Compound weather and climate events are combinations of climate drivers and/or hazards that contribute to societal or environmental risk. Studying compound events often requires a multidisciplinary approach combining domain knowledge of the underlying processes with, for example, statistical methods and climate model outputs. Recently, to aid the development of research on compound events, four compound event types were introduced, namely (a) preconditioned, (b) multivariate, (c) temporally compounding, and (d) spatially compounding events. However, guidelines on how to study these types of events are still lacking. Here, we consider four case studies, each associated with a specific event type and a research question, to illustrate how the key elements of compound events (e.g., analytical tools and relevant physical effects) can be identified. These case studies show that (a) impacts on crops from hot and dry summers can be exacerbated by preconditioning effects of dry and bright springs. (b) Assessing compound coastal flooding in Perth (Australia) requires considering the dynamics of a non‐stationary multivariate process. For instance, future mean sea‐level rise will lead to the emergence of concurrent coastal and fluvial extremes, enhancing compound flooding risk. (c) In Portugal, deep‐landslides are often caused by temporal clusters of moderate precipitation events. Finally, (d) crop yield failures in France and Germany are strongly correlated, threatening European food security through spatially compounding effects. These analyses allow for identifying general recommendations for studying compound events. Overall, our insights can serve as a blueprint for compound event analysis across disciplines and sectors.

The interaction between co-occurring drought and hot conditions is often particularly damaging to crop's health and may cause crop failure. Climate change exacerbates such risks due to an increase in the intensity and frequency of dry and hot events in many land regions. Hence, here we model the trivariate dependence between spring maximum temperature and spring precipitation and wheat and barley yields over two province regions in Spain with nested copulas. Based on the full trivariate joint distribution, we (i) estimate the impact of compound hot and dry conditions on wheat and barley loss and (ii) estimate the additional impact due to compound hazards compared to individual hazards. We find that crop loss increases when drought or heat stress is aggravated to form compound dry and hot conditions and that an increase in the severity of compound conditions leads to larger damage. For instance, compared to moderate drought only, moderate compound dry and hot conditions increase the likelihood of crop loss by 8 % to 11 %, while when starting with moderate heat, the increase is between 19 % to 29 % (depending on the cereal and region). These findings suggest that the likelihood of crop loss is driven primarily by drought stress rather than by heat stress, suggesting that drought plays the dominant role in the compound event; that is, drought stress is not required to be as extreme as heat stress to cause similar damage. Furthermore, when compound dry and hot conditions aggravate stress from moderate to severe or extreme levels, crop loss probabilities increase 5 % to 6 % and 6 % to 8 %, respectively (depending on the cereal and region). Our results highlight the additional value of a trivariate approach for estimating the compounding effects of dry and hot extremes on crop failure risk. Therefore, this approach can effectively contribute to design management options and guide the decision-making process in agricultural practices.

Human-induced climate change is increasing the incidence of fire events and associated impacts on livelihood, biodiversity, and nature across the world. Understanding current and projected fire activity together with its impacts on ecosystems is crucial for evaluating future risks and taking actions to prevent such devastating events. Here we focus on fire weather as a key driver of fire activity. Fire weather products that have a global homogenous distribution in time and space provide many advantages to advance fire science and evaluate future risks. Therefore, in this study we calculate and provide for the first time the Canadian Fire Weather Index (FWI) with all available simulations of the 6th phase of the Coupled Model Intercomparison Project (CMIP6). Furthermore, we expand its regional applicability by combining improvements to the original algorithm for the FWI from several packages. A sensitivity analysis of the default version versus our improved version shows significant differences in the final FWI. With the improved version, we calculate the FWI using average relative humidity in one case and minimum relative humidity in another case. We provide the data for both cases while recommending the one with minimum relative humidity for studies focused on actual FWI values and the one with average relative humidity for studies requiring larger ensembles. The following four annual indicators, (i) maximum value of the FWI (fwixx), (ii) number of days with extreme fire weather (fwixd), (iii) length of the fire season (fwils), and (iv) seasonal average of the FWI (fwisa), are made available and are illustrated here. We find that, at a global warming level of 3 ^∘C, the mean fire weather would increase on average by at least 66 % in duration and frequency, while associated 1-in-10-year events would approximately triple in duration and increase by at least 31 % in intensity. Ultimately, this new fire weather dataset provides a large ensemble of simulations to understand the potential impacts of climate change spanning a range of shared socioeconomic narratives with their radiative forcing trajectories over 1850–2100 at annual and 2.5^∘ × 2.5^∘ resolutions. The produced full global dataset is a freely available resource at https://doi.org/10.3929/ethz-b-000583391 (Quilcaille and Batibeniz, 2022) for fire danger studies and beyond, which highlights the need to reduce greenhouse gas emissions for reducing fire impacts.

Tropical fire activity closely follows the co-occurrence of multiple climate stressors. Yet, it remains challenging to quantify how changes in climate alter the likelihood of fire risks associated with compound events. Recent abrupt changes in fire regimes in iconic landscapes in Brazil (namely the Pantanal and Xingu) provide a key opportunity to evaluate how extremely dry and hot conditions, both together and individually, have influenced the probability of large fires. Here we quantify the relationships between climate and fire across these regions and provide evidence on the extent to which fire risk and the associated impacts could be constrained if anthropogenic global warming is limited. We investigate the burned area, differentiating between fire types according to land use (forest fires, savanna fires, farming fires and grassland and wetland fires), and derive present and future fire risks linked to multiple climate variables. We show that concurrent air dryness (high vapour-pressure deficit (VPD)) and low precipitation have driven fire occurrence in both Xingu and the Pantanal, with VPD playing a dominant role. Historical climatic change has already increased compound event-related (CE-related) fire risks of all fire types (5%–10%), and these risks are likely to increase in the future due to global warming. The likelihood of CE-related increase in fire risk may be reduced by up to 14.4% if global warming is constrained to +1.5 °C instead of +3 °C. Nevertheless, substantially increased CE-related fire risks are still expected even if restricting global mean warming to 1.5 °C, particularly in the Pantanal. We thus conclude that climate action should be coordinated with environmental protection to reduce ignition sources and promote effective conservation measures to preserve these biomes.