Machine learning (ML) is increasingly used in environmental research to process large data
sets and decipher complex relationships between system variables. However, due to the …

Artificial intelligence has been applied in wildfire science and management since the 1990s,
with early applications including neural networks and expert systems. Since then, the field …

Key message Wildfire danger and burnt areas should increase over the century in southern
Europe, owing to climate warming. Fire-prone area expansion to the north and to …

The observed trend towards warmer and drier conditions in southern Europe is projected to
continue in the next decades, possibly leading to increased risk of large fires. However, an …

Most bias correction algorithms used in climatology, for example quantile map**, are
applied to univariate time series. They neglect the dependence between different variables …

Forest fires are a persistent global problem, causing devastating consequences such as loss
of human lives, harm to the environment, and substantial economic losses. To mitigate these …

This study quantifies how changes in temperature and precipitation would influence the
intensity and duration of extreme fires across Europe. The analysis explores the impact of a …

Forest fires are a serious environmental hazard in southern Europe. Quantitative
assessment of recent trends in fire statistics is important for assessing the possible shifts …

Forests cover over a third of the total land area of Europe. In recent years, large forest fires
have repeatedly affected Europe, in particular the Mediterranean countries. Fire danger is …

We analyse the observed climate-driven changes in summer wildfires and their future
evolution in a typical Mediterranean environment (NE Spain). By analysing observed climate …