In summertime, eastern China experiences severe ozone pollution. Stratosphere-to-troposphere transport (STT), as the primary natural source of tropospheric ozone, may have a non-negligible contribution to ground-level ozone. Rossby wave breaking (RWB) is a leading mechanism that triggers STT, which can be categorized as anticyclonic wave breakings (AWBs) and cyclonic wave breakings (CWBs). This study uses an objective method to diagnose AWBs and CWBs and to investigate their influence on the surface ozone in eastern China using ground-based ozone observations, satellite ozone data from AIRS, a stratospheric ozone tracer simulated by CAM-chem, and meteorological fields from MERRA-2. The results indicate that AWBs occur mainly and frequently over northeast China, while CWBs occur mostly over the northern Sea of Japan. STTs triggered by AWBs mainly have sinking areas over the North China Plain, increasing the ground-level ozone concentrations by 5–10 ppbv in eastern China. The downwelling zones in the CWBs extend from Mongolia to the East China Sea, potentially causing an elevation of 5–10 ppbv of ozone in both central and eastern China. This study gives an overview of the impacts of AWBs and CWBs on surface ozone in eastern China and helps to improve our understanding of summertime ozone pollution in eastern China.

Water vapor in the upper troposphere and lower stratosphere plays a crucial role for climate, affecting radiation, chemistry, and atmospheric dynamics. This study applies a simplified Lagrangian method to reconstruct stratospheric water vapor based on satellite observations from the Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) and the Aura Microwave Limb Sounder (MLS). The objective is to improve understanding of moisture enhancements in the Asian and North American monsoons and to identify the key factors contributing to reconstruction biases. The performance of Lagrangian reconstructions significantly improves with the size of trajectory ensembles but exhibits a general dry bias. The reconstruction represents the summertime local water vapor maximum well in the Asian monsoon, particularly above the tropopause, but not in the North American monsoon. The main dehydration region diagnosed from trajectories indicates that water vapor in the Asian monsoon is predominantly controlled by local tropopause temperatures. The dry bias in reconstructions below the tropopause over the Asian monsoon shows a positive correlation with convection intensity, particularly in the western part of the monsoon region, suggesting that underestimated moistening from convection may contribute to this bias. Water vapor mixing ratios in the North American monsoon are largely influenced by long-range transport from dehydrated regions over southern Asia and additional local moistening. The limited performance of reconstructions in the North American monsoon is therefore likely linked to underestimation of local convection or uncertainties in long-range transport.

Water vapor in the Upper Troposphere and Lower Stratosphere (UTLS) plays a crucial role in climate feedback by influencing radiation, chemistry, and atmospheric dynamics. The amount of water vapor entering the stratosphere is sensitive to cold point temperatures (CPT), making Northern Hemisphere summer monsoons more favorable for transporting water vapor into the stratosphere. This study uses a Lagrangian method to reconstruct water vapor over the Asian (ASM) and North American (NAM) monsoons, investigating their contributions to stratospheric water vapor. The Lagrangian method tracks air parcels and identifies the coldest temperature along each trajectory, contrasting with local methods that rely on vertical temperature profiles. The reconstructed water vapor fields are validated against satellite observations from SAGE III/ISS and NASA’s Aura MLS. SAGE III/ISS shows stronger moisture enhancements than MLS, but both datasets reveal similar water vapor anomalies within the ASM and NAM anticyclones. Although the Lagrangian method is dry-biased compared to observations, it effectively reconstructs UTLS water vapor (correlation coefficient 0.75), capturing moist anomalies in the ASM but performing less well in the NAM. Our analysis shows that, large-scale cold point tropopause temperatures in the vicinity of the monsoons primarily drive the moisture anomalies, with NAM water vapor significantly influenced by long-range transport from South Asia. Some convection-related processes, such as east-west shifts within the ASM, are not fully captured due to unresolved temperature variability in ERA5 and missing ice microphysics. Despite biases and computational challenges, the Lagrangian method provides valuable insights into UTLS water vapor transport.

Water vapor in the Upper Troposphere and Lower Stratosphere (UTLS) plays a crucial role in climate feedback by influencing radiation, chemistry, and atmospheric dynamics. The amount of water vapor entering the stratosphere is sensitive to cold point temperatures (CPT), making Northern Hemisphere summer monsoons more favorable for transporting water vapor into the stratosphere. This study uses a Lagrangian method to reconstruct water vapor over the Asian (ASM) and North American (NAM) monsoons, investigating their contributions to stratospheric water vapor. The Lagrangian method tracks air parcels and identifies the coldest temperature along each trajectory, contrasting with local methods that rely on vertical temperature profiles. The reconstructed water vapor fields are validated against satellite observations from SAGE III/ISS and NASA’s Aura MLS. SAGE III/ISS shows stronger moisture enhancements than MLS, but both datasets reveal similar water vapor anomalies within the ASM and NAM anticyclones. Although the Lagrangian method is dry-biased compared to observations, it effectively reconstructs UTLS water vapor (correlation coefficient ~0.75), capturing moist anomalies in the ASM but performing less well in the NAM. Our analysis shows that, rather than local conditions, large-scale cold point tropopause temperatures in the vicinity of the monsoons primarily drive the moisture anomalies, with NAM water vapor significantly influenced by long-range transport from South Asia. Some convection-related processes, such as east-west shifts within the ASM, are not fully captured due to unresolved temperature variability in ERA5 and missing ice microphysics. Despite biases and computational challenges, the Lagrangian method provides valuable insights into UTLS water vapor transport.

Water vapor in the Upper Troposphere and Lower Stratosphere (UTLS) plays a crucial role in climate feedback by influencing radiation, chemistry, and atmospheric dynamics. The amount of water vapor entering the stratosphere is sensitive to cold point temperatures (CPT), making Northern Hemisphere summer monsoons more favorable for transporting water vapor into the stratosphere. This study uses a Lagrangian method to reconstruct water vapor over the Asian (ASM) and North American (NAM) monsoons, investigating their contributions to stratospheric water vapor. The Lagrangian method tracks air parcels and identifies the coldest temperature along each trajectory, contrasting with local methods that rely on vertical temperature profiles. The reconstructed water vapor fields are validated against satellite observations from SAGE III/ISS and NASA’s Aura MLS. SAGE III/ISS shows stronger moisture enhancements than MLS, but both datasets reveal similar water vapor anomalies within the ASM and NAM anticyclones. Although the Lagrangian method is dry-biased compared to observations, it effectively reconstructs UTLS water vapor (correlation coefficient 0.75), capturing moist anomalies in the ASM but performing less well in the NAM. Our analysis shows that, large-scale cold point tropopause temperatures in the vicinity of the monsoons primarily drive the moisture anomalies, with NAM water vapor significantly influenced by long-range transport from South Asia. Some convection-related processes, such as east-west shifts within the ASM, are not fully captured due to unresolved temperature variability in ERA5 and missing ice microphysics. Despite biases and computational challenges, the Lagrangian method provides valuable insights into UTLS water vapor transport.

Water vapor in the Upper Troposphere and Lower Stratosphere (UTLS) plays a crucial role in climate feedback by influencing radiation, chemistry, and atmospheric dynamics. The amount of water vapor entering the stratosphere is sensitive to cold point temperatures (CPT), making Northern Hemisphere summer monsoons more favorable for transporting water vapor into the stratosphere. This study uses a Lagrangian method to reconstruct water vapor over the Asian (ASM) and North American (NAM) monsoons, investigating their contributions to stratospheric water vapor. The Lagrangian method tracks air parcels and identifies the coldest temperature along each trajectory, contrasting with local methods that rely on vertical temperature profiles. The reconstructed water vapor fields are validated against satellite observations from SAGE III/ISS and NASA’s Aura MLS. SAGE III/ISS shows stronger moisture enhancements than MLS, but both datasets reveal similar water vapor anomalies within the ASM and NAM anticyclones. Although the Lagrangian method is dry-biased compared to observations, it effectively reconstructs UTLS water vapor (correlation coefficient 0.75), capturing moist anomalies in the ASM but performing less well in the NAM. Our analysis shows that, large-scale cold point tropopause temperatures in the vicinity of the monsoons primarily drive the moisture anomalies, with NAM water vapor significantly influenced by long-range transport from South Asia. Some convection-related processes, such as east-west shifts within the ASM, are not fully captured due to unresolved temperature variability in ERA5 and missing ice microphysics. Despite biases and computational challenges, the Lagrangian method provides valuable insights into UTLS water vapor transport.