Flash droughts have occurred frequently worldwide, with a rapid onset that challenges drought monitoring and forecasting capabilities. However, there is no consensus on whether flash droughts have become the new normal because slow droughts may also increase. In this study, we show that drought intensification rates have sped up over subseasonal time scales and that there has been a transition toward more flash droughts over 74% of the global regions identified by the Intergovernmental Panel on Climate Change Special Report on Extreme Events during the past 64 years. The transition is associated with amplified anomalies of evapotranspiration and precipitation deficit caused by anthropogenic climate change. In the future, the transition is projected to expand to most land areas, with larger increases under higher-emission scenarios. These findings underscore the urgency for adapting to faster-onset droughts in a warmer future.

Flash droughts refer to a type of droughts that have rapid intensification without sufficient early warning. To date, how will the flash drought risk change in a warming future climate remains unknown due to a diversity of flash drought definition, unclear role of anthropogenic fingerprints, and uncertain socioeconomic development. Here we propose a new method for explicitly characterizing flash drought events, and find that the exposure risk over China will increase by about 23% ± 11% during the middle of this century under a socioeconomic scenario with medium challenge. Optimal fingerprinting shows that anthropogenic climate change induced by the increased greenhouse gas concentrations accounts for 77% ± 26% of the upward trend of flash drought frequency, and population increase is also an important factor for enhancing the exposure risk of flash drought over southernmost humid regions. Our results suggest that the traditional drought-prone regions would expand given the human-induced intensification of flash drought risk.

Hyperresolution land surface modeling provides an unprecedented opportunity to simulate locally relevant water and energy cycle, but lateral surface and/or subsurface flows that are essential at fine scale are often neglected by most one‐dimensional land surface models (LSMs). To analyze effects of lateral flows across scales, a Conjunctive Surface‐Subsurface Process model, which considers soil moisture‐surface flow interaction and quasi‐three‐dimensional subsurface flow, is implemented over a mountainous HyperHydro test bed in southwestern USA at different resolutions. Validation over more than 70 International Soil Moisture Network stations shows that there are significant improvements in soil moisture simulations from 30 km to 4 km as finer soil property and precipitation data are used, with correlation increased by 5%–16% and error decreased by 5%. Lateral surface flow has a significant influence on surface soil moisture and ground evaporation even at coarse resolution. Effect of lateral subsurface flow on soil moisture is nontrivial at 1 km or finer resolution especially over wet areas. At 100 m resolution, topography‐induced lateral subsurface flow causes drier peaks and wetter valleys, decreases latent heat by 8% at peaks, while increases it by 12% at valleys. Furthermore, influences of lateral subsurface flow on ground evaporation and vegetation transpiration are more significant during dry season due to a stronger coupling between soil moisture and evapotranspiration. Therefore, it is worthy to incorporate lateral flow processes in hyperresolution LSMs to better represent water and energy heterogeneity even with limited hyperresolution meteorological and surface data.

High‐resolution modeling became popular in recent years due to the availability of multisource observations, advances in understanding fine‐scale processes, and improvements in computing facilities. However, modeling of hydrological changes over mountainous regions is still a great challenge due to the sensitivity of highland water cycle to global warming, tightly coupled hydrothermal processes, and limited observations. Here we show a successful high‐resolution (3 km) land surface modeling over the Sanjiangyuan region located in the eastern Tibetan plateau, which is the headwater of three major Asian rivers. By developing a new version of a Conjunctive Surface‐Subsurface Process model named as CSSPv2, we increased Nash‐Sutcliffe efficiency by 62–130% for streamflow simulations due to the introduction of a storage‐based runoff generation scheme, reduced errors by up to 31% for soil moisture modeling after considering the effect of soil organic matter on porosity and hydraulic conductivity. Compared with ERA‐Interim and Global Land Data Assimilation System version 1.0 reanalysis products, CSSPv2 reduced errors by up to 30%, 69%, 92%, and 40% for soil moisture, soil temperature, evapotranspiration, and terrestrial water storage change, respectively, as evaluated against in situ and satellite observations. Moreover, CSSPv2 well captured the elevation‐dependent ground temperature warming trends and the decreased frozen dates during 1979–2014, and significant increasing trends (p < 0.05) in evapotranspiration and terrestrial water storage during 1982–2011 and 2003–2014 respectively, while ERA‐Interim and Global Land Data Assimilation System version 1.0 showed no trends or even negative trends. This study implies the necessity of developing high‐resolution land surface models in realistically representing hydrological changes over highland areas that are sentinels to climate change.

Known as the “China Water Tower,” the Sanjiangyuan region over the eastern Tibetan Plateau experienced significant hydrological changes during the past few decades, potentially affecting the security of food, energy, and water over the downstream areas. Previous studies attributed the hydrological changes to global warming or land cover change, and obtained contrary conclusions on the dominant drivers. Here we show that natural climate change is mainly responsible for most hydrological changes (except low flows) over the Sanjiangyuan region, followed by the anthropogenic climate change, while land cover contributed the least. The newly developed Conjunctive Surface‐Subsurface Process version 2 land surface model that was evaluated comprehensively in the first part of this series was used to conduct a set of high‐resolution simulations driven by Coupled Model Intercomparison Project phase 5 detection and attribution experiment outputs with natural or anthropogenic forcings. By using an integrated hydroclimate attribution framework, anthropogenic climate change was found to cause significant ground temperature warming and soil frozen period shortening. However, significant decreasing trends in annual mean streamflow and high flows over the Yellow River headwater region and the terrestrial water storage averaged over the Sanjiangyuan region were mainly caused by natural climate change, with contribution by 57–97%. The contributions from land cover change are less than 11%. This study suggests that adaptations are more important than mitigations for the water resource management over the Sanjiangyuan and its downstream regions, because natural climate change outweighed human‐induced climate change in the headwater region.

The increasing occurrence of flash droughts with rapid onsets poses a great threat to food security and ecosystem productivity. While temporal trends in flash droughts have been extensively studied, the contributions of climate warming, vegetation greening, and the physiological effect of rising CO₂ to trends in flash drought characteristics remain unclear. Here we show there are significant increasing trends in flash drought frequency, duration, and intensity for most of China during 1961–2016. Warmer temperatures and vegetation greening increase evapotranspiration and decrease soil moisture, and explain 89% and 54% of the increasing frequency of flash drought respectively. Rising CO₂ concentrations reduce stomatal conductance, which acts to decelerate the increasing drought frequency trend by 18%, whereas the physiological effects of rising CO₂ on flash drought duration and intensity are smaller. Warming also outweighs vegetation greening for the increasing trends of flash drought duration and intensity over most of China, except North China. Our study highlights the role of climate warming in increasing the risk of flash droughts.