The quantification of climate change impacts on hydrology is subjected to multiple uncertainty sources. Large ensembles of hydrological simulations based on multimodel ensembles (MMEs) have been commonly applied to represent overall uncertainty of hydrological impacts. However, as increasing numbers of global climate models (GCMs) are being developed, how many GCMs in MMEs are sufficient to characterize overall uncertainty is not clear. Therefore, this study investigates the influences of GCM quantity on quantifying overall uncertainty and uncertainty contributions of multiple sources in hydrological impacts. Large ensembles of hydrological simulations are obtained through the permutation of 3 greenhouse gas emission scenarios, 22 GCMs, 6 downscaling techniques, 5 hydrological models (HMs), and 5 sets of HM parameters, which enables to decompose uncertainty components using analysis of variance. The influences of GCM quantity are investigated by repeatedly conducting uncertainty decomposition for hydrological simulations from subsets with different numbers of GCMs. The results show that GCMs are the leading uncertainty sources in evaluating changes in annual and peak streamflows, while for changes in low flow, other uncertainty sources except HM parameters also have large contributions to overall uncertainty. Furthermore, on the condition of using no more than five GCMs, there are large possibilities that the overall uncertainty and GCMs' uncertainty contribution are underestimated. Using around 10 GCMs can ensure that the median of different combinations generates similar uncertainty components as the whole ensemble. Therefore, it is recommended to use at least 10 GCMs in studies of climate change impacts on hydrology to thoroughly quantify uncertainty.

Compound drought and heatwave (CDHW) events have received considerable attention in recent years due to their devastating effects on human society and ecosystem. In this study, we systematically investigated the changes of CDHW events in multi‐spatiotemporal scales for historical period (1951–2014) and four future scenarios (2020–2100) (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5) over global land by using Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The responses of the CDHW events to the changes of maximum air temperature and the climatic water balance variable are also examined. The results show that the multi‐model ensembles project a significant increasing trend in CDHW characteristics over almost all global lands under SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5, especially across northern North‐America, Caribbean, Mediterranean and Russian‐Arctic, there is a stronger increasing trend. A significantly increasing CDHW risk will occur across most global land for the medium to long term future without aggressive adaptation and mitigation strategies. The results of path analysis suggest that temperature is the dominant factor influencing CDHW events. Additionally, higher sensitivity of CDHW events to global warming will occur in the future. Particularly, each 1°C global warming increases the duration of the CDHW events by 3 days in the historical period, but by about 10 days in the future period. Overall, this study improves our understanding in the projection of CDHW events and the impacts of climate drivers to the CDHW events under various future scenarios, which could provide supports about the risk assessment, adaptation and mitigation strategies under climate change.

Meteorological to hydrological drought propagation has been widely studied to reflect the relationship between these drought categories and better understand drought mechanisms. However, global warming may alter the drought propagation features, which are not fully understood. This study aims to investigate changes in meteorological and hydrological drought conditions, especially their propagation features in 1.5–3.0°C warmer climates for 8,655 watersheds globally. First, the three‐month scale standardized precipitation index and the standardized runoff index are calculated based on the precipitation simulated by the 15 global climate models and the runoff simulated by the four hydrological models, respectively. Drought events are then identified using the run theory, followed by the calculation of drought propagation features (i.e., pooling, lag, and lengthening) for matched meteorological and hydrological droughts. As a result, both meteorological and hydrological drought conditions (i.e., duration and severity) would relieve in warmer climates due to increased precipitation for regions excluding Western North America, South America, the Mediterranean, Southern Africa, East Asia, and Australia. However, the drought conditions would be more severe during drought propagation from meteorological to hydrological droughts over most regions. During drought propagation, the worsening drought conditions over half of the regions would be more serious first and then relieved with the rising temperature. These results indicate that efforts to slow down global warming can suppress the deterioration of drought conditions in the propagation.

The Paris Agreement sets a long-term temperature goal to hold global warming to well below 2.0 ^∘C and strives to limit it to 1.5 ^∘C above preindustrial levels. Droughts with either intense severity or a long persistence could both lead to substantial impacts such as infrastructure failure and ecosystem vulnerability, and they are projected to occur more frequently and trigger intensified socioeconomic consequences with global warming. However, existing assessments targeting global droughts under 1.5 and 2.0 ^∘C warming levels usually neglect the multifaceted nature of droughts and might underestimate potential risks. This study, within a bivariate framework, quantifies the change in global drought conditions and corresponding socioeconomic exposures for additional 1.5 and 2.0 ^∘C warming trajectories. The drought characteristics are identified using the Standardized Precipitation Evapotranspiration Index (SPEI) combined with the run theory, with the climate scenarios projected by 13 Coupled Model Inter-comparison Project Phase 5 (CMIP5) global climate models (GCMs) under three representative concentration pathways (RCP 2.6, RCP4.5 and RCP8.5). The copula functions and the most likely realization are incorporated to model the joint distribution of drought severity and duration, and changes in the bivariate return period with global warming are evaluated. Finally, the drought exposures of populations and regional gross domestic product (GDP) under different shared socioeconomic pathways (SSPs) are investigated globally. The results show that within the bivariate framework, the historical 50-year droughts may double across 58 % of global landmasses in a 1.5 ^∘C warmer world, while when the warming climbs up to 2.0 ^∘C, an additional 9 % of world landmasses would be exposed to such catastrophic drought deteriorations. More than 75 (73) countries' populations (GDP) will be completely affected by increasing drought risks under the 1.5 ^∘C warming, while an extra 0.5 ^∘C warming will further lead to an additional 17 countries suffering from a nearly unbearable situation. Our results demonstrate that limiting global warming to 1.5 ^∘C, compared with 2 ^∘C warming, can perceptibly mitigate the drought impacts over major regions of the world.

Atmospheric moisture holding capacity increases with temperature by about 7% per °C according to the Clausius‐Clapeyron relationship. Thermodynamically then, precipitation intensity should exponentially intensify and thus worsen flood conditions as the climate warms. However, regional and global analyses often report a nonmonotonic (hook) scaling of precipitation and runoff, in which extremes strengthen with rising temperature up to a maximum or peak point (T_pp) and decline thereafter. The underlying cause of this hook structure is not yet well‐understood, and whether it may shift and/or regulate storm runoff extremes under anthropogenic climate warming remains unknown. Here, we examine temperature scaling of precipitation and storm runoff extremes under different climate conditions using observations and large ensemble hydroclimatic simulations over mainland China. In situ observations suggest a spatially homogeneous, negative response of relative humidity to warming climates over 34.6% of the land area, and the remaining hook‐dominated regions usually show a colder T_pp than that of precipitation or storm runoff extremes. The precipitation and streamflow series over mainland China's catchments throughout the 21st century are projected by a model cascade chain under a high‐end emission scenario (RCP 8.5), which involves 31 CMIP5 climate models, 11 CMIP6 climate members, a daily bias correction method, and four lumped conceptual hydrological models. The CMIP5 ensemble projects that the hook structures shift toward warmer temperature bins, resulting in 10%–30% increases in storm runoff extremes over mainland China, while the CMIP6 ensemble projects more severe flood conditions in future warming climates.