New gridded daily wildfire risk products for Slovakia and their validation using observed data and expert assessment

Daily wildfire risk has been monitored in Slovakia since 2002 and it is legally binding within the fire prevention. The original methodology needed an update to improve the accuracy and to bring more robust information about wildfire risk in different parts of country with high diversity of a terrain and land use. Therefore, new wildfire risk forecasting products, which were developed under the project Clim4Cast, were adopted, customized and implemented into existing national platform. The products consist of following indicators: Fire Weather Index (FWI), Fuel Moisture 1H, 10H, 100H and 1000H. The original Clim4Cast wildfire forecasting products are computed using deterministic ECMWF model with the spatial resolution of 9 km. The adopted Slovak products are based on ALADIN NWP model with 2 km resolution (for the first three days, including the day of calculation) and coarser ensemble mean of ECMFW IFS model (day 4 – 7).

As the wildfire risk monitoring products are legally binding for the Firefighting and Rescuing Corps of the Slovak Republic (HaZZ SR), it was necessary to understand the uncertainty of new forecasting products. Therefore, two types of validation assessment was proceeded. The first validation based on the expert assessment (qualitative approach) was done during the wildfire season 2025. This testing of the new products was conducted in selected NUTS4 regions in the co-operation with HaZZ SR. The experts received on daily basis updated forecasting maps of the wildfire risk and evaluated their accuracy with the conditions in their region. The expert assessment as a qualitative validation approach is used on weekly basis within the soil drought monitoring (Intersucho) and shows well reliability on expert assessment. Further, this testing helped us to gather the feedback by the end users and to customize the products for the specific needs of the firefighters.

The second part of validation was based on observed data at 101 meteorological stations in Slovakia. We chose two case study periods – summer 2025 and spring 2026. Both study periods were characterised by diverse weather conditions (dynamically changing weather with convective precipitation vs. long-lasting stable dry and warm weather), which enabled us to test the performance of the forecasting products under different weather conditions and to reach more robust information about uncertainty, which needs to be communicated to the end users, especially firefighters. The validation on objective data showed well accuracy and reliability of the new products. However, the uncertainty rises in the case of forecasted convective precipitation.

Acknowledgment

This work was supported by project Clim4Cast (Central European Alliance for Increasing Climate Change Resilience to Combined Consequences of Drought, Heatwave, and Fire Weather through Regionally-Tuned Forecasting; CE0100059) co-funded by European Union funds (ERDF – Interreg Central Europe).