Preprints
https://doi.org/10.5194/egusphere-2024-1973
https://doi.org/10.5194/egusphere-2024-1973
02 Aug 2024
 | 02 Aug 2024

Understanding and simulating cropland and non-cropland burning in Europe using the BASE (Burnt Area Simulator for Europe) model

Matthew Forrest, Jessica Hetzer, Maik Billing, Simon P. K. Bowring, Eric Kosczor, Luke Oberhagemann, Oliver Perkins, Dan Warren, Fátima Arrogante-Funes, Kirsten Thonicke, and Thomas Hickler

Abstract. Fire interacts with many parts of the Earth system. However, its drivers are myriad and complex, interacting differently in different regions depending on prevailing climate regimes, vegetation types, socioeconomic development, and land use and management. Europe is facing strong increases in projected meteorological fire danger as a consequence of climate change, and has experienced extreme fire seasons and events in recent years. Here, we focus on understanding and simulating burnt area across a European study domain using remote sensing data and Generalised Linear Models (GLMs). We first examined fire occurrence across land cover types and found that all non-cropland vegetation types (NCV, comprising 26 % of burnt area) burned with similar spatial and temporal patterns, which were very distinct from those in croplands (74 % of burned area). We then used GLMs to predict cropland and NCV burnt area at ~9x9 km and monthly spatial and temporal resolution, respectively, which together we termed BASE (Burnt Area Simulator for Europe). Compared to satellite burned area products, BASE effectively captured the general spatial and temporal patterns of burning, explaining 32 % (NCV) and 36 % (cropland) of the deviance, and gave similar performance of state-of-the-art global fire models. The most important drivers were fire weather and monthly indices derived from gross primary productivity, followed by coarse socioeconomic indicators and vegetation properties. Crucially, we found that the drivers of cropland and NCV burning were very different, highlighting the importance of simulating burning in different land cover types separately. Through the choice of predictor variables, BASE was designed for coupling with dynamic vegetation and Earth System models, and thus enabling future projections. In particular, the strong model skill of BASE when reproducing seasonal and interannual dynamics of NCV burning (i.e. temporally evolving wildfire risk), and the novel inclusion of cropland burning, recommend it for this purpose. In addition to this, the BASE framework may serve as a basis for further studies using additional predictors to further elucidate drivers of fire in Europe. Through these applications, we suggest BASE may be a useful tool for understanding, and therefore adapting to, the increasing fire risk in Europe.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Matthew Forrest, Jessica Hetzer, Maik Billing, Simon P. K. Bowring, Eric Kosczor, Luke Oberhagemann, Oliver Perkins, Dan Warren, Fátima Arrogante-Funes, Kirsten Thonicke, and Thomas Hickler

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2024-1973', Taimur Khan, 06 Aug 2024
    • AC1: 'Reply on CC1', Matthew Forrest, 04 Oct 2024
  • RC1: 'Comment on egusphere-2024-1973', Anonymous Referee #1, 21 Aug 2024
    • AC2: 'Reply on RC1', Matthew Forrest, 04 Oct 2024
  • RC2: 'Comment on egusphere-2024-1973', Anonymous Referee #2, 23 Aug 2024
    • AC3: 'Reply on RC2', Matthew Forrest, 04 Oct 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2024-1973', Taimur Khan, 06 Aug 2024
    • AC1: 'Reply on CC1', Matthew Forrest, 04 Oct 2024
  • RC1: 'Comment on egusphere-2024-1973', Anonymous Referee #1, 21 Aug 2024
    • AC2: 'Reply on RC1', Matthew Forrest, 04 Oct 2024
  • RC2: 'Comment on egusphere-2024-1973', Anonymous Referee #2, 23 Aug 2024
    • AC3: 'Reply on RC2', Matthew Forrest, 04 Oct 2024
Matthew Forrest, Jessica Hetzer, Maik Billing, Simon P. K. Bowring, Eric Kosczor, Luke Oberhagemann, Oliver Perkins, Dan Warren, Fátima Arrogante-Funes, Kirsten Thonicke, and Thomas Hickler

Data sets

Data for fitting Burnt Area Simulator for Europe (BASE v1.0) Matthew Forrest https://zenodo.org/records/12580343

Model code and software

BASE-v1.0: Submission Release (v1.0) Matthew Forrest https://zenodo.org/records/12580481

Matthew Forrest, Jessica Hetzer, Maik Billing, Simon P. K. Bowring, Eric Kosczor, Luke Oberhagemann, Oliver Perkins, Dan Warren, Fátima Arrogante-Funes, Kirsten Thonicke, and Thomas Hickler

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Short summary
Climate change is causing an increase in extreme wildfires in Europe but drivers of fire are not well understood, especially across different land cover types. We used statistical models with satellite data, climate data and socioeconomic data to determine what affects burning in cropland and non-cropland area Europe. We found different drivers of burning in cropland burning vs non-cropland, to the point that some variable, e.g. population density, had completely the opposite effects.