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  3. Impact model: BuRNN1-1

Impact model: BuRNN1-1

Sector
Fire
Region
global

Statistical fire model using the mean of 5 LSTMs at each location. Trained on GFEd5.1. BuRNN v1.1 uses gpp, lai and cveg from VISIT for all simulations.

Information for the model BuRNN1-1 is provided for the simulation rounds shown in the tabs below. Click on the appropriate tab to get the information for the simulation round you are interested in.

Person responsible for model simulations in this simulation round
Seppe Lampe: seppe.lampe@vub.be, 0000-0002-7907-4496, Vrije Universiteit Brussel, Department of Water & Climate (Belgium)
Output Data
Experiments: (*) ssp126_ssp126soc-noadapt+image_default, ssp585_2015soc-from-histsoc_default, ssp585_2015soc_default, ssp370_2015soc_default, historical_2015soc_default, ssp370_ssp370soc-noadapt+image_default, ssp370_ssp370soc-adapt+image_default, ssp126_2015soc-from-histsoc_default, historical_histsoc_default, ssp126_ssp126soc-adapt+image_default, ssp585_ssp585soc-noadapt+image_default, ssp126_2015soc_default, ssp585_ssp585soc-adapt+image_default, ssp370_2015soc-from-histsoc_default
Climate Drivers: GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL
Date: 2026-07-03
Basic information
Model Version: 1.1
Person responsible for model simulations in this simulation round
Seppe Lampe: seppe.lampe@vub.be, 0000-0002-7907-4496, Vrije Universiteit Brussel, Department of Water & Climate (Belgium)
Additional persons involved: Wim Thiery
Basic information
Model Version: 1.1
Model Homepage: https://github.com/VUB-HYDR/BuRNN
Model License: CC BY 4.0
Reference Paper: Main Reference: Lampe S, Gudmundsson L, Kraft B, Hantson S, Kelley D, Humphrey V, Le Saux B, Chuvieco E, Thiery W et al. BuRNN (v1.0): a data-driven fire model. Geoscientific Model Development,19,955-988,2026
Resolution
Spatial aggregation: regular grid
Horizontal resolution: 0.5°x0.5°
Vertically resolved: No
Temporal resolution of input data: climate variables: monthly
Temporal resolution of input data: land use/land cover: annual
Input data
Observed atmospheric climate data sets: GSWP3-W5E5 (ISIMIP3a)
Land use data sets: Historical, gridded land use
Other human influences data sets: Lakes area fraction
Other data sets: Lightning, Land-sea mask
Climate variables: hurs, sfcWind, tasmax, pr
Spin-up
Was a spin-up performed?: Yes
Spin-up design: Repeated the 1901-1903 in front of the 1901-2019 input dataset to spin up the memory of the LSTM (similar procedure as during model traiing).
Natural Vegetation
Natural vegetation partition: We applied the CLM pft structure and then regrouped the original pfts into 11 pfts (see model description paper).
Natural vegetation dynamics: It is not, for gpp, lai and cveg we used the values available on the ISIMIP repository from VISIT (which was not coupled to BuRNN).




Website consultancy, design and implementation:
Matthias Brück
brueck.io

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