Submitted as: model evaluation paper
07 Oct 2022
Submitted as: model evaluation paper | 07 Oct 2022
Status: this preprint is currently under review for the journal GMD.

Evaluation of CMIP6 model performances in simulating fire weather spatiotemporal variability on global and regional scales

Carolina Gallo1, Jonathan M. Eden1, Bastien Dieppois1, Igor Drobyshev2,3,4, Peter Z. Fulé5, Jesús San-Miguel-Ayanz6, and Matthew Blackett1,7 Carolina Gallo et al.
  • 1Centre for Agroecology, Water and Resilience, Coventry University, Coventry, CV8 3LG, UK
  • 2Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Alnarp, 230 53, Sweden
  • 3Institut de recherche sur les forêts, Université du Québec en Abitibi-Témiscamingue (UQAT), QC J9X 5E4, Canada
  • 4Forest Research Institute of the Karelian Research Centre of the Russian Academy of Sciences, Petrozavodsk, 185910, Russia
  • 5School of Forestry, Northern Arizona University, Flagstaff, Arizona, 86011, USA
  • 6Disaster Risk Management Unit, Directorate for Space, Security and Mitigation, Joint Research Centre (JRC), European Commission, Ispra, 21027, Italy
  • 7School of Energy, Construction and Environment, Coventry University, Coventry, CV1 5FB, UK

Abstract. Weather and climate play an important role in shaping global wildfire regimes and geographical distributions of burnable area. As projected by the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6), in the near future, fire danger is likely to increase in many regions due to warmer temperatures and drier conditions. General Circulation Models (GCMs) are an important resource in understanding how fire danger will evolve in a changing climate but, to date, the development of fire risk scenarios has not fully accounted for systematic GCM errors and biases. This study presents a comprehensive global evaluation of the spatiotemporal representation of fire weather indicators from the Canadian Forest Fire Weather Index System simulated by 16 GCMs from the 6th Coupled Model Intercomparison Project (CMIP6). While at the global scale, the ensemble mean is able to represent variability, magnitude and spatial extent of different fire weather indicators reasonably well when compared to the latest global fire reanalysis, there is considerable regional and seasonal dependence in the performance of each GCM. To support the GCM selection and application for impact studies, the evaluation results are combined to generate global and regional rankings of individual GCM performance. The findings highlight the value of GCM evaluation and selection in developing more reliable projections of future climate-driven fire danger, thereby enabling decision makers and forest managers to take targeted action and respond to future fire events.

Carolina Gallo et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2022-223', Anonymous Referee #1, 22 Nov 2022
  • RC2: 'Comment on gmd-2022-223', Anonymous Referee #2, 03 Jan 2023
  • RC3: 'Review of gmd-2022-223', Matthew Kasoar, 06 Jan 2023

Carolina Gallo et al.

Carolina Gallo et al.


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Short summary
The study conducts the first global evaluation of the latest generation of global climate models to simulate a set of fire weather indicators from the Canadian Fire Weather Index System. Models are shown to perform relatively strongly at the global scale, but show substantial regional and seasonal differences. The results demonstrate the value of model evaluation and selection in producing reliable fire danger projections, ultimately to support decision making and forest management.