1,2,3,4,5,6,8- 1Norwegian University of Science and Technology, Biology, Trondheim, Norway (els.ribbers@ntnu.no)
- 2Norwegian University of Science and Technology, Biology, Trondheim, Norway
- 3Norce Research Centre, Climate and Environment, Bergen, Norway
- 4Norwegian University of Science and Technology, Energy and Process Engineering, Trondheim, Norway
- 5NILU, Atmosphere and Climate, Kjeller, Norway
- 6Lund University, Earth and Environmental Sciences, Lund, Sweden
- 7City University of Hong Kong, Energy and Environment, Hong Kong
- 8Yunnan University, Atmospheric Sciences, Kunming, China
Recent studies have shown an increase in fire damage risks in northern latitudinal forests related to climate warming (Maes et al., 2020; Venäläinen et al., 2020). These forest systems are complex, with many feedback loops, such as between different types of damage and forest structure parameters. Due to this complexity, the resilience to damage and therefore ability of forests to mitigate climate on a regional scale are still poorly understood. Understanding this complexity requires model work and extensive literature research, as most studies only focus on a few aspects of the forest system (Lagergren & Jonsson, 2017; Konôpka et al., 2016).
Within Fennoscandia, fire risk warnings are mainly based on the output of the Canadian Fire Weather Index (FWI). This index is purely weather based and does not differentiate between vegetation types. Other fire risk prediction models, such as the US National Fire Danger Rating System (NFDRS), are more comprehensive and might therefore lead to more accurate results. The aim of this study was therefore to test the FWI and NFDRS models in their ability to predict forest fire size in boreal Fennoscandia. Expectation was that the more comprehensive NFDRS, which includes vegetation-specific information, would outperform the purely weather-based FWI in predicting forest fire risk in Fennoscandia.
Output from the 3km resolution HARMONIE Climate (HCLIM3) model was used as input in both the FWI and NFDRS to model forest fire risk in boreal Fennoscandia over the years 2001-2018. The output from these models was then compared to burned area data from a variety of data sources in Fennoscandia (MODIS and EFFIS burned area products) and Norway (DBS fire statistics, Skogbrand forest insurance, NIBIO National Forest Inventory).
Our results show that both the FWI and NFDRS fail to capture forest fire intensity in boreal Fennocandia. Neither model shows any pattern that relates historical forest fire size to predicted fire risk. Additionally, the different burned area datasets disagree with each other both in terms of number, location and date of historical fires, as well as fire size. In this poster presentation we will discuss these results, as well as the methodology we used to reach this conclusion.
How to cite: Ribbers, E., Lee, H., Mooney, P., Muri, H., Nieradzik, L., Kim, J.-S., and Cai, L.: When increased complexity does not help model accuracy: both FWI and NFDRS fail to accurately predict forest fire risk in Fennoscandia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3604, https://doi.org/10.5194/egusphere-egu26-3604, 2026.
