Significance: We project drought losses in China under global warming of 1.5 °C and 2.0 °C. To assess future drought losses, we project the regional gross domestic product under shared socioeconomic pathways instead of using a static socioeconomic scenario. We identify increasing precipitation and evapotranspiration patterns. With increasing drought intensity and areal coverage across China, drought losses will increase considerably. The estimated losses in a sustainable development pathway at 1.5 °C warming will be 10 times higher than in the reference period 1986–2005 and three times higher than in 2006–2015. Yet, climate change mitigation, limiting the temperature increase to 1.5 °C, can considerably reduce the annual drought losses in China, compared with 2.0 °C warming.

Beginning in 2016, all couples in China were allowed to have two children without any restrictions. This paper provides population and economic projections under five shared socioeconomic pathways (SSPs) and three fertility policies. By replacing the one‐child policy with a two‐child policy, the population is predicted to continue growing until 2025‐2035, with a peak of approximately 1.39‐1.42 billion, and then to decline under four SSPs, with the exception of the fragmented world SSP3. As a result, the two‐child policy will lead to mitigation of the pressure from labour shortages and ageing problems to a certain extent. In addition, an increase in working‐age people with higher education level relative to projections based on the one‐child policy will lead to an increase in gross domestic product by approximately 38.1%‐43.9% in the late 21^st century. However, labour shortages and ageing problems are inevitable, and the proportion of elderly in China will be greater than 14% and 21% by approximately 2025 and 2035, respectively. Full liberalization of fertility is expected to reduce the share of elderly people by 0.7%‐1.0% and to lead to an increase in gross domestic product by 5.3%‐6.7% relative to the two‐child policy in the late 21^st century. The full liberalization of fertility policies is recommended, supplemented by increases in pension and child‐rearing funds, improvement in the quality of health services for females and children, and extension of compulsory education to meet the needs of an aged society.

The increase in surface air temperature in China has been faster than the global rate, and more high temperature spells are expected to occur in future. Here we assess the annual heat-related mortality in densely populated cities of China at 1.5 °C and 2.0 °C global warming. For this, the urban population is projected under five SSPs, and 31 GCM runs as well as temperature-mortality relation curves are applied. The annual heat-related mortality is projected to increase from 32.1 per million inhabitants annually in 1986–2005 to 48.8–67.1 per million for the 1.5 °C warming and to 59.2–81.3 per million for the 2.0 °C warming, taking improved adaptation capacity into account. Without improved adaptation capacity, heat-related mortality will increase even stronger. If all 831 million urban inhabitants in China are considered, the additional warming from 1.5 °C to 2 °C will lead to more than 27.9 thousand additional heat-related deaths, annually.

Land evaporation (ET) plays a crucial role in the hydrological and energy cycle. However, the widely used model-based products, even though helpful, are still subject to great uncertainties due to imperfect model parameterizations and forcing data. The lack of available observed data has further complicated estimation. Hence, there is an urgency to define the global proxy land ET with lower uncertainties for climate-induced hydrology and energy change. This study has combined three existing model-based products – the fifth-generation ECMWF reanalysis (ERA5), Global Land Data Assimilation System Version 2 (GLDAS2), and the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) – to obtain a single framework of a long-term (1980–2017) daily ET product at a spatial resolution of 0.25^∘. Here, we use the reliability ensemble averaging (REA) method, which minimizes errors using reference data, to combine the three products over regions with high consistencies between the products using the coefficient of variation (CV). The Global Land Evaporation Amsterdam Model Version 3.2a (GLEAM3.2a) and flux tower observation data were selected as the data for reference and evaluation, respectively. The results showed that the merged product performed well over a range of vegetation cover scenarios. The merged product also captured the trend of land evaporation over different areas well, showing the significant decreasing trend in the Amazon Plain in South America and Congo Basin in central Africa and the increasing trend in the east of North America, west of Europe, south of Asia and north of Oceania. In addition to demonstrating a good performance, the REA method also successfully converged the models based on the reliability of the inputs. The resulting REA data can be accessed at https://doi.org/10.5281/zenodo.4595941 (Lu et al., 2021).