Our Earth experienced an extreme solar storm on the Mother's Day weekend from 10-12 May 2024, leading to the most severe geomagnetic storm in the past two decades. In addition to significant changes in the near-Earth space environment from the magnetosphere to the ionosphere, this study primarily shows notable disturbances in the atmospheric electric field (Ez), as recorded by the electric field mill of the MVP-LAI (Monitoring Vibrations and Perturbations in the Lithosphere, Atmosphere, and Ionosphere) system located in LeShan (29.6 degrees N, 103.9 degrees E; L-shell value similar to 1.12), Sichuan Province, during the initial and main phases of the storm. Here, we employed a data-adaptive method to identify storm characteristics by resolving complex changes in atmospheric Ez over short to long periods. For further investigating causal mechanisms, we also analyzed the collocated measurements of the MVP-LAI system, including atmospheric pressure, geomagnetic fields, ionospheric total electron content (TEC), and High-frequency Doppler echoes over LeShan, as well as the ionosonde echoes at DaoFu (31.0 degrees N, 101.12 degrees E) and the magnetic field observation from Geostationary Operational Environmental Satellite (GOES) 16 at similar to 6.6 Earth radii. The key finding is the nearly coincident disturbances from space to the atmospheric Ez at similar to 20:00 UT, which indicated the possible impact of electrodynamic changes on the atmosphere at the time of storm onset. Short-period perturbations (with frequency >1 mHz) observed in the ionospheric TEC, atmospheric pressure and electric field suggest the appearance of acoustic resonance in the atmosphere during the storm's main phase.

The fine-scale vertical structure of atmospheric water vapor on a global scale is still not well understood. This study employs 1.4 million high-resolution radiosonde profiles from over 440 stations to examine total atmospheric water content and the vertical mixing efficiency of water vapor across various climatic zones, altitude ranges, and seasons. The findings reveal significant statistical variations in total water content at different altitudes and within diverse climatic zones, with temperature identified as the dominant controlling factor, although wind is also shown to be relevant for continental climates and polar regions. High water vapor content generally corresponds to warm but calm ambient atmospheric conditions, with an increased likelihood of static instability and updraft air movement. Furthermore, buoyancy-driven turbulence is found to enhance the vertical mixing of water vapor, with buoyancy frequency and the Richardson number acting as key parameters for determining vertical mixing.

Long-term monitoring of global wind fields, particularly at lower altitudes, has been historically constrained, limiting a complete understanding of low-level jets (LLJs). These LLJs are consequential for turbulence, wind energy production, water vapor transport, and aviation safety. To address this limitation, this study analyzes up to 25 years of global, high-resolution wind data, incorporating 3.5 million measurements from 560 radiosonde stations. The research investigates the climatology and long-term trends of LLJ characteristics and their influence on turbulent activity. LLJ occurrence is modulated by the complex interplay of climatic zone, season, and terrain, with lower-intensity LLJs more prevalent in tropical regions and higher-intensity LLJs in polar regions. The most frequent LLJ observation altitude ranges from 300 to 900 m above ground level. Strong LLJs correlate with increased turbulence; their presence elevates the probability of turbulence occurrence by approximately 70% compared to conditions without LLJs, underscoring the importance of LLJ detection for low-altitude economic activities. Observational data suggest a general decline in low-level maximum wind speed since 2000, resulting in a decreasing LLJ occurrence frequency of approximately - 3.53% per decade and a corresponding reduction in the occurrence probability of low-level turbulence.

Mars has been a primary focus of planetary science, with significant advancements over the past two decades across disciplines including geological evolution, surface environment, and atmospheric and space science. However, the rapid growth of the related literature has rendered traditional manual review methods increasingly inadequate. This inadequacy is particularly evident in interdisciplinary research, which is often characterized by dispersed topics and complex semantics. To address this challenge, this study proposes an automated analysis framework based on natural language processing (NLP) to systematically review the Martian research in Earth and space science over the past two decades. The research database contains 151,196 Mars-related sentences extracted from 10,655 publications spanning 2001 to 2024. Using machine learning techniques, the framework clusters Mars-related sentences into semantically coherent groups and applies topic modeling to extract core research themes. It then analyzes their temporal evolution across the Martian solid, surface, atmosphere, and space environments. Finally, through sentiment analysis and semantic matching, it highlights unresolved scientific questions and potential directions for future research. This approach offers a novel perspective on the knowledge structure underlying Mars exploration and demonstrates the potential of NLP for large-scale literature analysis in planetary science. The findings potentially provide a structured foundation for building an interdisciplinary, peer-reviewed Mars knowledge base, which may inform future scientific research and mission planning.

Using the vertical velocity (w) observed by a Ka-band millimeter wave cloud radar (MMCR) at Wuhan, we investigate the evolution of the convective boundary layer height (CBLH) based on a specified threshold of vertical velocity variance (σw2). The CBLHs from the MMCR w in the selected durations are compared with those estimated by the lidar range-corrected signal (RCS) and radiosonde temperature based on different algorithms, showing good agreement with each other. Although these algorithms are based on different dynamic and thermodynamic effects, the diurnal evolution of the CBLH from MMCR is generally consistent with that from lidar, except for a few hours post-sunrise and pre-sunset due to the influence of the aerosol residual layer on the lidar RCS. Meanwhile, the CBLH from MMCR shows less variation with the occurrence of sand and dust and a swifter response for thick clouds relative to that from lidar. In this case, σw2 of the MMCR w identifies the CBLH based on a dynamic effect, which can accurately capture the diurnal evolution of the CBLH compared with that from the change in long-time-mixing aerosol concentration. The monthly and seasonal features of the CBLH at Wuhan are revealed via the MMCR measurement. Hence, considering that the MMCR is capable of continuous observation in various weather conditions, the MMCR w with high resolution can be applied for monitoring the evolution of the CBLH in different atmospheric conditions, which is helpful for improving our comprehensive understanding of the convective boundary layer (CBL) and dynamic processes in the CBL.

The tropopause plays a critical role in stratosphere-troposphere exchange and climate change. Its height is widely defined based on the World Meteorological Organization (WMO) threshold temperature gradient. High-resolution (5–10 m) soundings, therefore, are expected to substantially minimize uncertainties of tropopause height (TH) arising from limited vertical resolution and imprecise temperature measurements. The high-resolution radiosonde data, accumulated from 2000 to 2023 from a globally distributed, sparse network (about 1.5 million profiles from 222 stations), offers valuable insights into climatological tropopause variability. While radiosonde observations are limited by spatiotemporal coverage, European Centre for Medium–Range Weather Forecasts Reanalysis v5 (ERA5) reanalysis datasets offer globally complete tropopause representations. To leverage both the high resolution of radiosonde measurements and the global coverage of ERA5, this study compares their TH estimates and analyzes long-term trends across different latitude zones and seasons. The results indicate that the mean and absolute differences (radiosonde minus ERA5) in TH were 32 and 336 m, respectively, with larger discrepancies observed during the spring season in the tropics (±20°). Overall, point-to-point comparisons indicate that ERA5 effectively captures climatological TH variations in both time and space. Long-term trend analyses revealed increases of +9 m yr−1 (radiosonde) and +7 m yr−1 (ERA5) based on point-to-point comparisons. However, these site-specific trends may differ substantially from the long-term trends observed in ERA5 with complete spatiotemporal resolution, even showing opposite trends. Therefore, continued accumulation of high-resolution radiosonde profile data is crucial to further characterize tropopause changes in a warming climate.

While large language models (LLMs) have introduced novel paradigms in science and education, their adoption in higher education is constrained by inherent limitations. These include a tendency to produce inaccuracies and high computational requirements, which compromise the strict demands for accurate and reliable knowledge essential in higher education. Small language models (MiniLMs), by contrast, offer distinct advantages in professional education due to their lightweight nature and precise retrieval capabilities. This research takes "Atmospheric Physics" as an example. We established a specialized corpus and image repository by gathering over 550,000 full-text PDFs from over 130 international well-respected journals in Earth and environmental science. From this collection, we extracted over 100 million high-quality sentence-level corpus and more than 3 million high-resolution academic images. Using MiniLMs, these resources were organized into a high-dimensional vector library for precise retrieval and efficient utilization of extensive educational content. Consequently, we systematically redesigned the courses, textbooks, and teaching strategies for "Atmospheric Physics" based on MiniLMs. The course is designed as a "interdisciplinary-frontier" system, breaking down traditional boundaries between atmospheric science, space science, hydrology, and remote sensing. Teaching materials are transformed from static, lagging text formats into a dynamic digital resource library powered by MiniLM. For teaching methods, we have designed a question-based learning pathway. This paradigm promotes a shift from passive knowledge transfer to active cognitive development. Consequently, this MiniLM-driven "Atmospheric Physics" course demonstrates a specific avenue for "AI for education".

Abstract. The tropopause plays a critical role in stratosphere–troposphere exchange and climate change. Its height is conventionally defined based on the World Meteorological Organization (WMO) threshold temperature gradient, yet this gradient is intrinsically linked to vertical resolution. Data with higher vertical resolution inevitably reveal finer gradient structures. While in situ radiosonde temperature measurements are considered the most reliable source for tropopause structure, high-resolution (5–10 m) soundings would be expected to yield more precise height estimates. The near-global coverage of high-resolution radiosondes, accumulated over even decades, promises valuable insights into long-term tropopause variability. However, our analysis demonstrates that the original WMO definition can lead to an underestimation of the tropopause height when using high-resolution soundings, potentially misidentifying the tropopause within thin inversions or temperature gradient discontinuities below tropopause. To address this, we leverage ERA5 tropopause heights as a reference to develop a high-resolution-optimized method. We evaluate three methods: original WMO method, Moving average method, and Coarse–Fine method. The results reveal that the mean differences between the three methods and ERA5 were 800 m, 280 m, and 180 m, respectively. Notably, ERA5 systematically overestimated the tropopause height compared to all methods, with this discrepancy particularly pronounced in the edges of the Hadley circulation. The proposed Coarse–Fine method, by effectively bypassing thin inversions and gradient extrema while preserving the fine–scale structure of the tropopause height, presents a promising tool for future investigations into long-term tropopause trends.

Wind shear has important implications for Kelvin–Helmholtz instability (KHI) and gravity waves (GWs) in the mesosphere–lower thermosphere (MLT) region where its momentum transport process is dominated by short-period (<1 h) GWs. However, the sub-hourly variation in wind shear is still not well quantified. This study aims to improve current understanding of vertical wind shear by analyzing multi-year meteor radar measurements at the Mohe (MH, 53.5°N, 122.3°E), Beijing (BJ, 40.3°N, 116.2°E), Wuhan (WH, 30.5°N, 114.6°E), and Fuke (FK, 19.5°N, 109.1°E) stations in China. The wind field is estimated by a new algorithm, e.g., the damped least squares fitting. Taking the wind shear estimated by normal products as a criterion, the shear produced by the new algorithm has more statistical convergence as compared to the traditional algorithm, e.g., the least squares fitting. Therefore, we argue that the 10 min DLSA wind probably produces a more reasonable vertical shear. Both intensive wind shears and GW kinetic energy can be simultaneously captured during the 0600–1600 UTs of May at MH and during the 1300–2400 UTs of March at FK, possibly implying that the up-propagation of GWs could contribute to the production of large wind shears. The sub-hourly variation in wind shears is potentially valuable for understanding the interrelationship between shear (or KHI) and GWs.

The planetary boundary layer (PBL) is the lowermost part of the troposphere that governs the exchange of momentum, mass and heat between surface and atmosphere. To date, the radiosonde measurements have been extensively used to estimate PBL height (PBLH); suffering from low spatial coverage and temporal resolution, the radiosonde data are incapable of providing a diurnal description of PBLH across the globe. To fill this data gap, this paper aims to produce a temporally continuous PBLH dataset during the course of a day over the global land by applying machine learning algorithms to integrate high-resolution radiosonde measurements, ERA5 reanalysis, and the Global Land Data Assimilation System (GLDAS) product. This dataset covers the period from 2011 to 2021 with a temporal resolution of 3 h and a horizontal resolution of 0.25∘×0.25∘. The radiosonde dataset contains around 180 million profiles over 370 stations across the globe. The machine learning model was established by taking 18 parameters derived from ERA5 reanalysis and GLDAS as input variables, while the PBLH biases between radiosonde observations and ERA5 reanalysis were used as the learning targets. The input variables were presumably representative regarding the land properties, near-surface meteorological conditions, terrain elevations, lower tropospheric stabilities, and solar cycles. Once a state-of-the-art model had been trained, the model was then used to predict the PBLH bias at other grids across the globe with parameters acquired or derived from ERA5 and GLDAS. Eventually, the merged PBLH can be taken as the sum of the predicted PBLH bias and the PBLH retrieved from ERA5 reanalysis. Overall, this merged high-resolution PBLH dataset was globally consistent with the PBLH retrieved from radiosonde observations in terms of both magnitude and spatiotemporal variation, with a mean bias of as low as −0.9 m. The dataset and related codes are publicly available at https://doi.org/10.5281/zenodo.6498004 (Guo et al., 2022), and are of significance for a multitude of scientific research endeavors and applications, including air quality, convection initiation, climate, and climate change, to name but a few.

. Kelvin Helmholtz instability (KHI) is most likely to be the primary source 29 for clear-air turbulence that is of importance in pollution transfer and diffusion and 30 aircraft safety. It is exemplarily indicated by the critical value of Richardson ( Ri ) 31 number, which is typically taken as 1/4. However, Ri is fairly sensitive to the vertical 32 resolution of the dataset: a higher resolution systematically leads to a finer structure. 33 The study aims to evaluate the performance of ERA5 reanalysis (137 model levels) in 34 determining KHI spatial-temporal variabilities, by comparing it against a near-global 35 high-resolution (10-m) radiosonde dataset during years 2017 to 2022, and to further 36 highlight the global climatology and dynamical environment of KHIs. Overall, the 37 occurrence frequency of Ri <1/4 in the free atmosphere is inevitably underestimated 38 by the ERA5 reanalysis over all climate zones, compared to radiosonde, due largely to 39 the severe underestimation in wind shears. Otherwise, the occurrence frequency of 40 KHI indicated by Ri <1 in ERA5 is climatologically consistent with that from 41 radiosondes in the free troposphere, especially over the midlatitude and subtropics in 42 the Northern/Southern Hemisphere. Therefore, we infer that the threshold value of Ri 43 should be approximated as 1, rather than 1/4, when using ERA5 for the KHI 44 estimation. KHI occurrence frequencies revealed by both datasets exhibit significant 45 seasonal cycles over polar, midlatitude, and subtropics regions, and they are 46 consistently strong at heights of 10–15 km in the tropic region. In addition, the 47 frequency at low-levels is positively correlated with the standard derivation of 48 orography, and it is exceptionally strong over the Niño 3 region at heights of 6–13 km. 49 Furthermore, the dynamical environment of KHI favors strong wind shears probably 50 induced by the mean flows and the propagation of orographic or non-orographic 51 gravity waves. 52

Atmospheric gravity waves (GWs) in the mesosphere-lower thermosphere (MLT) are crucial for the understanding of general circulation. However, their dynamical characteristics are hardly retrieved due to the difficulty in the high-resolution observation of wind. Therefore, this paper uses eight years (2013–2020) of meteor radar measurements in the MLT region at Mohe station (53.5°N, 122.3°E), China, to retrieve high-temporal-resolution mesospheric wind data and further evaluate the temporal variation of GW kinetic energy. As the detected meteor trails exceed 6, the wind velocity is recalculated using the least square algorithm method, significantly increasing the temporal resolution of wind from 1 h up to 5 min. This resolution is sufficiently high for the investigation of GW kinetic energy, which exhibits a high spatial-temporal variability. For instance, it is enhanced in the winter season during the period of 0200–1400 UT and in the spring season during the period of 0800–1300 UT. The similarity between the climatological characteristics of GWs in MLT and the seasonal variation of GW total energy in the troposphere, determined from high-resolution radiosondes near to Mohe station, suggests that the meteorology in the lower atmosphere could be an important source of GWs in the MLT region.

Cloud remains one of the largest uncertainties in weather and climate research due to the lack of fine-resolution observations of cloud vertical structure (CVS) on a large scale. In this study, near-global CVS is characterized by high-vertical-resolution twice-daily radiosonde observations from 374 stations over land, which are distributed in Europe, North America, East Asia, Australia, the Pacific Ocean, and Antarctica. To this end, we initially develop a novel method to determine CVS, by combining both the vertical gradients of air temperature and relative humidity (RH) and the altitude-dependent thresholds of RH. It is found that the cloud base heights (CBHs) from radiosondes have a higher correlation coefficient (R= 0.91) with the CBHs from a millimeter-wave cloud radar than those from the ERA5 reanalysis (R= 0.49). Overall, cloudy skies occur 65.3 % (69.5 %) of the time, of which 55.4 % (53.8 %) are one-layer clouds at 00:00 (12:00) UTC. Most multi-layer clouds are two-layer clouds, accounting for 62.2 % (61.1 %) among multi-layer clouds at 00:00 (12:00) UTC. Geographically, one-layer clouds tend to occur over arid regions, whereas two-layer clouds do not show any clear spatial preference. The cloud bases and tops over arid regions are higher compared with humid regions albeit with smaller cloud thickness (CT). Clouds tend to have lower bases and thinner layer thicknesses as the number of cloud layer increases. The global-mean CT, CBH, and cloud top height (CTH) are 4.89 ± 1.36 (5.37 ± 1.58), 3.15 ± 1.15 (3.07 ± 1.06), and 8.04 ± 1.60 (8.44 ± 1.52) km above ground level (a.g.l.) at 00:00 (12:00) UTC, respectively. The occurrence frequency of clouds is bimodal, with lower peaks between 0.5 and 3 km a.g.l. and upper peaks between 6 and 10 km a.g.l. The CBH, CTH, and CT undergo almost the same seasonality; namely, their magnitudes in boreal summer are greater than in boreal winter. As expected, the occurrence frequencies of clouds exhibit pronounced diurnal cycles in different seasons. In boreal summer, clouds tend to form as the sun rises and the occurrence frequencies increase from morning to late afternoon, with the peak in the early afternoon at the altitude of 6–12 km a.g.l., while in boreal winter, clouds have peak occurrence frequencies in the morning. The relations between surface meteorological variables and moisture with CBH are investigated as well, showing that CBHs are generally more significantly correlated with 2 m relative humidity (RH2 m) and 2 m air temperature (T2 m) than with surface pressure and 10 m wind speed. Larger T2 m and smaller RH2 m always correspond to higher CBH. In most cases CBHs are negatively correlated to soil water content. The near-global CVS obtained from high-vertical-resolution radiosondes in this study can provide key data support for improving the accuracy of cloud radiative forcing simulation in climate models.

Kelvin–Helmholtz instability (KHI) is most likely to be the primary source for clear-air turbulence, which is of importance in pollution transfer and diffusion and aircraft safety. It is indicated by the critical value of the dimensionless Richardson (Ri) number, which is predicted to be 1/4 from linear stability analysis. However, Ri is fairly sensitive to the vertical resolution of the dataset; a higher resolution systematically leads to a finer structure. The study aims to evaluate the performance of ERA5 reanalysis in determining the spatial–temporal variabilities in subcritical Ri by comparing it against a near-global high-resolution radiosonde dataset during the years 2017 to 2022 and further highlights the global climatology and dynamical environment of subcritical Ri. Overall, the occurrence frequency of Ri<1/4 is inevitably underestimated by the ERA5 reanalysis over all climate zones at all heights from the near-ground atmosphere up to 30 km, compared to radiosonde, due directly to the severe underestimation in wind shears. Otherwise, the occurrence frequency of Ri<1 in ERA5 is climatologically consistent with that from Ri<1/4 in radiosondes in the free troposphere, especially over the midlatitude and subtropics in the Northern Hemisphere and Southern Hemisphere. Therefore, we argue that the threshold value of Ri could be approximated as 1 rather than 1/4 when using ERA5-based Ri as a proxy for KHI. The occurrence frequency of subcritical Ri revealed by both datasets exhibits significant seasonal cycles over all climate zones. In addition, it is positively correlated with the standard derivation of orography at low levels and is exceptionally strong over the Niño-3 region at heights of 6–13 km. Furthermore, a high occurrence of subcritical Ri would likely be accompanied by strong wind speeds and intensive orographic or non-orographic gravity waves.

Abstract. Kelvin Helmholtz instability (KHI) is most likely to be the primary source for clear-air turbulence that is of importance in pollution transfer and diffusion and aircraft safety. It is exemplarily indicated by the critical value of Richardson (Ri) number, which is typically taken as 1/4. However, Ri is fairly sensitive to the vertical resolution of the dataset: a higher resolution systematically leads to a finer structure. The study aims to evaluate the performance of ERA5 reanalysis (137 model levels) in determining KHI spatial-temporal variabilities, by comparing it against a near-global high-resolution (10-m) radiosonde dataset during years 2017 to 2022, and to further highlight the global climatology and dynamical environment of KHIs. Overall, the occurrence frequency of Ri < 1/4 in the free atmosphere is inevitably underestimated by the ERA5 reanalysis over all climate zones, compared to radiosonde, due largely to the severe underestimation in wind shears. Otherwise, the occurrence frequency of KHI indicated by Ri < 1 in ERA5 is climatologically consistent with that from radiosondes in the free troposphere, especially over the midlatitude and subtropics in the Northern/Southern Hemisphere. Therefore, we infer that the threshold value of Ri should be approximated as 1, rather than 1/4, when using ERA5 for the KHI estimation. KHI occurrence frequencies revealed by both datasets exhibit significant seasonal cycles over polar, midlatitude, and subtropics regions, and they are consistently strong at heights of 10–15 km in the tropic region. In addition, the frequency at low-levels is positively correlated with the standard derivation of orography, and it is exceptionally strong over the Niño 3 region at heights of 6–13 km. Furthermore, the dynamical environment of KHI favors strong wind shears probably induced by the mean flows and the propagation of orographic or non-orographic gravity waves.

AbstractThe tropopause region is crucial for the stratosphere‐troposphere exchange (STE) and acts as an indicator of climate change. Double tropopauses (DTs) act to increase the STE process but their driving mechanisms remain an open question. The present assessment offers for the first time the linkage between tropospheric gravity waves (GWs) and DT events by exploring a global data set of multi‐year radiosonde measurements. In the extratropics, the occurrence frequency of DT events keeps a remarkably consistent spatial‐temporal structure with GW total energy. Under the DT scenario, GW total energy has increased by 37.67% compared to single tropopause events. Based on a statistical assessment, the upward propagating GWs throughout the second tropopause region can probably raise Kelvin‐Helmholtz instability or turbulence, leading permanent irregularities in thermodynamic structure, and consequently, increasing the likelihood of DT.

FIGURESFigure S1.The monthly cloud amount at (a) 0000 UTC, and (b) 1200 UTC.The red and blue lines represent the cloud amount from radiosonde and ERA5, respectively.

The westerly phase of the stratospheric Quasi-Biennial Oscillation (QBO) was unprecedentedly interrupted by an easterly jet at around 22 km during boreal wintertime in 2015/2016 and 2019/2020. Many studies have investigated the role of planetary waves during these disruptions. However, the behavior of gravity waves (GWs) during these disruptions is still unclear. In this paper, we investigated the characteristics of stratospheric GWs during QBO disruptions by analyzing the U.S. high-resolution radiosonde data from 1998 to 2021 from three equatorial stations. The disruptions were separated into three stages: the westerly zonal wind decreasing stage, the easterly zonal wind developing stage, and the westerly zonal wind recovery stage. Notably, the tropical stratospheric GWs’ total energy densities were enhanced during all three stages of both events compared to those in typical years. The low-tropospheric convection, the middle-tropospheric jet, and the low-stratospheric vertical wind shear were statistically associated with the stratospheric GW variations. A quantitative analysis further indicated that the low-tropospheric convection activity, tropospheric jets, and wind shears in the lower stratosphere could well explain the variations in the stratospheric GWs in the westerly zonal wind decreasing and easterly zonal wind developing stages by applying a partial least squares regress analysis.

The inertia-gravity wave (IGW), Kelvin–Helmholtz instability (KHI) and turbulence in the lower free atmosphere are tightly linked through complex dynamical processes and their interactions profoundly shape the energy and mass transfer processes, but they remain largely unidentified. Here the near-global distributions of IGW energy, KHI (indicated by the critical value of Richardson number, Ri ), and turbulence in the free atmosphere are investigated based on 5 years (2016–2020) of high-resolution radiosonde data. A poleward decrease can be detected in IGW energy density, as well as in the occurrence frequencies of KHI and turbulence. Their maxima occur at 15 km above ground level (AGL) at low latitudes but move to 5 km AGL at high latitudes, with notable latitudinal and seasonal variations. Over the contiguous United States, spatial distributions in KHI and turbulence frequencies agree well with moderate-or-greater turbulence frequency gathered from pilot reports. Vertically, the turbulence dissipation rate follows a log-normal distribution. Notably, a half of burst turbulence exists in the regime of Ri larger than 1 instead of 1/4, beyond or even far beyond what is known as the critical value of 1/4. Positive correlations have been extensively uncovered between IGW energy and KHI frequency, KHI and turbulence frequencies, wave energy dissipation and turbulence frequency, which indicate that IGW and KHI could be major drivers for the occurrence of turbulence in the free atmosphere. These findings could advance our understanding of the physical connection from medium-scale IGWs to small-scale turbulence and are theoretically valuable for aircraft safety.

The knowledge of atmospheric turbulence over urban environment remains limited albeit its great importance for air pollution and convection initiation. This study investigates turbulence characteristics in boundary layer based on concurrent radar wind profiler (RWP) and radiosonde observations for the year 2019 at an urban site in Beijing, China. The eddy dissipation rate (epsilon) is retrieved based on Doppler spectral width measurements from RWP. The radiosonde measurements are utilized for estimating the Brunt-Vaisala frequency which is further collocated with RWP based epsilon retrievals for the estimation of vertical eddy diffusivity, outer scale length and inner scale length profiles. Contrasting seasonality is revealed in diurnal cycle of height-resolved turbulence parameters over Beijing. Within the lowermost 1 km altitude, epsilon is estimated to be more than 10(-2) m(2)s(-3) during all seasons (except for winter), which possibly represents the highly turbulent state of the atmosphere near ground surface due to the local mountain-plain flow variation. However, above 1 km altitude, the epsilon magnitude varies between 10(-4) and 10(-2) m(2)s(-3). The vertical eddy diffusivity is found to be higher in the spring and summer seasons while being approximately an order of magnitude lower in the autumn and winter seasons, which agrees with few existing studies.