Graupel Particles Research Articles

Numerical simulation of the cloud seeding operation of a convective rainfall event occurred in Beijing

Observation-validated cloud seeding simulation is valuable in assisting in evaluating seeding effect, but its sensitivity to microphysics schemes and cloud seeding parameterizations is rarely investigated. In this research three cloud seeding parameterizations (the Hsie, Demott and Xue parameterizations) are coupled with two microphysics schemes (the Thompson and Milbrandt schemes), to perform simulations of the rainfall suppression cloud seeding operation on a convective rainfall event occurred in North China on 1 July 2021, aiming to evaluate the seeding effect and investigate its sensitivity to microphysics schemes and seeding parameterizations. The differences of rainfall suppression effect between three seeding parameterizations are smaller than those between two microphysics schemes. The rainfall suppression ratios produced by the simulations configured with the Milbrandt scheme range from 16.3% to 24.7%, while those with the Thompson scheme range from 0.47% to 1.38%. The difference of the seeding effect between these two microphysics schemes arises from their different method in parameterizing the snow deposition growth process. In addition, in the seeding simulations with the Milbrandt scheme, the surface rainfall decrease region is followed by a rainfall increase region. This rainfall decrease-increase pattern is caused by the fact that the reduced graupel particles caused by cloud seeding falls to the ground earlier with its larger fall velocity, while the seeding-increased snow particle falls to the ground later due to its smaller fall velocity. This result suggests there is an ephemeral cloud seeding window for rainfall suppression operation.

Joint Retrieval of Multiple Species of Ice Hydrometeor Parameters from Millimeter and Submillimeter Wave Brightness Temperature Based on Convolutional Neural Networks

Submillimeter wave radiometers are promising remote sensing tools for sounding ice cloud parameters. The Ice Cloud Imager (ICI) aboard the second generation of the EUMETSAT Polar System (EPS−SG) is the first operational submillimeter wave radiometer used for ice cloud remote sensing. Ice clouds simultaneously contain three species of ice hydrometeors—ice, snow, and graupel—the physical distributions and submillimeter wave radiation characteristics of which differ. Therefore, jointly retrieving the mass parameters of the three ice hydrometeors from submillimeter brightness temperatures is very challenging. In this paper, we propose a multiple species of ice hydrometeor parameters retrieval algorithm based on convolutional neural networks (CNNs) that can jointly retrieve the total content and vertical profiles of ice, snow, and graupel particles from submillimeter brightness temperatures. The training dataset is generated by a numerical weather prediction (NWP) model and a submillimeter wave radiative transfer (RT) model. In this study, an end to end ICI simulation experiment involving forward modeling of the brightness temperature and retrieval of ice cloud parameters was conducted to verify the effectiveness of the proposed CNN retrieval algorithm. Compared with the classical Unet, the average relative errors of the improved RCNN–ResUnet are reduced by 11%, 25%, and 18% in GWP, IWP, and SWP retrieval, respectively. Compared with Bayesian Monte Carlo integration algorithm, the average relative error of the total content retrieved by RCNN–ResUnet is reduced by 71%. Compared with BP neural network algorithm, the average relative error of the vertical profiles retrieved by RCNN–ResUnet is reduced by 69%. In addition, this algorithm was applied to actual Advanced Technology Microwave Sounder (ATMS) 183 GHz observed brightness temperatures to retrieve graupel particle parameters with a relative error in the total content of less than 25% and a relative error in the profile of less than 35%. The results show that the proposed CNN algorithm can be applied to future space borne submillimeter wave radiometers to jointly retrieve mass parameters of ice, snow, and graupel.

Quantifying riming from airborne data during the HALO-(AC)3 campaign

Abstract. Riming is a key precipitation formation process in mixed-phase clouds which efficiently converts cloud liquid to ice water. Here, we present two methods to quantify riming of ice particles from airborne observations with the normalized rime mass, which is the ratio of rime mass to the mass of a size-equivalent spherical graupel particle. We use data obtained during the HALO-(AC)3 aircraft campaign, where two aircraft collected radar and in situ measurements that were closely spatially and temporally collocated over the Fram Strait west of Svalbard in spring 2022. The first method is based on an inverse optimal estimation algorithm for the retrieval of the normalized rime mass from a closure between cloud radar and in situ measurements during these collocated flight segments (combined method). The second method relies on in situ observations only, relating the normalized rime mass to optical particle shape measurements (in situ method). We find good agreement between both methods during collocated flight segments with median normalized rime masses of 0.024 and 0.021 (mean values of 0.035 and 0.033) for the combined and in situ method, respectively. Assuming that particles with a normalized rime mass smaller than 0.01 are unrimed, we obtain average rimed fractions of 88 % and 87 % over all collocated flight segments. Although in situ measurement volumes are in the range of a few cubic centimeters and are therefore much smaller than the radar volume (about 45 m footprint diameter at an altitude of 500 m above ground, with a vertical resolution of 5 m), we assume they are representative of the radar volume. When this assumption is not met due to less homogeneous conditions, discrepancies between the two methods result. We show the performance of the methods in a case study of a collocated segment of cold-air outbreak conditions and compare normalized rime mass results with meteorological and cloud parameters. We find that higher normalized rime masses correlate with streaks of higher radar reflectivity. The methods presented improve our ability to quantify riming from aircraft observations.

Sensitivity of summer precipitation simulation to the physical parameterizations in WRF over the Tibetan Plateau: A case study of 2018

The Tibetan Plateau (TP) holds a pivotal position in regional and global climate, whereas the atmospheric characteristics vary greatly in the simulation with different physical parameterization schemes at the gray-zone scale (around 9 km). In this study, 24 sets of experiments were set up with different cumulus parameterization schemes (CPSs), microphysics parameterization schemes (MPSs) and planetary boundary layer parameterization schemes (PBLSs) using the WRF model driven by the ERA5 reanalysis to explore the sensitivity and try to summarize a combination of parameterization schemes suitable for the simulation over TP. Based on comparisons against in-situ observations, most CPS experiments showed large wet bias and overestimated occurrence of precipitation events, and CTL without CPS and CU6 with Tiedtke CPS show better performance at gray-zone scale. The influence of MPS and PBLS is less than CPS on the simulation, and Thompson MPS and UW PBLS showed a better performance. Most of the CPS experiments reach an earlier and more intensive peak compared to the Integrated Multi-satellite Retrievals for GPM (IMERG) version 6 satellite precipitation product, except CTL, CU11, and CU6, which show closer but weaker peaks. CPS experiments simulate more precipitation associated with water vapor transporting into TP and anomalous cyclonic circulation against CTL. The less water vapor transport from the south edge of TP in the CTL against CU14, CU16, and CU2, leads to more local precipitation. Graupel particles and the warm-rain process play a crucial role in the precipitation simulation with different MPSs. Although with less water vapor in the low atmosphere, MP2 simulates more precipitation due to more graupel particles and warm-rain processes against CTL. PBLSs have a substantial impact on latent heat, then influence evaporation and precipitation. The lower PBL height usually leads to more latent heat and more precipitation.

Observation of a dramatic increase in the positive cloud-to-ground lightning in the Indian summer monsoon season

Lightning is known for its meteorological importance and associated hazard potential. It is known that the polarity of cloud-to-ground flash (CG) can act as a prognosis of the storm's characteristics. Ground-based observation of lightning over the Indian region suggests that during the break period in the summer monsoon seasons, CG lightning of positive polarity increases dramatically relative to the pre-monsoon days. Here we propose that for thunderstorms forming in the wet season, the non-inductive charge separation happens in the presence of larger mean cloud liquid water in the mixed phase region of the storms. This facilitates the positive charging of graupel particles, thereby producing a large amount of positive CG lightning on these days. This observation is found to be consistent with the laboratory results of Takahashi (1978). The implication of these results has been discussed from the perspective of hazard mitigation associated with positive lightning over India.

Influence of cloud microphysics schemes on weather model predictions of heavy precipitation

Abstract. Cloud microphysics is one of the major sources of uncertainty in numerical weather prediction models. In this work, the ability of a numerical weather prediction model to correctly predict high-impact weather events, i.e., hail and heavy rain, using different cloud microphysics schemes is evaluated statistically. Polarimetric C-band radar observations over 30 convection days are used as the observation dataset. Simulations are made using the regional-scale Weather Research and Forecasting (WRF) model with five microphysics schemes of varying complexity (double moment, spectral bin (SBM), and Predicted Particle Properties (P3)). Statistical characteristics of heavy-rain and hail events of varying intensities are compared between simulations and observations. All simulations, regardless of the microphysics scheme, predict heavy-rain events (15, 25, and 40 mm h−1) that cover larger average areas than those observed by radar. The frequency of these heavy-rain events is similar to radar-measured heavy-rain events but still scatters by a factor of 2 around the observations, depending on the microphysics scheme. The model is generally unable to simulate extreme hail events with reflectivity thresholds of 55 dBZ and higher, although they have been observed by radar during the evaluation period. For slightly weaker hail/graupel events, only the P3 scheme is able to reproduce the observed statistics. Analysis of the raindrop size distribution in combination with the model mixing ratio shows that the P3, Thompson two-moment (2-mom), and Thompson aerosol-aware schemes produce large raindrops too frequently, and the SBM scheme misses large rain and graupel particles. More complex schemes do not necessarily lead to better results in the prediction of heavy precipitation.

Impacts of microphysical parameterizations on banded convective system in convection-permitting simulation: a case study

The representation of cloud microphysical processes in models has always been a challenge leading to uncertainty in convective simulations. This paper evaluates the effect of cloud microphysical parameterizations on the simulation of mesoscale convective systems (MCSs) through a realistic banded convection process. A series of numerical simulation experiments are performed using the Weather Research and Forecasting (WRF) model at a convection-permitting scale with a 3 km horizontal grid spacing. Specifically, four experiments considering different hydrometeor species within the WRF single-moment-microphysics schemes (WSMMPs) are conducted, and three additional sensitivity tests change the graupel particle properties. The results indicate that the significant differences in the times of convection initiation across the experiments reach 120 min, and more hydrometeor species may lead to later convection initiation. Moreover, the frozen graupel hydrometeor characteristics can appreciably alter the simulated convective morphology, even more than other hydrometeor species. When the graupel becomes smaller (such as Graupel-like), the fall speed of the graupel particles decreases. Therefore, more numerous graupel particles reside in clouds for a longer time, and experience more atmospheric diabatic heating and cooling effects. As a result, the simulated convective systems exhibit strong banded convective echo characteristics, the surface 10-m wind gust increases, and the cold pools associated with additional melting and evaporation become stronger, accelerating the propagation of the system. In contrast, larger and less abundant graupels (e.g., Hail-like) have a faster fall speed, and the atmospheric diabatic heating and cooling decrease by shortening the duration of their residence time within the clouds, resulting in a weak quasi-linear convective system, weak surface 10-m wind gust, unobvious cold pool, and slower propagation. Comparisons of the experiments further demonstrate that the fall speeds of frozen graupel particles largely impact the vertical distribution of the hydrometeors and the related microphysical processes.

Aerosol Impacts on Storm Electrification and Lightning Discharges Under Different Thermodynamic Environments

AbstractThe impacts of aerosol and thermodynamics on electrification and lightning activities have been investigated in detail using the Weather Research and Forecasting Model coupled with a double‐moment microphysics parameterization and an explicit electrification lightning scheme. To obtain a varied combination of convective available potential energy (CAPE) values and aerosol concentrations, a sounding was modified consistently and initiated with five sets of aerosol concentrations that served as cloud condensation nuclei. The simulated electric processes respond to the varying dynamical and microphysical characteristics associated with the different CAPE and aerosol conditions. Under high CAPE circumstances, the augmentation of ice‐phase particle leads to the enhancement of non‐inductive charging primarily through the dynamic processes. Increased aerosol content further invigorates the electrification through microphysical processes. Elevated aerosol loading under low CAPE conditions increases cloud droplet and ice crystal numbers. Larger graupel particle size further leads to the enhanced electric intensity and lightning discharges.

Simulation Study of Microphysical and Electrical Processes of a Thunderstorm in Sichuan Basin

Based on the Morrison Two-Moment Scheme coupled with the non-inductive electrification mechanism and the discharge parameterization scheme in the Weather Research and Forecasting (WRF) model, a thunderstorm process was simulated by using the WRF electrical coupling model in Sichuan Basin on 21 July 2019, in this paper. Through analysis and discussion of the macroscopic and microscopic characteristics of the thunderstorm activity and the microphysical and dynamic processes, respectively, the study shows that the simulation results of radar echo and lightning are well consistent with the meteorological observation which indicates the WRF model has a certain ability to reproduce the thunderstorm process in Sichuan Basin, there is a good correspondence between the main electrification area and the distribution position of the ice-phase particles in the thunderstorm. The simulated charge structure of the thunderstorm is that the graupel particles are mainly negatively charged, the ice crystals and snow particles are mainly positively charged, and the thunderstorm shows a dipole charge structure with an upper positive charge center and a lower negative charge center. It also shows that the updrafts greatly influence ice-graupel and snow-graupel collisions during the thunderstorm discharge process, the higher the updraft speed, the stronger the electrical activity, and, especially, the stronger the discharge process of ice-particle collisions and separation.

The numerical study on the sensitivity of different auto-conversion parameterization to CCN concentration

The auto-conversion from cloud droplet to raindrop is a process whereby rain drops formed by collision-coalescence of cloud droplets. As an essential link connecting aerosol-cloud interaction, it significantly influences the changes in cloud morphology and precipitation. In order to explore the sensitivity of auto-conversion schemes to cloud condensation nuclei (CCN) concentration, using the auto-conversion scheme in the Thompson scheme (TH-AU) and Milbrandt-Yau scheme (MY-AU), we set four groups of CCN concentrations to simulate a strong convection process in Ningxia region of China. The results show that: The sensitivity of different auto-conversion schemes to changes in CCN concentrations varies significantly, and the aerosol-induced changes in precipitation and convection strongly depend on the auto-conversion scheme. With the increase of CCN concentration, the mixing ratio of cloud droplets increases, and the particle size decreases, resulting in a decrease in the auto-conversion intensity for the two schemes, which makes more supercooled water participate in the ice phase process. Compared with the TH-AU, the MY-AU has lower auto-conversion intensity at the same CCN concentration, the proportion of supercooled cloud droplets participating in the ice phase process is higher than that in the TH-AU, which leads to the raindrop mixing ratio of 4000–6000 m in MY-AU is lower than that in TH-AU at the same CCN concentration, and the mixing ratio of ice phase particles in MY-AU scheme is higher in the convective mature stage, especially snow and graupel particles, and the graupel particle generation height of MY-AU is lower than that of TH-AU. In terms of dynamic structure, with the increase of CCN concentration, more cloud droplets are activated and frozen which makes the enhancement of updraft mainly occur in the upper layer in both schemes, but the stronger gravitational drag caused by graupel particles in MY-AU may enhance the downdraft in the middle and lower layers, which makes the convection of MY-AU decay early at higher CCN concentration. In addition, changes in microphysical processes also lead to differences in cumulative precipitation and accumulated ground graupel-fall of the two schemes. The cumulative precipitation and the accumulated ground graupel-fall of the MY-AU decrease strongly with the increase of CCN concentration because the warm rain process of MY-AU is strongly inhibited. Compared with MY-AU, the warm rain process of TH-AU is not significantly inhibited, which leads to the cumulative precipitation and the accumulated ground graupel-fall of the TH-AU scheme increases when the CCN concentration is 50–200 cm−3 and slightly decreases when the CCN concentration is 200–10000 cm−3.

Analysis of Pre-Monsoon Convective Systems over a Tropical Coastal Region Using C-Band Polarimetric Radar, Satellite and Numerical Simulation

Analysis of pre-monsoon convective systems over the southern peninsular India has been performed using C-band radar and numerical simulation. Statistics on the radar polarimetric measurements show that the distribution of differential reflectivity (Zdr) and specific differential phase (Kdp) have much higher spread over convective regions. The distribution of Kdp is almost uniform across the vertical over the stratiform regions. The mean profile of Zdr over stratiform regions shows a distinct local maxima near melting level. A comprehensive analysis has been done on an isolated deep convective system on 13 May 2018. Plan position indicator (PPI) diagrams and satellite measured cloud top temperature demonstrate that pre-monsoon deep convective systems can develop very rapidly within a very short span of time over the region. Heavy precipitation near the surface is reflected in the high value of Kdp (>5° km−1). High values of Zdr (>3 dB) were measured at lower levels indicating the oblate shape of bigger raindrops. A fuzzy logic-based hydrometeor identification algorithm has been applied with five variables (Zh, Zdr, ρhv, Kdp, and T) to understand the bulk microphysical properties at different heights within the storm. The presence of bigger graupel particles near the melting layer indicates strong updrafts within the convective core regions. The vertical ice hydrometeor signifies the existence of a strong electric field causing them to align vertically. Numerical simulation with the spectral bin microphysics (SBM) scheme could produce most of the features of the storm reasonably well. In particular, the simulated reflectivity, graupel mixing ratio and rainfall were in good agreement with the observed values.

Numerical Simulation of a Typical Convective Precipitation and Its Cloud Microphysical Process in the Yushu Area, Based on the WRF Model

Cloud microphysical processes significantly impact the time variation and intensity of precipitation. However, due to the high altitude of the Tibetan Plateau (TP) and the lack of observational data, the understanding of cloud microphysical processes on the TP is relatively insufficient, affecting the accuracy of precipitation simulations around the TP. To further reveal the characteristics of convective precipitation and cloud microphysical structure over the TP, the mesoscale numerical model, WRF, and various observational data were used to simulate and evaluate typical convective precipitation in the Yushu area, which was recorded from 11 to 12 August 2020. The results showed that the combination of the Lin scheme in the WRF model could effectively reproduce this case’s characteristics and evolution process. In the simulation process, the particles of each phase were distributed at different altitudes, and their mass and density over time reflected the characteristics of surface precipitation changes. Among the particles mentioned above, rainwater contributed the most to the initiation and growth of graupel particles. Further research established that the initiation of graupel was mainly affected by the freezing effect of rainwater and cloud ice, while the growth of graupel was influenced primarily by the collision of graupel particles and rainwater. On the whole, from the evolution characteristics of microphysical processes over time, it was found that the ice phase process plays an essential role in this typical convective precipitation.

The Impacts of Midlevel Moisture on the Structure, Evolution, and Precipitation of Afternoon Thunderstorms: A Real-Case Modeling Study at Taipei on 14 June 2015

Abstract A severe afternoon thunderstorm (ATS) system developed within the Taipei basin on 14 June 2015, which produced intense rainfall (with a rainfall rate of 131 mm h−1) and urban-scale flooding. A control simulation (CNTL) using the Weather Research and Forecasting (WRF) Model with the horizontal grid size nested down to 500 m was performed to capture reasonably well the onset of the sea breeze, the merger of convective cells, and the evolution of the afternoon thunderstorm system. Four numerical sensitivity experiments with the increase or decrease of midlevel (700–500 hPa) relative humidity (RH) of 10% and 20% were conducted, and simulation results were compared with those from the CNTL. Although the response of convection to midlevel RH was somewhat nonlinear, sensitivity experiments showed that a dry layer at middle levels would result in stronger cold pool, more intense convection, stronger updraft, more graupel particles, stronger net latent heating above the melting level, and a much larger area of the potential flooding region [>40 mm (30 min)−1]. The estimation of bulk entrainment rate provided evidence that the entrainment rate could be reduced by stronger cold pool and the widening of moist convection area. Three terrain-removal sensitivity experiments indicated that Taipei basin modulated the response of convection intensity to midlevel RH. The basin terrain confined the outflow associated with ATS and forced it to converge with the moist sea breeze continuously, providing a favorable dynamic and thermodynamic environment for subsequent convection development. This “basin confinement effect” may be crucial for short-duration rainfall extremes over complex terrain. Significance Statement This study has examined the impact of midlevel moisture on the structure, evolution, and precipitation of an afternoon thunderstorm system that produced intense rainfall at Taipei using eight numerical experiments based on high-resolution model outputs. Our findings explain how a drier layer at middle levels would produce a more intense thunderstorm system, although the response of convection intensity to midlevel moisture is somewhat nonlinear. In addition, it is found that terrain could modulate the response of convection to midlevel moisture, which is rarely discussed in previous studies.

Radar Diagnosis of the Thundercloud Electron Accelerator

AbstractThunderstorm Ground Enhancements (TGEs) refer to correlated enhancements in surface electric field and gamma ray flux that are manifestations of electron runaway in the storm overhead. The electric field enhancements can be of positive or negative polarity. In this study, altitude‐resolved S‐band radar observations of graupel are used to demonstrate distinct differences in storm structure linked with these “positive” and “negative” TGEs. The physical interpretation rests on the well‐established temperature‐dependent tripole structure of thunderstorms, with the main negative charge of the tripole acting as an electron repeller. This interpretation is supported by case studies showing altitude‐stable convection, with shallow (deep) development linked with “positive” (“negative”) TGEs, and by case studies of collapsing storms that show upper dipole dominance early and lower inverted dipole dominance later when graupel particles descend from a colder to warmer temperature domain. In the case of many TGEs on Mt Aragats (3.2 km MSL), the temperature‐dependent altitude of downward electron acceleration and avalanching may be sufficiently distant (>500 m) from surface detectors that the energetic electrons (1–10 MeV) are not likely avalanche/runaway electrons. Instead, they are Compton‐scattered and pair‐produced electrons from bremsstrahlung gamma radiation emanating from the high‐field avalanche region aloft. These inferences are consistent with GEANT4 calculations that identify the physical origins of energetic electrons at the surface.

Identification of Concurrent Clear-Air and Precipitation Doppler Profiles for VHF Radar and an Incorporating Study of Strongly Convective Precipitation with Dual-Polarized Microwave Radiometer

Two approaches were designed to identify the echoes of clear air and precipitation when both coexist in the very-high-frequency (VHF) radar spectra: contour-based and peak-finding methods. The contour-based approach was used to model a 2D Doppler spectra to determine the locations of multiple spectral humps, and the peak-finding approach was used to find the spectral peaks on request. Grouping, sifting, and Gaussian fitting were performed further for such obtained contour centres and spectral peaks to yield Doppler velocities and spectral widths. In general, the two approaches resulted in corresponding outcomes and can be complementary to find the spectral peaks as fully as possible. The Doppler velocities retrieved from the two approaches were cooperatively used to develop an effective process of Doppler profiling for treating a great amount of radar data, which was validated with the radar data collected during a rainy and strongly convective atmosphere. As an application of Doppler profiling results, the hydrometeor parameters measured by a dual-polarized microwave radiometer were investigated jointly with radar observation, showing that a strong updraft air could bring the liquid water to a height above the melting layer and then the Bergeron effect and coalescence processes on formation of ice crystals and graupel particles occur accordingly.

Evaluation of convective cloud microphysics in numerical weather prediction models with dual-wavelength polarimetric radar observations: methods and examples

Abstract. The representation of cloud microphysical processes contributes substantially to the uncertainty of numerical weather simulations. In part, this is owed to some fundamental knowledge gaps in the underlying processes due to the difficulty of observing them directly. On the path to closing these gaps, we present a setup for the systematic characterization of differences between numerical weather model and radar observations for convective weather situations. Radar observations are introduced which provide targeted dual-wavelength and polarimetric measurements of convective clouds with the potential to provide more detailed information about hydrometeor shapes and sizes. A convection-permitting regional weather model setup is established using five different microphysics schemes (double-moment, spectral bin (“Fast Spectral Bin Microphysics”, FSBM), and particle property prediction (P3)). Observations are compared to hindcasts which are created with a polarimetric radar forward simulator for all measurement days. A cell-tracking algorithm applied to radar and model data facilitates comparison on a cell object basis. Statistical comparisons of radar observations and numerical weather model runs are presented on a data set of 30 convection days. In general, simulations show too few weak and small-scale convective cells. Contoured frequency by altitude diagrams of radar signatures reveal deviations between the schemes and observations in ice and liquid phase. Apart from the P3 scheme, high reflectivities in the ice phase are simulated too frequently. Dual-wavelength signatures demonstrate issues of most schemes to correctly represent ice particle size distributions, producing too large or too dense graupel particles. Comparison of polarimetric radar signatures reveals issues of all schemes except the FSBM to correctly represent rain particle size distributions.

Using artificial neural networks to predict riming from Doppler cloud radar observations

Abstract. Riming, i.e., the accretion and freezing of supercooled liquid water (SLW) on ice particles in mixed-phase clouds, is an important pathway for precipitation formation. Detecting and quantifying riming using ground-based cloud radar observations is of great interest; however, approaches based on measurements of the mean Doppler velocity (MDV) are unfeasible in convective and orographically influenced cloud systems. Here, we show how artificial neural networks (ANNs) can be used to predict riming using ground-based, zenith-pointing cloud radar variables as input features. ANNs are a versatile means to extract relations from labeled data sets, which contain input features along with the expected target values. Training data are extracted from a data set acquired during winter 2014 in Finland, containing both Ka- and W-band cloud radar and in situ observations of snowfall by a Precipitation Imaging Package from which the rime mass fraction (FRPIP) is retrieved. ANNs are trained separately either on the Ka-band radar or the W-band radar data set to predict the rime fraction FRANN. We focus on two configurations of input variables. ANN 1 uses the equivalent radar reflectivity factor (Ze), MDV, the width from left to right edge of the spectrum above the noise floor (spectrum edge width – SEW), and the skewness as input features. ANN 2 only uses Ze, SEW, and skewness. The application of these two ANN configurations to case studies from different data sets demonstrates that both are able to predict strong riming (FRANN > 0.7) and yield low values (FRANN ≤ 0.4) for unrimed snow. In general, the predictions of ANN 1 and 2 are very similar, advocating the capability of predicting riming without the use of MDV. The predictions of both ANNs for a wintertime convective cloud fit with coinciding in situ observations extremely well, suggesting the possibility to predict riming even within convective systems. Application of ANN 2 to an orographic case yields high FRANN values coinciding with observations of solid graupel particles at the ground.

Graupel Precipitating From Thin Arctic Clouds With Liquid Water Paths Less Than 50 g m−2

AbstractRimed precipitation growth can efficiently remove moisture and aerosols from the boundary layer, yet thin low‐level Arctic mixed‐phase clouds are generally thought to precipitate pristine and aggregated ice crystals. Here we present automated surface photographic measurements showing that only 34% of precipitation particles exhibit negligible riming and that graupel particles in diameter commonly fall from clouds with liquid water paths less than 50 g m−2. Analyses indicate that significant riming enhancement can occur provided sustained updrafts of 0.4 m s−1, consistent with those measured in Arctic clouds. A Lagrangian numerical simulation that tracks falling particles suggests that similar updraft speeds can account for about one half of the observed riming enhancement. Riming enhancement appears particularly likely when weak temperature inversions are observed at cloud top, but a full explanation remains to be determined.

Parameterizations of different hydrometeor spectral relative dispersion in the convective clouds

Spectral relative dispersion of different hydrometeors is vital to accurately describe sedimentation. Here, the Weather Research and Forecasting model with spectral bin microphysics is used to simulate convective clouds in Shouxian of Anhui province in China to study the spectral relative dispersion of different hydrometeors. Firstly, regardless of clean or polluted conditions, the relative dispersion of ice crystal spectra and its volume-mean diameter are negatively correlated, while the relative dispersion of other hydrometeor spectra is positively related to their respective volume-mean diameter. The correlations for cloud droplets and raindrops are affected by the process of collision–coalescence; the correlations for ice crystals, graupel particles, and snow particles could be affected by the deposition, riming, and aggregation processes, respectively. Secondly, relative dispersion parameterizations are developed based on a comprehensive consideration of the relationships between the relative dispersion and volume-mean diameter under both polluted and clean conditions. Finally, the relative dispersion parameterizations are applied to terminal velocity parameterizations. The results show that for cloud droplets, ice crystals, graupel particles, and snow particles, assuming the shape parameter in the Gamma distribution is equal to 0 underestimates the shape parameter and overestimates the relative dispersion; and for raindrops, assuming the shape parameter is equal to 0 is close to the relative dispersion parameterizations. The most appropriate constant shape parameters are recommended for different hydrometeors. The relative dispersion parameterizations developed here shed new light for further optimizing the terminal velocity parameterizations in models.摘要离散度的诊断对模式中沉降过程的准确描述至关重要. 本文利用WRF模式结合谱分档方案模拟安徽寿县地区的对流云, 研究不同水成物的离散度. 首先, 无论在清洁还是污染条件下, 除冰晶谱的离散度与体积平均直径间呈现负相关关系外, 云滴, 雨滴, 霰粒子与雪粒子谱离散度与体积平均直径呈现正相关关系; 云滴和雨滴受碰并过程影响, 冰晶, 霰粒子和雪粒子分别受凝华过程, 淞附过程和聚并增长影响. 其次, 综合考虑污染与清洁条件下离散度和体积平均直径之间的相关关系, 建立了离散度的参数化方案. 最后, 把该离散度方案应用到下落末速度的参数化方案中, 结果表明, 对于云滴, 冰晶, 霰粒子和雪粒子, 在Gamma分布中假设谱形参数等于0会低估谱形参数而高估离散度. 对于雨滴而言, 假设谱形参数等于0与参数化方案结果接近. 针对不同的水成物, 给出了最合适的谱形参数定值. 本文发展的离散度方案为进一步优化模式中下落末速度参数化方案提供参考.

Laboratory studies of the graupel nuclei formation and the processes of their further growth in a liquid droplet medium

The article presents a set of equipment for studying the growth of graupel nuclei and the growth of graupel particles. It was established in the work that the growth parameters as mass, the rate of mass growth have extreme values from –5 °C to –12 °C. It was found that at the initial stage of hail formation, two growth modes are observed: first, the growth of ice particles occurs due to the diffusion of water vapor; second, the growth of ice particles occurs as a result of crystal aggregation. The calculated values of the density of ice formed during the diffusion of water vapor vary from 0.9 to 0.97 g/cm3, in the second case from 0.2 to 0.6 g/cm3. A significant increase in the growth rate of hail occurs during the translational-rotational movement of the air flow in the wind tunnel. The article shows that with an increase in water content, the growth rate of hailstones increases. When the water content reaches approximately one gram per cubic meter there is a sharp decrease in the growth rate. With a further increase in the water content, the growth rate increases. The sharp decrease in the growth rate is most likely due to the fact that at a water level of about one gram per cubic meter, the nuclei are saturated with moisture and the ice density increases, and this leads to a decrease in the rate of hail growth.