Characterizing Wildfire Danger in Italy: The Added Value of High-Resolution Reanalyses

Wildfires are a critical threat to both people and infrastructures. Although most wildfires in Italy are human-caused, their ignition and propagation are strongly influenced by wildfire-prone meteorological conditions, such as droughts, heatwaves, and strong winds, which are projected to increase in both severity and frequency in the coming decades due to ongoing climate change.

To effectively prevent  wildfires and to forecast wildfire risk over a territory, it is essential to understand the meteorological situation in which they have ignited and developed in the past. In this work, we focus on calculating the meteorological wildfire danger through the Canadian Fire Weather Index (FWI) over two high resolution reanalyses for Italy, MERIDA HRES and MERIDA HRES OI.

The FWI represents an estimate of the meteorological wildfire danger of an area, combining 2m temperature, 2m relative humidity, 10m wind speed, and total rainfall fields; therefore, the more accurate the meteorological inputs are, the more accurate the FWI becomes. Meteorological reanalyses represent the most reliable source for such inputs, as they integrate observational data with numerical weather prediction models. This approach enables the detailed reconstruction of past weather conditions over extensive territories, including areas lacking direct observational data

In this context, we have investigated the added value of higher resolution reanalyses by comparing FWI computed over the coarser ERA5 reanalysis with the higher resolution MERIDA HRES and MERIDA HRES OI reanalyses. These two reanalyses, which use ERA5 as a meteorological driver, are downscaled through the WRF-ARW model with parametrizations specifically tailored to the complex geography of the Italian territory. MERIDA HRES covers the period from 1986 to 2021, while MERIDA HRES OI spans 2005 to 2021, integrating observational data for enhanced accuracy.

The comparison has been carried out through the analysis of several case studies and through the analysis of the datasets’ performances over all the wildfires that happened over Italy in the past decade, as well as through considerations over FWI climatological trends. While ERA5 is a robust and extensively validated resource, its coarser resolution poses limitations in accurately capturing the complex topography and local climatic variations of the Italian landscape. The MERIDA HRES datasets, with their finer resolution, consistently outperformed ERA5 in these scenarios, highlighting their added value for applications requiring detailed, high-resolution meteorological data.

In conclusion, MERIDA HRES and MERIDA HRES OI offer valuable tools for improving the characterization of wildfire danger across Italy, benefiting from their higher spatial resolution and parametrization specific for the Italian territory. These datasets contribute to a deeper understanding of the meteorological conditions associated with wildfire danger and provide robust resources for studying climatological trends. Additionally, they support a wide range of stakeholders by aiding in the development of more effective risk management and mitigation strategies in response to the growing threat of wildfires.