Development of an Empirical- Statistical Framework for Attributing Fire Weather Extremes to Anthropogenic Climate Change

The occurrence of large wildfire events across the world in recent years has led to greater effort to understand the extent to which climate change may be altering the frequency of fireconducive meteorological conditions. However, to date, the relative paucity of climate change attribution studies focused on wildfire episodes, coupled with limited observational records, makes it difficult to draw solid and collective conclusions to better inform forest management strategies. The inter-study differences that emerge due to the choice of methodology and event definition are common to many attribution studies, and wildfire attribution is no exception. Here, we present a framework for the simultaneous attribution of multiple extreme fire weather episodes of using an empirical-statistical methodology. Key to this framework is the development of a common spatiotemporal definition for extreme fire weather events. Firstly, we fit a Generalized Extreme Value (GEV) distribution, scaled by global mean surface temperature, to the annual maxima of a series of reanalysis-derived fire danger indicators. Using global maps of risk ratios and percentage changes, we quantify the influence of recent global warming on the frequency and magnitude of fire weather extremes according to a common ‘event type’ definition, irrespective of their spatiotemporal occurrence. We subsequently conduct a collective attribution analysis of a series of recent exceptional fire weather events. We conclude with suggestions for further application to climate model ensembles and a discussion of the potential of our findings to inform decision-makers and practitioners.