Heatwaves challenge electricity systems relying on wind energy for renewable power. However, the global availability of wind power during heatwaves remains unknown. Here, we provide a global assessment of wind power dynamics during heatwaves using weather reanalysis data from 1980 to 2023. Our results show the global land area experiencing wind power shortages during heatwaves has risen by 6.3% per decade, reaching 60% by 2023. Australia, Northern Asia, and Europe are particularly vulnerable, with wind power decreasing by 30–50%. Conversely, regions such as the Amazon, the Great Plains in North America, and Central Africa experience slight increases in wind power during heatwaves. 75.5% of land areas show a negative response between maximum temperatures and wind speeds. Our findings highlight the growing risk of concurrent heatwaves and wind power shortages, underscoring the need for targeted regional strategies to ensure the reliability of wind energy systems under a warming climate.

Reanalysis datasets, such as ERA5, are essential for climate research, offering comprehensive spatiotemporal coverage. However, their accuracy needs thorough evaluation for effective regional application, particularly in areas with complex topography like the Poyang Lake Basin (PLB), China’s largest freshwater lake. This study evaluated ERA5’s accuracy in simulating near-surface air temperature and precipitation in the PLB, using data from 24 meteorological stations. Key metrics, such as the correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) were applied across daily, monthly, seasonal, and annual scales. The results show that ERA5 performs well for daily mean temperature, with daily R values above 0.98 and RMSEs ranging from 0.95 °C to 3.11 °C. Its highest accuracy was in February and March, with R values exceeding 0.95, and seasonal trends were best captured in spring and autumn (R > 0.99). However, ERA5’s performance for precipitation was less accurate, with daily R values between 0.578 and 0.687 and RMSEs between 8.58 mm and 11.10 mm. ERA5 consistently overestimated precipitation, particularly during 1980–2003. These findings highlight ERA5’s strengths in temperature modeling and its limitations in precipitation, providing insights for identifying climate events and improving climate simulation in the PLB.

Surface ozone has emerged as a concerning pollutant in Beijing, China. This study assessed ozone pollution and its health impacts in Beijing using ground (35 stations) and satellite data (2014–2023). Temporal trends were analyzed across various temporal scales, while spatial variability was evaluated using integrated ground and satellite-derived continuous data. Health impacts were quantified via a log-linear concentration–response model. Results show that for ozone concentrations during the post-pandemic period (2019–2023, covering the onset of COVID-19 in 2019 and the period following), daytime concentrations decreased by 6.8 μg/m³, but nighttime concentrations increased by 5.4 μg/m³. Spatially, ozone concentrations were higher in urban areas than in suburban areas in summer, but the reverse occurred in other seasons. Satellite data revealed broader Grade II (160 μg/m³) exceedance variability (3.0–20.3%) compared to station estimates (15.3–18.7%). Health impact assessments indicated that achieving the Grade I standard (100 μg/m³) could prevent approximately 576 (95% CI: 317–827) all-cause deaths and 294 (95% CI: 111–467) cardiovascular deaths per year, which is 3.5 times more than the reductions from meeting the Grade II standard (160 μg/m³). These findings underscore the need for adaptive ozone controls and tiered mitigation strategies to reduce health risks in Beijing.