Improving the fire weather index system for peatlands using peat-specific hydrological input data

Mortelmans, Jonas; Felsberg, Anne; De Lannoy, Gabriëlle J. M.; Veraverbeke, Sander; Field, Robert D.; Andela, Niels; Bechtold, Michel

doi:https://doi.org/10.5194/nhess-24-445-2024

Articles | Volume 24, issue 2

https://doi.org/10.5194/nhess-24-445-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-24-445-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 2

Research article

|

09 Feb 2024

Research article |

| 09 Feb 2024

Improving the fire weather index system for peatlands using peat-specific hydrological input data

Jonas Mortelmans, Anne Felsberg, Gabriëlle J. M. De Lannoy, Sander Veraverbeke, Robert D. Field, Niels Andela, and Michel Bechtold

Data sets

The modern-era retrospective analysis for research and applications, version 2 (MERRA-2) (https://goldsmr4.gesdisc.eosdis.nasa.gov/data/MERRA2/) R. Gelaro et al. https://doi.org/10.1175/JCLI-D-16-0758.1

A land surface data assimilation product for peatlands using PEATCLSM and brightness temperature (Tb) satellite observations (Northern Hemisphere output) (1.0.0) M. Bechtold et al. https://doi.org/10.5281/zenodo.3731652

Global Fire Atlas with Characteristics of Individual Fires N. Andela et al. https://doi.org/10.3334/ORNLDAAC/1642

TUW-GEO/pytesmo: v0.15.1 (v0.15.1) C. Paulik et al. https://doi.org/10.5281/zenodo.8338451

Model code and software

Development of a Global Fire Weather Database (https://portal.nccs.nasa.gov/datashare/GlobalFWI/v2.0/20201013.GFWEDCode.tar.gz) R. D. Field et al. https://doi.org/10.5194/nhess-15-1407-2015

Short summary

With global warming increasing the frequency and intensity of wildfires in the boreal region, accurate risk assessments are becoming more crucial than ever before. The Canadian Fire Weather Index (FWI) is a renowned system, yet its effectiveness in peatlands, where hydrology plays a key role, is limited. By incorporating groundwater data from numerical models and satellite observations, our modified FWI improves the accuracy of fire danger predictions, especially over summer.