The 2015 Paris Agreement aims to limit global warming below 2 °C and pursue efforts to even limit it to 1.5 °C relative to pre-industrial levels. Decision makers need reliable information on the impacts caused by these warming levels for climate mitigation and adaptation measures. We explore the changes in climate extremes, which are closely tied to economic losses and casualties, under 1.5 °C and 2 °C global warming and their scenario dependence using three sets of ensemble global climate model simulations. A warming of 0.5 °C (from 1.5 °C to 2 °C) leads to significant increases in temperature and precipitation extremes in most regions. However, the projected changes in climate extremes under both warming levels highly depend on the pathways of emissions scenarios, with different greenhouse gas (GHG)/aerosol forcing ratio and GHG levels. Moreover, there are multifold differences in several heavily polluted regions, among the scenarios, in the changes in precipitation extremes due to an additional 0.5 °C warming from 1.5 °C to 2 °C. Our results demonstrate that the chemical compositions of emissions scenarios, not just the total radiative forcing and resultant warming level, must be considered when assessing the impacts of global 1.5/2 °C warming.

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A B S T R A C T Based on the final analyses data (FNL) of the Global Forecasting System of the National Centers for Environment Prediction (NCEP) and the radiosonde data over the Tibetan Plateau, evolutions of two types of the Tibetan Plateau vortices, moving-off the plateau (Type A) and dying-out on the plateau (Type B), are investigated respectively. Compared to Type B vortices, the large-scale circulations associated with Type A vortices show stronger ridge to the north of the plateau and deeper trough near the Bay of Bengal at 500 hPa, and the southwesterly flow from the trough and the northwesterly flow from the ridge converge more intensively to the east of Type A vortices. Meanwhile, at 200 hPa the divergence on the right-hand side of the upper westerly jet is just over the vortices. The convergence at 500 hPa and divergence at 200 hPa provide favourable conditions for the development and eastward motion of the vortices. The diagnoses of the potential vorticity (PV) budgets reveal that in the developing stages of the two types of vortices, the vertical distribution of the atmospheric heat source determines both their intensity and the moving direction. In the decaying stage, the maintenance and eastward movement for Type A vortices mainly depend on the convergence of the strong northwesterly and southwesterly to the east of the vortices. For Type B vortices, the vertical PV flux divergence caused by the ascending motion around the vortices reduces the intensity of the vortices and is unfavourable for their eastward motion.

Abstract. Fine particulate matter (PM2.5) has altered the radiation balance on Earth and raised environmental and health risks for decades but has only been monitored widely since 2013 in China. Historical long-term PM2.5 records with high temporal resolution are essential but lacking for both research and environmental management. Here, we reconstruct a site-based PM2.5 dataset at 6 h intervals from 1960 to 2020 that combines long-term visibility, conventional meteorological observations, emissions, and elevation. The PM2.5 concentration at each site is estimated based on an advanced machine learning model, LightGBM, that takes advantage of spatial features from 20 surrounding meteorological stations. Our model's performance is comparable to or even better than those of previous studies in by-year cross validation (CV) (R2=0.7) and spatial CV (R2=0.76) and is more advantageous in long-term records and high temporal resolution. This model also reconstructs a 0.25∘ × 0.25∘, 6-hourly, gridded PM2.5 dataset by incorporating spatial features. The results show PM2.5 pollution worsens gradually or maintains before 2010 from an interdecadal scale but mitigates in the following decade. Although the turning points vary in different regions, PM2.5 mass concentrations in key regions decreased significantly after 2013 due to clean air actions. In particular, the annual average value of PM2.5 in 2020 is nearly the lowest since 1960. These two PM2.5 datasets (publicly available at https://doi.org/10.5281/zenodo.6372847, Zhong et al., 2022) provide spatiotemporal variations at high resolution, which lay the foundation for research studies associated with air pollution, climate change, and atmospheric chemical reanalysis.

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