By pinpointing the temporal and spatial key zone where hail precipitation instantaneously responds to cloud condensation nuclei concentration (CCNC) explosions, this study offers significant advancements in understanding CCNC-cloud-hail interactions and the potential for artificial hail suppression. An idealized hailstorm was simulated using high-resolving (500 m) across a comprehensive ensemble comprising 151 runs. This simulation incorporated five distinct time points from convective initiation to hail formation. It encompassed six vertical zones of initial CCNC. Five categories of CCNC explosions between 700 cm-3 and 70,000 cm-3 were considered. The results indicate that the value of the minimum hail precipitation rate is from below 10 % to 45 % of control member with convection development. At the initial time point, hail precipitation rate exhibits a non-monotonic response to CCN concentration, first decreases and then increases. Raindrops' formation (10 and 15 min) shifts the inflexion point. Hail formation (20 min) causes the response to first increase and then decrease. The small cloud droplets from CCNC explosions impede raindrop formation (suppressing hail precipitation, dominant at low CCNC) and promote raindrop growth (enhancing hail precipitation, dominant at high CCNC). As convection develops, the key zone for the response of hail precipitation to CCNC explosions rises from the atmospheric boundary layer region to the 0 degrees C layer. This increase is due to changes in the critical region of microphysical processes at different time points. The CCNC explosion in the key zone causes smaller cloud droplets, rise rapidly to exceed the critical region, and inhibit its collection by hail particles.

Precipitation chemistry can reflect the impacts of both anthropogenic and natural sources on air quality and provide insights into material cycles between the Earth's surface and atmosphere. We explored the chemical characteristics of precipitation in relation to meteorological and environmental factors in Weinan, a key hub for agriculture and ecological protection on the Guanzhong Plain in Northwest China. Precipitation samples (n = 291) collected in Weinan from 2021 to 2022 were analyzed for their chemical compositions using chemometric analysis, correlation analysis, the positive matrix factorization (PMF) model, and the backward trajectory model. The findings revealed that the primary ions in the precipitation were Ca2+, NH4+, SO4 2- and NO3-. The concentrations of most ions were higher in winter and lower in summer due to changes in precipitation amount, humidity, PM2.5 and PM10. The PMF analysis identified six ion sources in precipitation, including crustal sources (24.9 %), secondary formation (20.7 %), waste incineration (16 %), marine sources (15 %), industrial emissions (11.8 %), and biomass burning (11.5 %). The backward trajectory analysis showed that water vapor transport varies seasonally and is primarily influenced by westerly, monsoonal, and regional circulations. The westerly circulation predominantly affects ion concentrations by transporting dust and anthropogenic pollutants to Weinan. The monsoonal circulation carries large amounts of water vapor and contributes the most to precipitation (54.38 %). This study reveals the impacts of natural factors, human activities, and water vapor sources on precipitation chemistry and offers decision support for air quality management and pollution control in Northwest China.

The investigation of chemical composition in hailstones offers valuable insights into cloud physics. Unique characteristics of heavy metals and water‐soluble ions have been detected to provide a comprehensive perspective on their presence and behavior within hailstones. 34 hailstone samples were collected from 12 cities in China between 2016 and 2021. Regional differences in heavy metal concentrations between northern and southern China are influenced by anthropogenic pollution sources. Water‐soluble ions are dominated by distant marine aerosol sources. The most notable distinction is that heavy metals display negligible correlation with PM 10 , whereas water‐soluble ions exhibit a statistically significant relationship. This suggests that chemical components contribute to hailstone formation through diverse pathways. Water‐soluble ions with hygroscopicity primarily act as cloud condensation nuclei (CCN) to promote the formation of cloud droplets. Heavy metals are barely noticeable when attached to aerosol particles due to random collisions with various hydrometeors.

The intricate nature of the physical parameterization schemes within the Weather Research and Forecasting (WRF) Model poses challenges in accurately simulating hailstorms, particularly the complex cloud processes involved. Significant yet robust differences in sensitivities between two different parameterization schemes in two ensembles, namely, the microphysical parameterization (MP) and planetary boundary layer (PBL) parameterization schemes, are found when simulating a hailstorm in the Loess Plateau region of China by comparing with observations. Experiments with variation in the MP scheme overestimate the strong reflectivity region (>45 dBZ) compared to radar observations. Conversely, experiments with variation in the PBL scheme better match observed locations, showing slightly higher peak reflectivity (>55 dBZ) in vertical structure compared to variation in the MP scheme. The reflectivity intensity in experiments with variation in the MP scheme is influenced by elevated rain mixing ratios below the 0 degrees C layer, rain-snow differences between 0 degrees and-38 degrees C, high ice crystal mixing ratios in certain members, and the combination of strong vertical wind shear variations and extensive, intense cold zones. While experiments with variation in the PBL scheme exhibit less variation in hydrometeor mixing ratios compared to variation in the MP scheme, significant differences persist among members, with some members doubling the particle mixing ratio. The reflectivity intensity is impacted by notable differences in the structures of vertical velocity, updraft volume, and the potential temperature perturbation between 0 degrees and-38 degrees C. This study highlights the importance of describing both MP and PBL schemes to improve the accuracy of hailstorm simulations in numeric models.

The growth trajectory of hailstones within clouds has remained elusive due to the inability to trace them directly, impeding the comprehension of their underlying growth mechanisms. This study investigated hailstone vertical growth trajectories by detecting the stable isotope signatures (2H and 18O compositions) of different shells in 27 hailstones from 9 hailstorms, which allowed us to capture the ambient temperature during hailstone growth. The vertical growth trajectories were obtained by comparing the isotopic compositions of water condensate in clouds, derived from the Adiabatic Model, with those measured in hailstones. Although hailstone growth was primarily observed in the −10°C to −30°C temperature layer, the embryo formation height and subsequent growth trajectories significantly varied among hailstones. Embryos formed over a wide range of temperatures (−8.7°C to −33.4°C); four originated at temperatures above −15°C and 16 originated at temperatures below −20°C, suggesting ice nuclei composed of bioproteins and mineral dust, respectively. Among the 27 measured hailstones, 3 exhibited minimal vertical movement, 16 exhibited a monotonic rise or fall, and the remaining 8 exhibited alternating up-down trajectories; only one experienced “recycling” during up-down drifting. Trajectory analysis revealed that similar-sized hailstones from a single storm tended to form at similar heights, whereas those larger than 25 mm in diameter exhibited at least one period of upward growth. Vertical trajectories derived from isotopic analysis were corroborated by radar hydrometeor observations.

The practical predictability of hail precipitation rates is significantly influenced by initial meteorological perturbations, stemming from various uncertainty sources. This study thoroughly assessed the predictability of hail precipitation rates in both climatologically and flow-dependent perturbed ensembles (CEns and FEns). These ensembles incorporated initial meteorological uncertainties derived separately from two operational ensembles. Leveraging the Weather Research and Forecasting model, we conducted cloud-resolving simulations of an idealized hailstorm. The practical predictability of hail responded comparably to both climatological and flow-dependent uncertainties, which was revealed across the entire ensemble of 50 members. However, a notable difference emerged when comparing the peak hail precipitation rates among the top 10 and bottom 10 members. From a thermodynamic perspective, the primary source of uncertainty in hail precipitation lay in the significant variations in temperature stratification, particularly at −20°C and −40°C. On the microphysical front, perturbations within CEns generated greater uncertainty in the process of rainwater collection by hail, contributing significantly to the microphysical growth mechanisms of hail. Furthermore, the findings reveal a stronger dependency of hail precipitation uncertainty on thermodynamic perturbations compared to kinematic perturbations. These insights enhance the comprehension of the practical predictability of hail and contribute significantly to the understanding of ensemble forecasting for hail events.

Understanding how hailstorm trends have changed in the context of climate change is a persistent challenge, mainly because of the lack of long-term consistent observations of hailstorms. Here, we leverage hail damage records from Chinese historical books and extend hailstorm records to approximately 2890 years ago, exploring variations in the number of hailstorm days between 1500 and 1949 based on reliable and consistent data. We show that the number of hailstorm days was constant before 1850, but has increased significantly afterwards. This increase in hailstorm days seems to be associated with the increase in surface temperature after the population effect is removed. In addition to the trend, hailstorm activity is found to display both quasicentennial and multidecadal variability, with the former (later) dominating before (after) the 1850s, driven by the Pacific Decadal Oscillation (PDO). These results suggest that long-term changes in hailstorm days in China are modulated by climate warming and natural variability, via the PDO. Future projections based on different climate change scenarios and a convolutional neural network model show a further increase in the number of hailstorm days in the 21st century.

AbstractDetermination of the key vertical level for cloud condensation nuclei concentration (CCNC) explosions has been a long‐term issue in CCN‐cloud interaction studies. An idealized hailstorm is simulated with 37 sensitivity runs, including an initial CCNC grouping vertically from the ground to the cloud top, increasing from 100 to 3,000 mg−1. The results reveal a key zone from 750 to 800 hPa near the median boundary layer, where an explosion of CCNC plays a dominant role in the nonmonotonic response of the hail precipitation rate. The explosion of CCNC in this zone could initially result in the condensation of more water vapor into the clouds, which could be transported to a greater vertical extent to significantly affect the riming collection efficiency. However, the dominant zone for the total precipitation rate is wider at heights of 700–800 hPa due to the lower sensitivity of the riming collection efficiency.

Water-soluble ions (Cl-, SO42-, NO3-, Ca2+, Mg2+, Na+, K+ and NH4+) and trace elements (Pb, Cd, Cr and As) in snow samples were analyzed from three different snowfall events (I, II, III) in December 2019 at Gande Meteorological Station, located in the southeastern part of the Tibetan Plateau region. From event I to III, the total concentration of water-soluble ions presented an increasing trend of 0.92, 1.43 and 3.01 mg L-1, respectively. The dominant cation was Ca2+ for all the events, while the dominate anion was SO42-, SO42- and Cl- in the event I, II and III, respectively. Meteorological field and backward trajectory cluster analysis presented three different large-scale predominant wind directions of northwest wind, southwest wind and west wind for each event, revealing different transport processes and sources for snow components. The total concentration of watersoluble ions was mainly related to PM10 as the in -situ PM10 observation showed a similar increasing trend. The dominant trace element was different Pb, Cr and Pb in each event. The mixed source of crustal and industrial inputs was the key factor in three snowfalls, and its contribution was consistent with the concentration of dominant trace element. Herein, high fractions of Pb and Ca2+ were appeared in the event I and III, but largest proportion to Cr was enhanced in the event II.

Atmospheric physical sounding data from three ground-based microwave radiometers located in Xi’an were analyzed to explore the temporal and spatial differences of a hailstorm event and were initialized into an idealized Weather Research and Forecasting (WRF) model to predict the total evolution of the event, which occurred on 29 July 2019. Liquid water and relative humidity profiles revealed a consistent sequence of hailstorm intensity among observations from surface meteorological stations and the FY-4A satellite, where the precipitation and cloud top temperature intensified from north to south, corresponding to the locations of the ground-based microwave radiometers in Gaoling, Weiyang, and Chang’an. Compared with those of a similar storm without hail that occurred on 9 August 2018, the humidity profiles and heights at 0 °C and −20 °C exhibited more dramatic changes. The heights at 0 °C and −20 °C obviously increased with a low-value zone in the relative humidity profiles during the strongest stage of the hailstorm in Chang’an and Weiyang. Later, the heights sharply dropped in Chang’an when strong, downward ice-phased hydrometers occurred with hail production in the storm. A time-saving, idealized WRF simulation, initialized with pre-3-h sounding data from ground-based microwave radiometers, was designed to qualitatively predict this hailstorm. The simulations consistently showed a strong-to-weak intensity of storms from Chang’an to Weiyang to Gaoling. Although the first attempt at this model has uncertainties in both the observations and the model, it provides a potential new method for single-point fine hailstorm prediction.

基于2000—2019年99个地面观测站记录的冰雹数据及ECMWF提供的ERA5各项参数月平均数据,结合线性回归、5a滑动平均等方法,分析了陕西省冰雹变化特征及关键影响因素.结果表明:(1)陕西省冰雹次数在地理位置上呈现由南到北增加的特征,海拔高度与年平均冰雹次数在低海拔表现出显著的正相关关系.(2)陕西省冰雹受季节影响程度呈现由南到北增强的特征,其中陕北、关中冰雹次数夏多冬少,陕南冰雹次数各季节相对平均.(3)陕西省年际冰雹次数整体呈下降趋势,其中陕北地区下降速度最快,关中地区其次,而陕南地区年际变化无明显变化趋势.(4)对流有效位能(CAPE)对陕西省冰雹年际趋势起主导作用;K指数对陕北夏季、关中春季冰雹次数变化趋势起主导作用;0℃层高度对关中夏、秋季与陕南春、夏季冰雹次数变化趋势起主导作用.

There are increasing concerns about the uncertainty aerosols produced in forecasting precipitation, particularly hail. This study provides an assessment of the contribution of aerosols to hail predictability by varying both the cloud condensation nuclei concentration (CCNC) and the initial meteorological conditions based on ensemble runs of 1,200 cloud‐resolving simulations. Although the meteorological perturbations produce large uncertainties in both hail and total precipitation, varying CCNC by an order of magnitude causes even larger uncertainties than the meteorological perturbations. Changing CCNC modifies the predictability of hail precipitation, with higher predictability in moderately polluted environments compared with very clean and polluted environments. Perturbing the initial meteorological conditions does not qualitatively change how aerosols affect hail and total precipitation. Constraining the initial meteorological perturbations helps reduce CCNC‐caused uncertainty. These findings suggest the importance of considering aerosol effects in severe weather simulations and forecasting.

The terrain effects of Qinling–Daba Mountains on reginal precipitation during a warm season were investigated in a two-month day-to-day experiment using the Weather Research and Forecasting (WRF) model. According to the results from the terrain sensitivity experiment with lowered mountains, Qinling–Daba Mountains have been found to have an obvious effect on both the spatial-temporal distribution and diurnal cycle of reginal precipitation from July to August in 2019, where the Qinling Mountains mainly enhanced the precipitation around 34° N, and the Daba Mountains mainly enhanced it around 32° N at the time period of early morning and midnight. Horizontal distribution of water vapor and convective available potential energy (CAPE), as well as cross section of vertical velocity of wind and potential temperature has been studied to examine the key mechanisms for these two mountains’ effect. The existence of Qinling Mountains intercepted transportation of water vapor from South to North in the lower troposphere to across 34° N and caused an obvious enhancement of CAPE in the neighborhood, while the Daba Mountains intercepted the northward water vapor transportation to across 32° N and caused an enhanced CAPE nearby. The time period of the influence is in a good accordance with the diurnal cycle. In the cross-section, the existence of Qinling Mountains and Daba Mountains are found to stimulate the upward motion and unstable environment effectively at around 34° N and 32° N, separately. As a result, the existence of the two mountains lead to a favorable environment in water vapor, thermodynamic, and dynamic conditions for this warm season precipitation.

Hail is produced by all types of deep convective storms and occurs commonly for short periods in most parts of the world [1].The growth path of hailstones in hailstorms remains largely uncertain [2-4].Due to the limitations hampering direct observations of severe hailstorms, it is difficult to identify definitively the in-cloud conditions and hailstone growth trajectories that lead to hailstone formation [2,3].However, natural hailstones can provide insights into hydrometeors and aerosols in deep convective storms.Hailstones have been collected and examined, and various techniques have been applied to measure representative atmospheric chemical isotopes [2,5], which is of great help when investigating hailstones' origin and structure, as well as for understanding the microphysical mechanisms and aerosol-collectionprocesses in hailstorms [2,5,6].

The sensitivity of hail precipitation from an idealized hailstorm to realistic environmental uncertainties was investigated through ensembles of cloud‐resolving simulations using the Weather Research and Forecasting model, with initial condition perturbations derived from the European Centre for Medium‐Range Weather Forecasting (ECMWF) operational ensemble. The analyses revealed that hail precipitation rate was very sensitive to small initial environmental perturbations, particularly in thermodynamic variables. The hail precipitation rate was significantly positively correlated with perturbations to the initial potential temperature below 750 hPa and to water vapor mixing ratio above 750 hPa. These small initial perturbations led to subsequent substantial differences in hail precipitation as well as in characteristics of the parent storm (e.g., updraft velocity, diabatic heating, and microphysical processes), all of which play a key role in hail growth. The larger sensitivity of hail precipitation to thermodynamic rather than kinematic environmental initial condition perturbations persisted even when the magnitude of the perturbations was reduced to 10% of the realistic uncertainties derived from the ECMWF ensemble. In the ensemble with reduced‐amplitude initial perturbations, there was still a moderately strong positive correlation between hail precipitation rate and the initial perturbations of the thermodynamic variables. However, these sensitivities were nonlinear, suggesting that the intrinsic predictability of hail precipitation rate may be limited, even when environmental uncertainties are reduced to 10%, 1.0 × 10−3, and 1.0 × 10−5 of the currently realistic magnitude of initial condition uncertainty.

The hail day climatology from 1961 to 2005 was previously studied based on hundreds of surface stations in China. Recently, both hail occurrence and maximum hail diameter (MHD) data from more than 2000 surface stations were released by the National Meteorological Information Center of China. These data enable hail climatology to be explored using both hail frequency (HF), which is defined as annual mean hail occurrence, and MHD records from more stations over the entire country. Following quality control, hail data from 2254 stations were selected for the period of 1980-2015. In general, HF increased with station topography height, with a maximum of more than 30 events per year in the Tibetan Plateau and a minimum of less than 1 event per year in southern China, whereas the station mean MHD decreased with topography height. The highest peak of the 80th-percentile cumulative distribution function of the annual MHD cycle in southern China occurred in May but was delayed to July in the north. Severe hail (MHD 20 mm; 5.32% of all cases) mainly occurred along the edge of the plain, near the mountainsides, and was most likely to develop in the afternoon.

>Natural hailstones were collected and analyzed in the laboratory not only for their physical properties (e.g., structure, density,shape, and air bubbles), but also for their chemical properties(e.g., organic particles, biological particles, and water-soluble ions),which can help a clear understanding on microphysics and development of hailstorms [1–4]. Aerosol particles were carried up from the atmospheric boundary layer to the free atmosphere into the

The effects of the initial cloud condensation nuclei (CCN) concentrations (100–3000 mg−1) on hail properties were investigated in an idealized non-severe hail storm experiment using theWeather Research and Forecasting (WRF) model, with the National Severe Storms Laboratory 2-moment microphysics scheme. The initial CCN concentration (CCNC) had obvious non-monotonic effects on the mixing ratio, number concentrations, and radius of hail, both in clouds and at the surface, with a CCNC threshold between 300 and 500 mg−1. An increasing CCNC is conducive (suppressive) to the amount of surface hail precipitation below (above) the CCNC threshold. The non-monotonic effects were due to both the thermodynamics and microphysics. Below the CCNC threshold, the mixing ratios of cloud droplets and ice crystals increased dramatically with the increasing CCNC, resulting in more latent heat released from condensation and frozen between 4 and 8 km and intensified updraft volume. The extent of the riming process, which is the primary process for hail production, increased dramatically. Above the CCNC threshold, the mixing ratio of cloud droplets and ice crystals increased continuously, but the maximum updraft volume was weakened because of reduced frozen latent heating at low level. The smaller ice crystals reduced the formation of hail and smaller clouds, with decreased rain water reducing riming efficiency so that graupel and hail also decreased with increasing CCNC, which is unfavorable for hail growth.

The response of hailstorm intensity to climate variability/change has become a topic of community interest recently. But the lack of persistent and homogenous observations makes it difficult to confidently describe its interannual variations. Hail size, as a common indicator of hailstorm intensity, displays distinct regional variability. Here, for the first time, we show robust evidence of a decrease in hail size using continuous and coherent hail size records from 2,254 manned stations in China since 1980. The stations were categorized based on their elevation: plateaus (above 2000 m), foothills (between 500 and 2000 m), and plains (below 500 m). Compared with 1980–1997, the hail size spectra from 1998 to 2015 all shifted toward smaller sizes significantly in plateaus, foothills, and plains. The proportion of overall hail events with maximum sizes of at least 5 and 20 mm significantly decreased since 1980. Meanwhile, the annual mean size of hail above 10 and 20 mm significantly decreased during the research period, especially after 1990. These changes in the hail size spectra may imply a weakened intensity of hailstorms in China in recent decades.