>/<<variable>>/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 Northeastern Amizonia and Pantanal-Chiquitano State of Wildfires 2024/25 regions here: