Better understanding how fires respond to climate variability is an issue of current interest in light of ongoing climate change. However, evaluating the global‐scale temporal variability of fires in response to climate presents a challenge due to the intricate processes at play and the limitation of fire data. Here, we investigate the links between year‐to‐year variability of burned area (BA) and climate using BA data, the Fire Weather Index (FWI), and the Standardized Precipitation Evapotranspiration Index (SPEI) from 2001 to 2021 at ecoregion scales. Our results reveal complex spatial patterns in the dependence of BA variability on antecedent and concurrent weather conditions, highlighting where BA is mostly influenced by either FWI or SPEI and where the combined effect of both indicators must be considered. Our findings indicate that same‐season weather conditions have a more pronounced relationship with BA across various ecoregions, particularly in climatologically wetter areas. Additionally, we note that BA is also significantly associated with periods of antecedent wetness and coolness, with this association being especially evident in more arid ecoregions. About 60% of the interannual variations in BA can be explained by climatic variability in a large fraction (∼77%) of the world's burnable regions.

Synchronous extreme fire weather can significantly increase the probability of fire ignition and spread, posing compounding threats to fire management efforts and potentially overwhelming firefighting capabilities. While substantial evidence indicates that weather conditions conducive to wildfires will likely become more frequent with higher levels of global warming, changes in extreme fire weather synchronicity remain understudied. Here, we quantify the synchronicity of extreme fire weather in Europe by analysing historical data of the Canadian fire weather index (FWI) from 1981 to 2022 and projecting FWI future scenarios with temperature increases from 1 °C to 6 °C and precipitation changes from −40% to +60%. Our results highlight Central Europe (CEU) as a significant hotspot, with synchronicity increases of up to 389%, while the Mediterranean region could see increases up to 66%. These findings emphasize the growing need for enhanced cross-border coordination and proactive fire management strategies to address the rising likelihood of concurrent extreme fire weather conditions in a warming climate.

We assembled the first gridded burned area (BA) database of national wildfire data (ONFIRE), a comprehensive and integrated resource for researchers, non-government organisations, and government agencies analysing wildfires in various regions of the Earth. We extracted and harmonised records from different regions and sources using open and reproducible methods, providing data in a common framework for the whole period available (starting from 1950 in Australia, 1959 in Canada, 1985 in Chile, 1980 in Europe, and 1984 in the United States) up to 2021 on a common 1° × 1° grid. The data originate from national agencies (often, ground mapping), thus representing the best local expert knowledge. Key opportunities and limits in using this dataset are discussed as well as possible future expansions of this open-source approach that should be explored. This dataset complements existing gridded BA data based on remote sensing and offers a valuable opportunity to better understand and assess fire regime changes, and their drivers, in these regions. The ONFIRE database can be freely accessed at https://zenodo.org/record/8289245.

We assembled the first gridded burned area (BA) database of national wildfire data (ONFIRE), a comprehensive and integrated resource for researchers, non-government organisations, and government agencies analysing wildfires in various regions of the Earth. We extracted and harmonised records from different regions and sources using open and reproducible methods, providing data in a common framework for the whole period available (starting from 1950 in Australia, 1959 in Canada, 1985 in Chile, 1980 in Europe and 1984 in the United States) up to 2021 on a common 1° × 1° grid. The data originate from national agencies (often, ground mapping), thus representing the best local expert knowledge. Key opportunities and limits in using this dataset are discussed as well as possible future expansions of this open-source approach should be explored. This dataset complements existing gridded BA data based on remote sensing and offers a valuable opportunity to better understand and assess fire regime changes, and their drivers, in these regions. The ONFIRE database can be freely accessed at https://zenodo.org/record/8289245.

This contribution seeks to better understand recent changes in synchronous fire danger across Europe that can overwhelm fire suppression capacity. We analyze the spatio-temporal synchronicity of fire danger in Europe over the period 1979-2021 based on the Canadian Fire Weather Index, one of the most commonly used fire indices globally (FWI; Vitolo et al. 2020). The daily synchronicity index indicates the total area with a level of FWI above 50, that represents the extreme fire danger threshold as classified by the European Forest Fire Information System (EFFIS). The annual mean surface affected by synchronicity extreme fire danger increased by about 100000 km2 over the 42-year-long study period (i.e. 57% of the mean historical value). The expansion of synchronized fire potential can compromise fire management efforts.ReferencesVitolo, C., Di Giuseppe, F., Barnard, C., Coughlan, R., San-Miguel-Ayanz, J., Libertá, G., & Krzeminski, B. (2020). ERA5-based global meteorological wildfire danger maps. Scientific data, 7(1), 1-11.AcknowledgmentsWe acknowledge funding through the project ONFIRE, grant PID2021-123193OB-I00, funded by MCIN/AEI/ 10.13039/501100011033. A.G. thanks the Ministerio de Ciencia, Innovación y Universidades of Spain for PhD contract FPU19/06536.

Droughts create significant societal and environmental challenges. Accurate seasonal drought forecasting can provide early insights into potential impacts, serving as a vital resource for informed decision-making. An operational prototype with high spatial resolution is presented to predict seasonal meteorological drought in Spain (4SPAIN).The prediction system is inspired by an empirical method known as Ensemble Streamflow Prediction (ESP; Day, 1985). The model forecasts drought using the Standardized Precipitation Index (SPI6; Mckee et al., 1993) based on accumulated monthly precipitation data over 6 months (Turco et al., 2017). Due to the near real-time availability of ERA5 and its high similarity with the Spanish Meteorological Agency Spanish database (Torres-Vázquez et al., 2023), this database was chosen for the development and implementation of 4SPAIN. The validation of the model shows that it has predictive skill generally up to four-month lead time, whereas worse results come from predicting the wet season.Finally, an online operational prediction system called "Drought forecast monitor for Spain" was implemented. This low computational cost tool can provides users and competent authorities with an interactive interface to make early decisions based on updated information about the magnitude of the drought, uncertainty, alert level, and the probability of moderate drought occurrences (https://matv.shinyapps.io/app_4SPAIN/).ReferencesDay, G. N. (1985). Extended streamflow forecasting using NWSRFS. Journal of Water Resources Planning and Management, 111(2), 157–170.McKee, T. B., Doesken, N. J., y Kleist, J. (1993). The relationship of drought frequency and duration to time scales. In Eighth Conference on Applied Climatology, January, Anaheim, California, 1993, pages 17–22. American Meteorological Society.Torres-Vázquez, M. Á., Halifa-Marín, A., Montávez, J. P., & Turco, M. (2023). High resolution monitoring and probabilistic prediction of meteorological drought in a Mediterranean environment. Weather and Climate Extremes, 40, 100558.Turco, M., Ceglar, A., Prodhomme, C., Soret, A., Toreti, A., & Francisco, J. D. R. (2017). Summer drought predictability over Europe: empirical versus dynamical forecasts. Environmental research letters, 12(8), 084006.Acknowledgements A.G. thanks to the Ministerio de Ciencia, Innovación y Universidades of Spain for PhD contract FPU19/06536. M.T. acknowledges funding by the Spanish Ministry of Science, Innovation and Universities through the Ramón y Cajal Grant Reference RYC2019-027115-I and through the project ONFIRE, Grant PID2021-123193OB-I00, funded by MCIN/AEI/ 10.13039/501100011033 and by “ERDF A way of making Europe”.