The tropopause chemical structure (TCS) is influenced by stratosphere-troposphere exchange (STE) and plays a role in the Earth’s climate. However, this role is still not fully understood in East Asia, where active STE and high anthropogenic emissions coexist. Using airborne measurements of trace gases, including O3, CO, and H2O, we reveal the variations in TCS during two consecutive cut-off lows (COLs), an important trigger of STE. We demonstrate the important roles of two-way STE and long-range transport processes in delivering natural and anthropogenic signatures in the TCS. The former COL case shows a normal pattern of TCS, consisting of stratospheric and tropospheric air and a mixture of them. The latter, as a novel type of STE, exhibits an anomalous and complex structure due to deep convective injection into stratospheric intrusions and advection of remote marine air. The distinct mixture of stratospheric air and anthropogenic pollution alters the TCS, with horizontal and vertical scales estimated to be 200 and 1 km, respectively. Moreover, air of maritime origin, which is convectively transported and strongly dehydrated during long-range transport, is also identified. Such a complex TCS can produce unique chemical environments that modulate cloud physics and atmospheric radiation. From a climatological perspective, events of these anomalous airmasses are nonnegligible in terms of their frequency and chemical impact, as revealed by multiyear observations. These new insights advance our understanding of the mixing of natural and anthropogenic species that shape the TCS in East Asia and have implications for climate change.

Surface ozone (O3) is influenced not only by anthropogenic emissions but also by meteorological factors, with wind direction being one of the most overlooked factors. Here, we combine the observational data of both O3 and wind flow to compare the variation in surface O3 with wind direction between coastal and inland regions of Fujian, a province in the southeast coast of China with complicated topography. We further conduct a numerical simulation using a global chemical transport model, GEOS-Chem, to interpret the observational results, explore the linkages between these O3 variations and wind flows, and identify the dominant processes for the occurrence of high O3 that varies with wind flows. The results from the observations over 2015–2021 suggest that, over coastal regions, surface O3 concentrations show a strong dependence on wind flow changes. On average, during the daytime, when southeasterly winds prevail, the mean of O3 concentrations reaches 83.5 μg/m3, which is 5.0 μg/m3 higher than its baseline values (the mean O3 concentrations), while the northwesterly winds tend to reduce surface O3 by 6.4 μg/m3. The positive O3 anomalies with southeasterly wind are higher in the autumn and summer than in the spring and winter. During the nighttime, the onshore northeasterly winds are associated with enhanced O3 levels, likely due to the airmass containing less NO2, alleviating the titration effects. Over inland regions, however, surface O3 variations are less sensitive to wind flow changes. The GEOS-Chem simulations show that the prevailing southeasterly and southwesterly winds lead to the positive anomaly of chemical reactions of O3 over coastal regions, suggesting enhanced photochemical production rates. Furthermore, southeasterly winds also aid in transporting more O3 from the outer regions into the coastal regions of Fujian, which jointly results in elevated surface O3 when southeasterly winds dominates. When affected by wind flows in different directions, the chemical reaction and transport in the inland regions do not exhibit significant differences regarding their impact on O3. This could be one of the reasons for the difference in O3 distribution between coastal and inland regions. This study could help to deepen our understanding of O3 pollution and aid in providing an effective warning of high-O3 episodes.

The air quality in China has substantially improved in recent years,as indicated by the declining trends in SO2,NO2,PM2.5 and PM10 concentrations.Despite the reduced anthropogenic pollutant emissions;however,sustained increases in surface ozone(O3)that may impair the effectiveness of clean air actions have been observed.Moreover,complex heavy pollution episodes can still occur,and some of these episodes are closely linked with weather.For example,two severe sandstorms occurred successively in the early spring of 2021 in North China,despite the sandstorm fre-quency in China having significantly decreased in recent years[1-3].The first sandstorm occurred on 15 March and was the most severe sandstorm in China over the past decade,with a dust plume(3.8 × 106 km2)covering approximately 40％of China's land area.

The upper atmosphere is dynamically perturbed by the underlying thunderstorms and lightning, and the optical phenomena known as transient luminous events (TLEs) are one of the manifestations. Up to now, TLEs includes sprites, elves, blue jets, blue starters, gigantic jets and halos, etc. Due to the very short duration, dim brightness and very large horizontal scale (hundreds of kilometers), elves are very hard to be captured by ground-based cameras. An elve event is recorded for the first time over inland region in Asia Continent on the night of 20 September 2016. The elve is unusual bright with its parent lightning located about 505 km away from the camera. The elve occurred in the parent thunderstorm dissipating stage with low cloud tops and the thunderstorm is located completely in inland region with relatively dry, stable and low shear environment, not documented so far. The elve parent stroke is vertically aligned located in small thunderstorm cell with weak reflectivity. Sferic waveforms suggest that the magnetic field of the elve parent stroke is the maximum among all the strokes during the storm life cycle. The impulse and total charge moment change of the parent stroke is 617 and 3577 C km, respectively. In addition, the elves parent stroke sferics exhibit unique wave train feature not available both in the sprite parent stroke and other strokes that did not produce TLEs in the same thunderstorm.

Events of stratospheric intrusions to the surface (SITS) can lead to severe ozone (O3) pollution. Still, to what extent SITS events impact surface O3 on a national scale over years remains a long-lasting question, mainly due to difficulty of resolving three key SITS metrics: frequency, duration and intensity. Here, we identify 27,616 SITS events over China during 2015-2022 based on spatiotemporally dense surface measurements of O3 and carbon monoxide, two effective indicators of SITS. An overview of the three metrics is presented, illustrating large influences of SITS on surface O3 in China. We find that SITS events occur preferentially in high-elevation regions, while those in plain regions are more intense. SITS enhances surface O3 by 20 ppbv on average, contributing to 30-45% of O3 during SITS periods. Nationally, SITS-induced O3 peaks in spring and autumn, while over 70% of SITS events during the warm months exacerbate O3 pollution. Over 2015-2022, SITS-induced O3 shows a declining trend. Our observation-based results can have implications for O3 mitigation policies in short and long terms. The authors analyze the frequency, duration and intensity of stratospheric intrusions to the surface in China over 2015-2022 and find that such intrusions enhance surface ozone pollution, especially in spring and autumn, followed by summer.

Solving partial differential equations (PDEs) numerically often requires huge computing time, energy cost, and hardware resources in practical applications. This has limited their applications in many scenarios (e.g., autonomous systems, supersonic flows) that have a limited energy budget and require near real-time response. Leveraging optical computing, this paper develops an on-chip training framework for physics-informed neural networks (PINNs), aiming to solve high-dimensional PDEs with fJ/MAC photonic power consumption and ultra-low latency. Despite the ultra-high speed of optical neural networks, training a PINN on an optical chip is hard due to (1) the large size of photonic devices, and (2) the lack of scalable optical memory devices to store the intermediate results of back-propagation (BP). To enable realistic optical PINN training, this paper presents a scalable method to avoid the BP process. We also employ a tensor-compressed approach to improve the convergence and scalability of our optical PINN training. This training framework is designed with tensorized optical neural networks (TONN) for scalable inference acceleration and MZI phase-domain tuning for in-situ optimization. Our simulation results of a 20-dim HJB PDE show that our photonic accelerator can reduce the number of MZIs by a factor of 1.17× 10^3, with only 1.36 J and 1.15 s to solve this equation. This is the first real-size optical PINN training framework that can be applied to solve high-dimensional PDEs.

The ozone (O3) variations in southeast China are largely different between mountainous forest areas located inland, and lowland urban areas located near the coast. Here, we selected these two kinds of areas to compare their similarities and differences in surface O3 variability from diurnal to seasonal scales. Our results show that in comparison with the lowland urban areas (coastal areas), the mountainous forest areas (inland areas) are characterized with less human activates, lower precursor emissions, wetter and colder meteorological conditions, and denser vegetation covers. This can lead to lower chemical O3 production and higher O3 deposition rates in the inland areas. The annual mean of 8-h O3 maximum concentrations (MDA8 O3) in the inland areas are ~15 μg·m−3 (i.e. ~15%) lower than that in the coastal areas. The day-to-day variation in surface O3 in the two types of the areas is rather similar, with a correlation coefficient of 0.75 between them, suggesting similar influences on large scales, such as weather patterns, regional O3 transport, and background O3. Over 2016–2020, O3 concentrations in all the areas shows a trend of “rising and then falling”, with a peak in 2017 and 2018. Daily MDA8 O3 correlates with solar radiation most in the coastal areas, while in the inland areas, it is correlated with relative humidity most. Diurnally, during the morning, O3 concentrations in the inland areas increase faster than in the coastal areas in most seasons, mainly due to a faster increase in temperature and decrease in humidity. While in the evening, O3 concentrations decrease faster in the inland areas than in the coastal areas, mostly attributable to a higher titration effect in the inland areas. Seasonally, both areas share a double-peak variation in O3 concentrations, with two peaks in spring and autumn and two valleys in summer and winter. We found that the valley in summer is related to the summer Asian monsoon that induces large-scale convections bringing local O3 upward but blocking inflow of O3 downward, while the one in winter is due to low O3 production. The coastal areas experienced more exceedance days (~30 days per year) than inland areas (~5-10 days per year), with O3 sources largely from the northeast. Overall, the similarities and differences in O3 concentrations between inland and coastal areas in southeastern China are rather unique, reflecting the collective impact of geographic-related meteorology, O3 precursor emissions, and vegetation on surface O3 concentrations.

Backward propagation (BP) is widely used to compute the gradients in neural network training. However, it is hard to implement BP on edge devices due to the lack of hardware and software resources to support automatic differentiation. This has tremendously increased the design complexity and time-to-market of on-device training accelerators. This paper presents a completely BP-free framework that only requires forward propagation to train realistic neural networks. Our technical contributions are three-fold. Firstly, we present a tensor-compressed variance reduction approach to greatly improve the scalability of zeroth-order (ZO) optimization, making it feasible to handle a network size that is beyond the capability of previous ZO approaches. Secondly, we present a hybrid gradient evaluation approach to improve the efficiency of ZO training. Finally, we extend our BP-free training framework to physics-informed neural networks (PINNs) by proposing a sparse-grid approach to estimate the derivatives in the loss function without using BP. Our BP-free training only loses little accuracy on the MNIST dataset compared with standard first-order training. We also demonstrate successful results in training a PINN for solving a 20-dim Hamiltonian-Jacobi-Bellman PDE. This memory-efficient and BP-free approach may serve as a foundation for the near-future on-device training on many resource-constraint platforms (e.g., FPGA, ASIC, micro-controllers, and photonic chips).

In this study, a lightning data assimilation (LDA) method adjusting dynamical fields was examined in the rapid cycle with Weather Research and Forecasting (WRF) model and WRF Data Assimilation (WRFDA). This method retrieves pseudo vertical velocity profiles from total lightning observations and promotes wind convergence over lightning regions. This newly developed LDA scheme is compared with radar data assimilation (RDA) that has been routinely applied in severe storm nowcasting models. Depending on whether the radar or lightning data is assimilated, four experiments were designed to evaluate the positive impacts of dynamical adjustment from LDA. Using a typical severe mesoscale convection system occurred in Beijing, we found that the effect of RDA and LDA are different. The assimilation of radar radial velocity mainly improves the forecast in a longer time, while assimilation of pseudo-vertical-velocity from lightning data mainly corrects intensity and location of the forecasted precipitation. When both radar and lightning data are assimilated, the small-scale wind convergence are promoted and contributes to the intensified updrafts. Thermal and water vapor fields are also adjusted indirectly. Consequently, the convective precipitation is significantly improved and the positive impacts from the combined assimilation scheme persisted over a longer period (at least 3 h). It can be concluded that a combined assimilation of convective data from multiple sources such as radar and lightning data enhance prominently the accuracy of short-term convection forecasts.

Rainfall amount and its variability on various time scales can significantly influence ecosystem evapotranspiration (ET) and gross primary productivity (GPP). However, little attention has been paid to how ET and GPP respond to diurnal rainfall variations. Here we investigate the effect of diurnal rainfall variations on ET and GPP, based on data at 14 forest sites between 35 degrees S-35 degrees N from FLUXNET2015. Diurnal rainfall variations are represented by four indices. The timing of precipitation within one day is represented by the fraction of daytime precipitation (Frc) and the rainfall peaking time hrpeak. The frequency of precipitation (Freq) is expressed in hours with rainfall out of 24 hours on the day. An Unranked Gini index (UGi) is newly introduced to represent the unevenness of diurnal rainfall distribution in both timing and frequency. Our results illustrate prominent influences of diurnal rainfall variations on ET and GPP at the studied forest sites in lower latitudes. Given an amount of daily total precipitation, more daytime rainfall either in intensity or frequency (larger Frc or Freq), especially occurring around noon (shorter period from hrpeak), could lead to less daily total ET and GPP. More unevenly distributed rainfall being more away from noon (larger UGi) could result in more daily total ET and GPP. These influences become stronger with more daily total rainfall except for Freq. The regression coefficients of ET and GPP to UGi could reach 0.6, which is twice of Frc and hrpeak. During a rainfall, solar radiation, air temperature and vapor pressure deficit would decrease, leading to decreases in ET and GPP. The concurrent diurnal variations in rainfall and other meteorological variables drive changes in ET and GPP. Considering diurnal variations of rainfall in observations and models would be helpful to improve our understanding of atmosphere-biosphere interactions in the future.

The Lightning Mapping Imager (LMI) onboard the Fengyun-4A (FY-4A) satellite is the first independently developed satellite-borne lightning imager in China. It enables continuous lightning detection in China and surrounding areas, regardless of weather conditions. The FY-4A LMI uses a Charge-Coupled Device (CCD) array for lightning detection, and the accuracy of lightning positioning is influenced by cloud top height (CTH). In this study, we proposed an ellipsoid CTH parallax correction (ECPC) model for lightning positioning applicable to FY-4A LMI. The model utilizes CTH data from the Advanced Geosynchronous Radiation Imager (AGRI) on FY-4A to correct the lightning positioning data. According to the model, when the CTH is 12 km, the maximum deviation in lightning positioning caused by CTH in Beijing is approximately 0.1177° in the east–west direction and 0.0530° in the north–south direction, corresponding to a horizontal deviation of 13.1558 km, which exceeds the size of a single ground detection unit of the geostationary satellite lightning imager. Therefore, it is necessary to be corrected. A comparison with data from the Beijing Broadband Lightning Network (BLNET) and radar data shows that the corrected LMI data exhibit spatial distribution that is closer to the simultaneous BLNET lightning positioning data. The coordinate differences between the two datasets are significantly reduced, indicating higher consistency with radar data. The correction algorithm decreases the LMI lightning location deviation caused by CTH, thereby improving the accuracy and reliability of satellite lightning positioning data. The proposed ECPC model can be used for the real-time correction of lightning data when CTH is obtained at the same time, and it can be also used for the post-correction of space-based lightning detection with other cloud top height data.

Understanding the causes and sources responsible for severe fine particulate matter (PM2.5) pollution episodes that occur under conducive synoptic weather patterns (SWPs) is essential for regional air quality management. The Yangtze River Delta (YRD) region in eastern China has experienced recurrent severe PM2.5 episodes during the winters from 2013 to 2017. In this study, we employed an objective classification approach, the self-organizing map, to investigate the underlying impact of predominant SWPs on PM2.5 pollution in the YRD. We further conducted a series of source apportionment simulations using the Particulate Source Apportionment Technology (PSAT) tool integrated within the Comprehensive Air Quality Model with Extensions (CAMx) to quantify the source contributions to PM2.5 pollution under different SWPs. Here we identified six predominant SWPs over the YRD that are robustly connected to the evolution of the Siberian High. Considering the regional average PM2.5 anomalies, our results show that polluted SWPs favourable for the occurrence of regional PM2.5 pollution account for 61-78 %. The most conducive SWP, associated with the highest regional exceedance (46 %) of PM2.5 levels, is characterized by noticeable cyclonic anomalies at 850 hPa and stagnant surface weather conditions. Our source apportionment analysis emphasizes the pivotal role of local emissions and intra-regional transport within the YRD in shaping PM2.5 pollution in representative cities. Local emissions have the most significant impact on PM2.5 levels in Shanghai (32-48 %), while PM2.5 pollution in Nanjing, Hangzhou, and Hefei is more influenced by intra-regional transport (33-61 %). Industrial and residential emissions are the dominant sources, contributing 32-41 % and 24-38 % to PM2.5, respectively. Under specific SWPs associated with a stronger influence of inter-regional transport from northern China, there is a synchronously remarkable enhancement in the contribution of residential emissions. Our study pinpoints the opportunities for future air quality planning that would benefit from quantitative source attribution linked to prevailing SWPs.

The Tibetan Plateau (TP) with a large landmass serves as an obstacle that hinders westerly flows and alters climate downwind. Here, we investigate the TP influence on the magnitude and spatial distribution of wintertime fine particulate matter (PM 2.5 ) concentrations downwind and associated underlying mechanisms. Based on simulations using an Earth system model, we show that the removal of the TP would reduce surface PM 2.5 concentrations by −30.4% in the Sichuan basin (SC) and by −12.4% in the North China Plain (NCP), but increase the concentrations by 18.1% in eastern China (EC), suggesting that the TP could naturally intensify PM 2.5 pollution in SC and NCP. If the TP were absent, more meridional circulations would turn into zonal ones and the East Asian winter monsoon would become weaker. There would be less precipitation and lower humidity over SC and EC in the south, while the opposite occurs over NCP in the north. Consequently, the changes in circulations would result in a net outflow of PM 2.5 from SC and NCP, but a net inflow of PM 2.5 to EC. In response to the spatial changes in precipitation, wet deposition would decrease in SC and EC but increase in NCP. PM 2.5 production would reduce in SC and EC but amplify in NCP, following the changes in humidity. In magnitude, the changes in transport and wet deposition would be dominant in SC and NCP, while in EC, transport, wet deposition, and chemical production would be equally important. This study illustrates significant and heterogeneous impacts of the TP on air quality downwind.

The surface ozone pollution is strongly coupled with ozone variations above the ground. Using sufficient airborne ozone profiles during 2012-2018, this study reveals the tropospheric ozone distributions over four cities located in coastal regions of southern China. The 7-year mean tropospheric ozone profiles in the four cities consistently show a double-maxima profile, with a local maximum at 1 km altitude and the other in the middle-to-upper troposphere. Seasonally, springtime ozone is larger than the annual mean throughout the troposphere, while ozone in summer is high in the middle-to-upper troposphere, leading to largest vertical variations among seasons. Ozone in the middle-to-upper troposphere is lower in autumn than in spring and summer. The winter ozone is characterized with a minimum in the lower troposphere, and low values in the middle-to-upper troposphere, leading to least vertical variations among seasons. We untangle the causes for these complicated vertical ozone variations using the GEOS-Chem model. The tropospheric ozone over southern China is partitioned into locally produced ozone, regionally transported native ozone, imported ozone from outside of China (foreign ozone) and natural stratospheric ozone. The results suggest that the springtime ozone abundance is due to the enhanced import of foreign and stratospheric ozone and the intensified regional transport processes of native ozone. In summer, local ozone production is enhanced and regional transport of ozone in the middle-to-upper troposphere is strengthened due to upward air motions, while such transport becomes weaker in autumn leaving low ozone in the middle-to-upper troposphere. In winter, the intensive westerly jets promote foreign and stratospheric ozone again in the middle-to-upper troposphere, but the local ozone production and regional transport are sharply reduced, resulting in low ozone near the surface. This study provides new insights into regional ozone profiles and reveals the significance of vertical ozone variations on surface ozone prevention strategy.

Surface ozone increased unexpectedly over northern China during the COVID-19 lockdown (CLD) period (23 January–29 February 2020), which was characterized by vigorous emission reduction. The reasons for this ozone enhancement have been speculated from perspectives of chemical responses to the emissions and meteorology. As known, the processes of natural stratospheric ozone injecting to the troposphere are most active in winter and spring. Yet, little attention was paid to stratospheric influences on this ozone enhancement. Here we report a stratospheric intrusion (SI) that reached the surface over northern China on 15–17 February during the CLD. The coevolution of enhanced ozone and sharply declined carbon monoxide and relative humidity (RH) was indicative of the SI occurrence. We show that the SI was facilitated by a cutoff low system that led to abnormally high surface ozone in most part of northern China. We estimate that over the SI period, the injected stratospheric ozone constituted up to 40–45% of the surface ozone over northern China. If the stratospheric ozone inputs were scaled over the entire CLD period, these inputs would account for 4–8% of the surface ozone. In view of the unexpected ozone increase during the CLD, this SI event could explain up to 18% of the ozone increase in some cities, and average 5–10% over larger areas that were affected. Hence, the nonnegligible stratospheric influences urge extra consideration of natural ozone sources in disentangling the role of emission reduction and meteorological conditions during the CLD in China and elsewhere in the world.

Severe ozone (O3) pollution can be harmful to human health and ecosystems. The O3 level in Fujian, a coast province in southeast China, is generally 30???60 ??g m- 3 lower than in highly polluted regions in China, including North China Plain (NCP), Yangtze River Delta (YRD), and Pearl River Delta (PRD). Yet, Fujian still experiences high O3 episodes that exceed the national standard. Here we investigate whether and how these high O3 episodes are impacted by regional O3 transport from polluted regions. A backward trajectory model, HYSPLIT, is combined with observational data to identify transport pathways and O3 source regions. The results show that the exceedance days (8 h O3 concentrations above 160 ??g m??? 3), averaged over 2015???2020, range 12???34 days for coastal cities and 3???9 days for inland cities, with two peaks in late-spring and early-autumn. On average, O3 transport from non-Fujian regions can impact 29???38% of exceedance days in coastal cities, and 44???50% of exceedance days in inland cities. The dominant transport pathways are from YRD and NCP to the East China Sea near Fujian in the lower troposphere, and then to Fujian near the ground level. Regional transport from PRD, mainly in spring, also happens. Using synoptic weather pattern (SWP) classification, we identify three SWPs in spring and two SWPs in autumn that are favorable to regional O3 transport. In summer, such transport is mainly associated with typhoon activities. This study underscores the importance of regional O3 transport to a clean coastal region and helps predict regional air pollution.

To investigate the process of convective merger (CM) and its effect on thunderstorms evolution and corresponding electrical activity, a severe squall line that took place on 27 July 2015 over the Beijing Metropolitan Region (BMR) is simulated and studied using the Weather Research and Forecasting (WRF) model coupled with an explicit electrification lightning scheme ( E‐ WRF). The model‐simulated radar reflectivity reasonably captured the whole squall line evolution, including the merging of individual cells and storms. The variation of normalized flash frequency simulated by E‐ WRF is highly consistent with the occurrence of a prominent flash rate surge during the CM both in the observation and the simulation. Cloud bridge is one of the regions where lightning events increase most. The upstream anvil and the sinking outflow led to the rapid connection and formation of new convective cells between the two older main storms. Subsequently, the mass of graupel and snow increased substantially at the middle level, and the mass of upper‐level ice was horizontally advected from upstream. During the merger, the in‐cloud charge distribution evolved from a staggered charge pocket structure into a vertically stratified five‐layer structure. This study supports the hypothesized role of CM in enhancing lightning activity, and further expands our understanding of CM effects on microphysics and charge‐redistribution.

Stratospheric ozone transported to the troposphere is estimated to account for 5 %–15 % of the tropospheric ozone sources. However, the chances of intruded stratospheric ozone reaching the surface are low. Here, we report an event of a strong surface ozone surge of stratospheric origin in the North China Plain (NCP, 34–40∘ N, 114–121∘ E) during the night of 31 July 2021. The hourly measurements reveal surface ozone concentrations of up to 80–90 ppbv at several cities over the NCP from 23:00 LST (Local Standard time, = UTC +8 h) on 31 July to 06:00 LST on 1 August 2021. The ozone enhancement was 40–50 ppbv higher than the corresponding monthly mean. A high-frequency surface measurement indicates that this ozone surge occurred abruptly, with an increase reaching 40–50 ppbv within 10 min. A concurrent decline in surface carbon monoxide (CO) concentrations suggests that this surface ozone surge might have resulted from the downward transport of a stratospheric ozone-rich and CO-poor air mass. This is further confirmed by the vertical evolutions of humidity and ozone profiles based on radiosonde and satellite data respectively. Such an event of stratospheric impact on surface ozone is rarely documented in view of its magnitude, coverage, and duration. We find that this surface ozone surge was induced by a combined effect of dying Typhoon In-fa and shallow local mesoscale convective systems (MCSs) that facilitated transport of stratospheric ozone to the surface. This finding is based on analysis of meteorological reanalysis and radiosonde data, combined with high-resolution Weather Research and Forecasting (WRF) simulation and backward trajectory analysis using the FLEXible PARTicle (FLEXPART) particle dispersion model. Although Typhoon In-fa on the synoptic scale was at its dissipation stage when it passed through the NCP, it could still bring down a stratospheric dry and ozone-rich air mass. As a result, the stratospheric air mass descended to the middle-to-low troposphere over the NCP before the MCSs formed. With the pre-existing stratospheric air mass, the convective downdrafts of the MCSs facilitated the final descent of stratospheric air mass to the surface. Significant surface ozone enhancement occurred in the convective downdraft regions during the development and propagation of the MCSs. This study underscores the substantial roles of weak convection in transporting stratospheric ozone to the lower troposphere and even to the surface, which has important implications for air quality and climate change.

基于北京宽频带闪电网(Beijing Broadband Lightning Network,简称BLNet)获得的全闪三维定位和多普勒天气雷达等资料,详细分析了 2015～2017年北京暖季7次强飑线过程的闪电活动与雷达回波强度之间的关系.结果表明,闪电主要发生于前部线状对流云区内且集中分布在30 dBZ以上的强回波区域,少部分的闪电分布在后部的层状云区域内.从闪电辐射源三维分布结构可以发现,闪电活动大部分处在6～11 km的高度范围.将能够同时反映强回波深度和面积的0～-30℃温度区域内大于30 dBZ雷达回波体积(V30dBZ)作为强回波指标,并与闪电活动进行统计分析发现,整体上在7次飑线过程中,总闪频数和V30dBZ存在较好的相关性,其中5次过程的闪电频数峰值同时或提前于V30dBZ的峰值出现,二者的时滞相关系数超过0.61,提前时间为0～96min.另外两次过程中闪电峰值落后于V30dBZ峰值,落后时间分别为30 min和60 min.研究结果不仅对认识闪电与对流活动的关系有重要的科学意义,也可为闪电资料在数值模式中的同化应用提供科学依据.