Explore the vast range of titles available.

This study develops an innovative approach to homogenize discontinuities in both mean and variance in global subdaily radiosonde temperature data from 1958 to 2018. First, temperature natural variations and changes are estimated using reanalyses and removed from the radiosonde data to construct monthly and daily difference series. A penalized maximal F test and an improved Kolmogorov–Smirnov test are then applied to the monthly and daily difference series to detect spurious shifts in the mean and variance, respectively. About 60% (40%) of the changepoints appear in the mean (variance), and ∼56% of them are confirmed by available metadata. The changepoints display a country-dependent pattern likely due to changes in national radiosonde networks. Mean segment length is 7.2 (14.6) years for the mean (variance)-based detection. A mean (quantile)-matching method using up to 5 years of data from two adjacent mean (variance)-based segments is used to adjust the earlier segments relative to the latest segment. The homogenized series is obtained by adding the two homogenized difference series back to the subtracted reference series. The homogenized data exhibit more spatially coherent trends and temporally consistent variations than the raw data, and lack the spurious tropospheric cooling over North China and Mongolia seen in several reanalyses and raw datasets. The homogenized data clearly show a warming maximumaround 300 hPa over 30°S–30°N, consistent with model simulations, in contrast to the raw data. The results suggest that spurious changes are numerous and significant in the radiosonde records and our method can greatly improve their homogeneity.

Snow‐cloud microphysics over inland hills partly resembles that over high mountains, yet exhibits notable differences. During 2024–2025 winter, coordinated observations in Tokamachi City, Niigata Prefecture, Japan, were conducted using four launches of a newly developed balloon‐borne particle‐imaging radiosonde (Rainscope) together with dual X‐band polarimetric radars deployed on both sides of Uonuma Hill (approximately 700 m ASL). Snow‐particle growth processes differed markedly depending on whether airflow passed over or was blocked by hills. Graupel formation is influenced by multiple mechanisms: advection from coastal convective clouds, orographic ascent along slopes, mountain‐wave propagation leeward of the hills, and seeder‐feeder interactions upstream. The findings demonstrate that even modest inland terrain can modulate snow‐cloud microphysics substantially, highlighting the complex role of hills in winter precipitation.

Forecasting Severe Convective Wind (SCW) events remains challenging due to unresolved precursors. Using 8‐year (2016–2023) high‐resolution soundings from China radiosonde network, we establish observational pre‐SCW thresholds, revealing divergent pre‐storm pathways that advance beyond conventional SCW paradigms: Wet SCW events exhibit abrupt energy cycling (≤20‐min Convective Available Potential Energy collapse coinciding with about 15% moisture surges) coupled with mid‐level cyclonic rotation breakdown, while dry SCW events show a distinct two‐stage kinetic energy descent, featuring initial downward wind kinetic energy transfer from 5 to 2 km altitude within −40 to −20 min, followed by rapid surface downdraft acceleration. Physically, wet events derive intensity from deep instability amplified by moisture enhancement, driving robust convection. Dry events originate from shallow instability released through pulsed downdrafts with weaker gusts. Machine learning attribution (SHAP >0.24) establishes precipitable water as the dominant discriminator (wet: >48 mm; dry: <40 mm). These pre‐storm signatures have great implications for nowcasting SCW events.

Global positioning system (GPS) data from over 260 ground-based permanent stations in China covering the period from 1 March 1999 to 30 April 2015 were used to estimate precipitable water (PW) above each site with an accuracy of about 0.75 mm. Four types of radiosondes (referred to as GZZ2, GTS1, GTS1-1, and GTS1-2) were used in China during this period. Instrumentation type changes in radiosonde records were identified by comparing PW calculated from GPS and radiosonde data. Systematic errors in different radiosonde types introduced significant biases to the estimated PW trends at stations where more than one radiosonde type was used. Estimating PW trends from reanalysis products (ERA-Interim), which assimilate the unadjusted radiosonde humidity data, resulted in an artificial downward PW trend at almost all stations in China. The statistically significant GPS PW trends are predominantly positive, consistent in sign with the increase in moisture expected from the Clausius–Clapeyron relation due to a global temperature increase. The standard deviations of the differences between ERA-Interim and GPS PW in the summer were 3 times larger than the observational error of GPS PW, suggesting that potentially significant improvements to the reanalysis could be achieved by assimilating denser GPS PW observations over China. This work, based on an entirely independent GPS PW dataset, confirms previously reported significant differences in radiosonde PW trends when using corrected data. Furthermore, the dense geographical coverage of the all-weather GPS PW observations, especially in remote areas in western China, provides a valuable resource for calibrating regional trends in reanalysis products.

The Integrated Global Radiosonde Archive (IGRA) is a collection of historical and near-real-time radiosonde and pilot balloon observations from around the globe. Consisting of a foundational dataset of individual soundings, a set of sounding-derived parameters, and monthly means, the collection is maintained and distributed by the National Oceanic and Atmospheric Administration’s National Centers for Environmental Information (NCEI). It has been used in a variety of applications, including reanalysis projects, assessments of tropospheric and stratospheric temperature and moisture trends, a wide range of studies of atmospheric processes and structures, and as validation of observations from other observing platforms. In 2016, NCEI released version 2 of the dataset, IGRA 2, which incorporates data from a considerably greater number of data sources, thus increasing the data volume by 30%, extending the data back in time to as early as 1905, and improving the spatial coverage. To create IGRA 2, 40 data sources were converted into a common data format and merged into one coherent dataset using a newly designed suite of algorithms. Then, an overhauled version of the IGRA 1 quality-assurance system was applied to the integrated data. Last, monthly means and sounding-by-sounding moisture and stability parameters were derived from the new dataset. All of these components are updated on a regular basis and made available for download free of charge on the NCEI website.

Hundreds of supercell proximity soundings obtained for field programs over the central United States are analyzed to reconcile differences in recent studies and to refine our knowledge of supercell environments. The large, storm-centric observation-based dataset and high vertical resolution of the sounding data provide an unprecedented look at supercell environments. Not surprisingly, storm-relative environmental helicity (SRH) is found to be larger in tornadic soundings than in nontornadic soundings. The primary finding that departs from previous studies is that storm-relative winds contribute substantially to the larger SRH. Stronger ground-relative winds and more rightward-deviant storm motions contribute to the larger storm-relative winds for the tornadic soundings. Spatial analyses of the soundings reveal lower near-ground pressure perturbations and stronger low- to midlevel cyclonic flow for the tornadic soundings, which suggests stronger mesocyclones, perhaps explaining the more rightward-deviant motions. Differences in the mean critical angle between the tornadic and nontornadic soundings are small and do not contribute to the larger mean SRH, but the tornadic soundings do have fewer instances of smaller (<60°) critical angles. Furthermore, the critical angle is shown to be a function of azimuth from the updraft. Other results include a low-to-the-ground (~250 m on average) hodograph kink for both the tornadic and nontornadic soundings and few notable differences in thermodynamic quantities, except for the expected lower LCLs related to higher RH for the tornadic soundings, somewhat smaller 0–3 km lapse rates in tornadic environments related to weaker/shallower capping inversions, and larger 0–3 km CAPE in near-field environments.

The mixing layer is an important meteorological factor that affects air pollution. In this study, the atmospheric mixing layer height (MLH) was observed in Beijing from July 2009 to December 2012 using a ceilometer. By comparison with radiosonde data, we found that the ceilometer underestimates the MLH under conditions of neutral stratification caused by strong winds, whereas it overestimates the MLH when sand-dust is crossing. Using meteorological, PM2.5, and PM10 observational data, we screened the observed MLH automatically; the ceilometer observations were fairly consistent with the radiosondes, with a correlation coefficient greater than 0.9. Further analysis indicated that the MLH is low in autumn and winter and high in spring and summer in Beijing. There is a significant correlation between the sensible heat flux and MLH, and the diurnal cycle of the MLH in summer is also affected by the circulation of mountainous plain winds. Using visibility as an index to classify the degree of air pollution, we found that the variation in the sensible heat and buoyancy term in turbulent kinetic energy (TKE) is insignificant when visibility decreases from 10 to 5 km, but the reduction of shear term in TKE is near 70 %. When visibility decreases from 5 to 1 km, the variation of the shear term in TKE is insignificant, but the decrease in the sensible heat and buoyancy term in TKE is approximately 60 %. Although the correlation between the daily variation of the MLH and visibility is very poor, the correlation between them is significantly enhanced when the relative humidity increases beyond 80 %. This indicates that humidity-related physicochemical processes is the primary source of atmospheric particles under heavy pollution and that the dissipation of atmospheric particles mainly depends on the MLH. The presented results of the atmospheric mixing layer provide useful empirical information for improving meteorological and atmospheric chemistry models and the forecasting and warning of air pollution.

The tropopause layer plays a key role in manifold processes in atmospheric chemistry and physics. Here we compare the representation and characteristics of the lapse rate tropopause according to the definition of the World Meteorological Organization (WMO) as estimated from European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Our study is based on 10-year records (2009 to 2018) of ECMWF's state-of-the-art reanalysis ERA5 and its predecessor ERA-Interim. The intercomparison reveals notable differences between ERA5 and ERA-Interim tropopause data, in particular on small spatiotemporal scales. The monthly mean differences of ERA5 minus ERA-Interim tropopause heights vary between −300 m at the transition from the tropics to the extratropics (near 30∘ S and 30∘ N) to 150 m around the Equator. Mean tropopause temperatures are mostly lower in ERA5 than in ERA-Interim, with a maximum difference of up to −1.5 K in the tropics. Monthly standard deviations of tropopause heights of ERA5 are up to 350 m or 60 % larger than for ERA-Interim. Monthly standard deviations of tropopause temperatures of ERA5 exceed those of ERA-Interim by up to 1.5 K or 30 %. The occurrence frequencies of double-tropopause events in ERA5 exceed those of ERA-Interim by up to 25 percentage points at middle latitudes. We attribute the differences between the ERA5 and ERA-Interim tropopause data and the larger, more realistic variability of ERA5 to improved spatiotemporal resolution and better representation of geophysical processes in the forecast model as well as improvements in the data assimilation scheme and the utilization of additional observations in ERA5. The improved spatiotemporal resolution of ERA5 allows for a better representation of mesoscale features, in particular of gravity waves, which affect the temperature profiles in the upper troposphere and lower stratosphere (UTLS) and thus the tropopause height estimates. We evaluated the quality of the ERA5 and ERA-Interim reanalysis tropopause data by comparisons with COSMIC and MetOp Global Positioning System (GPS) satellite observations as well as high-resolution radiosonde profiles. The comparison indicates an uncertainty of the first tropopause for ERA5 (ERA-Interim) of about ±150 to ±200 m (±250 m) based on radiosonde data and ±120 to ±150 m (±170 to ±200 m) based on the coarser-resolution GPS data at different latitudes. Consequently, ERA5 will provide more accurate information than ERA-Interim for future tropopause-related studies.

A set of CMIP6 models is evaluated for the turning of the wind over the planetary boundary layer (PBL) and the corresponding cross-isobaric mass flux. The bulk Richardson number method is used to calculate the height of the PBL to allow for comparisons with a climatology of observed wind-turning angles documented by Lindvall and Svensson based on more than 800 stations in the Integrated Global Radiosonde Archive. Wind-turning angles are found to be underestimated in all models, with the GFDL CM4 model having the closest distribution to the observations. Large, negative cross-isobaric mass fluxes (flow toward higher pressure) are found over high-terrain areas and the North Atlantic stormtrack region in all models and the ERA-Interim reanalysis. Bulk Richardson number–derived PBLs are particularly shallow in the Norwegian Earth System Model, medium atmosphere-medium ocean resolution (NorESM2-MM), likely caused by a change in the turbulence and cloud scheme as compared to the CESM2 model that uses the same atmospheric model, leading to small wind-turning angles and cross-isobaric mass fluxes. Using the 850-hPa level as the upper boundary broadens the wind-turning angle distribution and increases the amount of cross-isobaric mass flux for all models. This makes the models closer to the observations, although substantial differences are still present. The assumption of a constant geostrophic wind throughout the PBL possibly affects the calculated mass fluxes.

The 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. Plain Language Summary Atmospheric disturbances above the troposphere are predominantly associated with waves generated in the troposphere. Among others, gravity waves (GWs) play major roles in transport of energy and momentum from the lower to the upper atmosphere. The double tropopause (DT) caused by irregular temperature changes is a common phenomenon in the lowermost stratosphere, which has an indicative significance for climate change. The upward propagating GWs sourced from the troposphere can probably alter the temperature variability in the tropopause region, and therefore, they are likely associated with the occurrence of DTs. By analyzing a large amount of global radiosonde data, simultaneous measurements of tropospheric GWs and irregularities in the tropopause enable us to argue that GWs sourced from troposphere could increase the likelihood of DTs. Key Points A good level of agreement in spatial‐temporal variability has been identified between Double tropopause (DT) events and tropospheric gravity wave (GW) total energy Substantial tropospheric GW and Kelvin‐Helmholtz instability frequency enhancements in the tropopause region can be observed with DT phenomena The tropospheric GWs may increase the likelihood of DT events by introducing permanent localized irregularities or instabilities