Understanding the effects of climate variability and reservoir operation on runoff is important for shipping, irrigation and water supply services, especially during extreme drought years. After the operation of the Three Gorges Dam (TGD) began, the discharge processes in the mid-lower reaches of the Yangtze River were completely different from those during the pre-dam period. The measured hydrological data and the Mike 11-HD model were used to estimate the contributions of the TGD operation and climate variability to the variation in discharge during extreme drought years. The results are as follows: under the effects of the TGD operation and extreme drought, the special phenomenon of a “positive discharge anomaly in drought season and negative discharge anomaly in flood season” occurred compared with the conditions in the pre-dam period. During the flood season, the contributions of climate variation (TGD operation) to the changes in streamflow from Yichang station to Datong station were 86.6% (13.4%) and 80.7% (19.7%) in 2006 and 64.8% (35.2%) and 71.3% (28.7%) in 2011. During the dry season, the values were 81.2% (18.8%) and 93.9% (6.1%) in 2006 and 59.9% (40.1%) and 72.9% (27.1%) in 2011. Clearly, climate variation was the main reason for the variation in seasonal runoff. Furthermore, even in the 156 m and 175 m impoundments, climate variation was the dominant factor.

Climate projections are essential for decision-making but contain non-negligible uncertainty. To reduce projection uncertainty over Asia, where half the world’s population resides, we develop emergent constraint relationships between simulated temperature (1970–2014) and precipitation (2015–2100) growth rates using 27 CMIP6 models under four Shared Socioeconomic Pathways. Here we show that, with uncertainty successfully narrowed by 12.1–31.0%, constrained future precipitation growth rates are 0.39 ± 0.18 mm year⁻¹ (29.36 mm °C⁻¹, SSP126), 0.70 ± 0.22 mm year⁻¹ (20.03 mm °C⁻¹, SSP245), 1.10 ± 0.33 mm year⁻¹ (17.96 mm °C⁻¹, SSP370) and 1.42 ± 0.35 mm year⁻¹ (17.28 mm °C⁻¹, SSP585), indicating overestimates of 6.0–14.0% by the raw CMIP6 models. Accordingly, future temperature and total evaporation growth rates are also overestimated by 3.4–11.6% and −2.1–13.0%, respectively. The slower warming implies a lower snow cover loss rate by 10.5–40.2%. Overall, we find the projected increase in future water availability is overestimated by CMIP6 over Asia.

The complete or partial collapse of the forests of Amazonia is consistently named as one of the top ten possible tipping points of Planet Earth in a changing climate. However, apart from a few observational studies that showed increased mortality after the severe droughts of 2005 and 2010, the evidence for such collapse depends primarily on modelling. Such studies are notoriously deficient at predicting the rainfall in the Amazon basin and how the vegetation interacts with the rainfall is poorly represented. Here, we use long-term surface-based observations of the air temperature and rainfall in Amazonia to provide a constraint on the modelled sensitivity of temperature to changes in precipitation. This emergent constraint also allows us to significantly constrain the likelihood of a forest collapse or dieback. We conclude that Amazon dieback under IPCC scenario RCP8.5 (crossing the tipping point) is not likely to occur in the twenty-first century.