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Compound hot–dry events—co-occurring hot and dry extremes—frequently cause damages to human and natural systems, often exceeding separate impacts from heatwaves and droughts. Strong increases in the occurrence of these events are projected with warming, but associated uncertainties remain large and poorly understood. Here, using climate model large ensembles, we show that mean precipitation trends exclusively modulate the future occurrence of compound hot–dry events over land. This occurs because local warming will be large enough that future droughts will always coincide with at least moderately hot extremes, even in a 2 °C warmer world. By contrast, precipitation trends are often weak and equivocal in sign, depending on the model, region and internal climate variability. Therefore, constraining regional precipitation trends will also constrain future compound hot–dry events. These results help to assess future frequencies of other compound extremes characterized by strongly different trends in the drivers.Co-occurring hot and dry extremes are predicted to increase with global warming. Changes in precipitation will modulate the extent of these changes, highlighting the importance of understanding regional precipitation trends to prepare society and minimize impacts.

Extreme event attribution answers the question of whether and by how much anthropogenic climate change has contributed to the occurrence or magnitude of an extreme weather event. It is also used to link extreme event impacts to climate change. Impacts, however, are often related to multiple compounding climate drivers. Because extreme event attribution typically focuses on univariate assessments, these assessments might only provide a partial answer to the question of anthropogenic influence to a high-impact event. We present a theoretical extension to classical extreme event attribution for certain types of compound events. Based on synthetic data, we illustrate how the bivariate fraction of attributable risk (FAR) differs from the univariate FAR depending on the extremeness of the event as well as the trends in and dependence between the contributing variables. Overall, the bivariate FAR is similar in magnitude or smaller than the univariate FAR if the trend in the second variable is comparably weak and the dependence between both variables is moderate or high, a typical situation for temporally co-occurring heat waves and droughts. If both variables have similarly large trends or the dependence between both variables is weak, bivariate FARs are larger and are likely to provide a more adequate quantification of the anthropogenic influence. Using multiple climate model large ensembles, we apply the framework to two case studies, a recent sequence of hot and dry years in the Western Cape region of South Africa and two spatially co-occurring droughts in crop-producing regions in South Africa and Lesotho.

Climate-related disasters cause substantial disruptions to human societies. With climate change, many extreme weather and climate events are expected to become more severe and more frequent. The International Disaster Database (EM-DAT) records climate-related disasters associated with observed impacts such as affected people and economic damage on a country basis. Although disasters are classified into different meteorological categories, they are usually not linked to observed climate anomalies. Here, we investigate countrywide climate features associated with disasters that have occurred between 1950 and 2015 and have been classified as droughts, floods, heat waves, and cold waves using superposed epoch analysis. We find that disasters classified as heat waves are associated with significant countrywide increases in annual mean temperature of on average 0.13 ∘C and a significant decrease in annual precipitation of 3.2%. Drought disasters show positive temperature anomalies of 0.08 ∘C and a 4.8 % precipitation decrease. Disasters classified as droughts and heat waves are thus associated with significant annual countrywide anomalies in both temperature and precipitation. During years of flood disasters, precipitation is increased by 2.8 %. Cold wave disasters show no significant signal for either temperature or precipitation. We further find that climate anomalies tend to be larger in smaller countries, an expected behavior when computing countrywide averages. In addition, our results suggest that extreme weather disasters in developed countries are typically associated with larger climate anomalies compared to developing countries. This effect could be due to different levels of vulnerability, as a climate anomaly needs to be larger in a developed country to cause a societal disruption. Our analysis provides a first link between recorded climate-related disasters and observed climate data, which is an important step towards linking climate and impact communities and ultimately better constraining future disaster risk.

Satellite retrievals of information about the Earth’s surface are widely used to monitor global terrestrial photosynthesis and primary production and to examine the ecological impacts of droughts. Methods for estimating photosynthesis from space commonly combine information on vegetation greenness, incoming radiation, temperature and atmospheric demand for water (vapour-pressure deficit), but do not account for the direct effects of low soil moisture. They instead rely on vapour-pressure deficit as a proxy for dryness, despite widespread evidence that soil moisture deficits have a direct impact on vegetation, independent of vapour-pressure deficit. Here, we use a globally distributed measurement network to assess the effect of soil moisture on photosynthesis, and identify a common bias in an ensemble of satellite-based estimates of photosynthesis that is governed by the magnitude of soil moisture effects on photosynthetic light-use efficiency. We develop methods to account for the influence of soil moisture and estimate that soil moisture effects reduce global annual photosynthesis by ~15%, increase interannual variability by more than 100% across 25% of the global vegetated land surface, and amplify the impacts of extreme events on primary production. These results demonstrate the importance of soil moisture effects for monitoring carbon-cycle variability and drought impacts on vegetation productivity from space.Soil moisture effects can substantially reduce photosynthesis and amplify the impacts of extreme events on primary production, potentially leading to biases in satellite-based estimates of photosynthesis, suggests an analysis of ground-based measurements.

Compound events (CEs) are weather and climate events that result from multiple hazards or drivers with the potential to cause severe socio-economic impacts. Compared with isolated hazards, the multiple hazards/drivers associated with CEs can lead to higher economic losses and death tolls. Here, we provide the first analysis of multiple multivariate CEs potentially causing high-impact floods, droughts, and fires. Using observations and reanalysis data during 1980–2014, we analyse 27 hazard pairs and provide the first spatial estimates of their occurrences on the global scale. We identify hotspots of multivariate CEs including many socio-economically important regions such as North America, Russia and western Europe. We analyse the relative importance of different multivariate CEs in six continental regions to highlight CEs posing the highest risk. Our results provide initial guidance to assess the regional risk of CE events and an observationally-based dataset to aid evaluation of climate models for simulating multivariate CEs. Compound climate events such as floods and droughts together can cause severe socio-economic impacts. Here, the authors analyse global hazard pairs from 1980–2014 and find global hotspots for the occurrence of compound events.

Climate change amplifies dry and hot extremes, yet the mechanism, extent, scope, and temporal scale of causal linkages between dry and hot extremes remain underexplored. Here using the concept of system dynamics, we investigate cross-scale interactions within dry-to-hot and hot-to-dry extreme event networks and quantify the magnitude, temporal-scale, and physical drivers of cascading effects (CEs) of drying-on-heating and vice-versa, across the globe. We find that locations exhibiting exceptionally strong CE (hotspots) for dry-to-hot and hot-to-dry extremes generally coincide. However, the CEs differ strongly in their timescale of interaction, hydroclimatic drivers, and sensitivity to changes in the soil-plant-atmosphere continuum and background aridity. The CE of drying-on-heating in the hotspot locations reaches its peak immediately driven by the compounding influence of vapor pressure deficit, potential evapotranspiration, and precipitation. In contrast, the CE of heating-on-drying peaks gradually dominated by concurrent changes in potential evapotranspiration, precipitation, and net-radiation with the effect of vapor pressure deficit being strongly controlled by ecosystem isohydricity and background aridity. Our results help improve our understanding of the causal linkages and the predictability of compound extremes and related impacts. This study quantifies the scope, time scale, and physical mechanisms underlying the cascade effects of drying on heating and vice versa across the various ecosystems of the world.

Climate extremes such as droughts and heatwaves have a large impact on terrestrial carbon uptake by reducing gross primary production (GPP). While the evidence for increasing frequency and intensity of climate extremes over the last decades is growing, potential systematic adverse shifts in GPP have not been assessed. Using observationally-constrained and process-based model data, we estimate that particularly northern midlatitude ecosystems experienced a +10.6% increase in negative GPP extremes in the period 2000–2016 compared to 1982–1998. We attribute this increase predominantly to a greater impact of warm droughts, in particular over northern temperate grasslands (+95.0% corresponding mean increase) and croplands (+84.0%), in and after the peak growing season. These results highlight the growing vulnerability of ecosystem productivity to warm droughts, implying increased adverse impacts of these climate extremes on terrestrial carbon sinks as well as a rising pressure on global food security.The authors show increased negative extremes in gross primary productivity in northern midlatitude ecosystems, particularly over grasslands and croplands, attributed to impacts of warm droughts. This highlights the vulnerability of terrestrial carbon sinks and food security to increasing extreme events.

Land ecosystems absorb on average 30 per cent of anthropogenic carbon dioxide (CO 2 ) emissions, thereby slowing the increase of CO 2 concentration in the atmosphere 1 . Year-to-year variations in the atmospheric CO 2 growth rate are mostly due to fluctuating carbon uptake by land ecosystems 1 . The sensitivity of these fluctuations to changes in tropical temperature has been well documented 2 – 6 , but identifying the role of global water availability has proved to be elusive. So far, the only usable proxies for water availability have been time-lagged precipitation anomalies and drought indices 3 – 5 , owing to a lack of direct observations. Here, we use recent observations of terrestrial water storage changes derived from satellite gravimetry 7 to investigate terrestrial water effects on carbon cycle variability at global to regional scales. We show that the CO 2 growth rate is strongly sensitive to observed changes in terrestrial water storage, drier years being associated with faster atmospheric CO 2 growth. We demonstrate that this global relationship is independent of known temperature effects and is underestimated in current carbon cycle models. Our results indicate that interannual fluctuations in terrestrial water storage strongly affect the terrestrial carbon sink and highlight the importance of the interactions between the water and carbon cycles. The growth rate of global atmospheric CO 2 concentration is faster in drier years, independently of temperature; this relationship is underestimated in current carbon cycle models.

Societally relevant weather impacts typically result from compound events, which are rare combinations of weather and climate drivers. Focussing on four event types arising from different combinations of climate variables across space and time, here we illustrate that robust analyses of compound events — such as frequency and uncertainty analysis under present-day and future conditions, event attribution to climate change, and exploration of low-probability-high-impact events — require data with very large sample size. In particular, the required sample is much larger than that needed for analyses of univariate extremes. We demonstrate that Single Model Initial-condition Large Ensemble (SMILE) simulations from multiple climate models, which provide hundreds to thousands of years of weather conditions, are crucial for advancing our assessments of compound events and constructing robust model projections. Combining SMILEs with an improved physical understanding of compound events will ultimately provide practitioners and stakeholders with the best available information on climate risks. The authors show that robust analyses of high-impact compound weather and climate events require many samples. Thus, they argue that large ensemble climate model simulations should be used to provide the best available information on climate risks.

The emergence of abrupt shift from drought to downpour has attracted widespread attention in recent years, with particularly disastrous consequences in low‐income regions. However, the spatiotemporal evolution and poverty exposure to such drought‐to‐downpour events remain poorly understood. Here, we investigate the connection between poverty and drought‐to‐downpour events based on three data products and climate models on a global scale. We find that the drought‐to‐downpour events increased by 24%–48% in the poorest 20% of the world's population from 1980 to 2010. The drought‐to‐downpour events do not appear to be occurring more frequently in most regions globally, just affecting regions with higher poverty rates more frequently, especially in African countries. The exposure inequality remains under future socioeconomic pathways, with a nearly fivefold increase in the exposure for the poorer populations. Poverty exposure to more frequent drought‐to‐downpour events demands greater support for climate adaptation in low‐income countries to reduce poverty and inequality. Plain Language Summary Many regions have suffered greatly from recent occurrences of abrupt shift from drought to downpour, suggesting that the emerging threat is a global challenge. Such drought‐to‐downpour events pose challenges to water infrastructures in developed countries, let alone those poor countries with limited adaptation capacity and resources. However, the connection between the drought‐to‐downpour events and poverty incidence remains poorly understood. Here, we show that such drought‐to‐downpour events experienced by the poorest 20% of the world's population increased significantly by 24%–48% from 1980 to 2010. Such a significant increase, however, is not observed for the remaining wealthiest 80%. The drought‐to‐downpour events do not appear to be occurring more frequently in most global regions, just affecting regions with higher poverty rates more frequently, especially in African countries. Climate projections show that such inequality would remain in a warming climate. Our results highlight the urgency to provide greater support for climate adaptation in low‐income countries to reduce poverty and inequality. Key Points The connection between poverty incidence and drought‐to‐downpour weather whiplashes is uncovered on a global scale The drought‐to‐downpour events increased by 24%–48% in the poorest 20% of the world's population from 1980 to 2010 The drought‐to‐downpour events do not appear to be occurring more frequently in most global regions, just affecting regions with higher poverty rates more frequently