Aggregation Of Ice Crystals Research Articles

Precipitation Characteristics at Different Developmental Stages of the Tibetan Plateau Vortex in July 2021 Based on GPM-DPR Data

The Tibetan Plateau vortex (TPV), as an α-scale mesoscale weather system, often brings severe weather conditions like torrential rain and severe convective storms. Based on the detections from the Global Precipitation Measurement (GPM) Core Observatory’s Dual-frequency Precipitation Radar (DPR) and the FY-4A satellite’s Advanced Geostationary Radiation Imager (AGRI), combined with ERA5 reanalysis data, the precipitation characteristics of a TPV moving eastward during 8–13 July 2021 at different developmental stages are explored in this study. It was clear that the near-surface precipitation rate of the TPV during the initial stage at the eastern Tibetan Plateau (TP) was below 1 mm·h−1, implying overall weak precipitation dominated by stratiform clouds. After moving out of the TP, the radar reflectivity factor (Ze), precipitation rate, and normalized intercept parameter (dBNw) significantly increased, while the proportion of convective clouds gradually rose. Following the TPV movement, the distribution range and vertical thickness of Ze, mass-weighted mean diameter (Dm), and dBNw tended to increase. The high-frequency region of Ze appeared at 15–20 dBZ, while Dm and dBNw occurred at around 1 mm and 33 mm−1·m−3, respectively. Near the melting layer, Ze was characterized by a significant increase due to the aggregation and melting of ice crystals. The precipitation rate of convective clouds was generally greater than that of stratiform clouds, whilst both of them increased during the movement of the TPV. Particularly, at 01:00 on 12 July, there was a significant increase in the precipitation rate and Dm of convective clouds, while dBNw noticeably decreased. These findings could provide valuable insights into the three-dimensional structure and microphysical characteristics of the precipitation during the movement of the TPV, contributing to a better understanding of cloud precipitation mechanisms.

Study of Microphysical Signatures Based on Spectral Polarimetry during the RELAMPAGO Field Experiment in Argentina

Abstract Weather radars with dual-polarization capabilities enable the study of various characteristics of hydrometeors, including their size, shape, and orientation. Radar polarimetric measurements, coupled with Doppler information, allow for analysis in the spectral domain. This analysis can be leveraged to reveal valuable insight into the microphysics and kinematics of hydrometeors in precipitation systems. This paper uses spectral polarimetry to investigate precipitation microphysics and kinematics in storm environments observed during the Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) field experiment in Argentina. This study uses range–height indicator scan measurements from a C-band polarimetric Doppler weather radar deployed during the field campaign. In this work, the impact of storm dynamics on hydrometeors is studied, including the size sorting of hydrometeors due to vertical wind shear. In addition, particle microphysical processes because of aggregation and growth of ice crystals in anvil clouds, as well as graupel formation resulting from the riming of ice crystals and dendrites, are also analyzed here. The presence of different particle size distributions because of the mixing of hydrometeors in a sheared environment and resulting size sorting has been reported using spectral differential reflectivity (sZdr) slope. Spectral reflectivity sZh and sZdr have also been used to understand the signature of ice crystal aggregation in an anvil cloud. The regions of pristine ice crystals are identified from vertical profiles of spectral polarimetric variables in anvil cloud because of sZh < 0 dB and sZdr values around 2 dB. It is also found that the growth process of these ice crystals causes a skewed bimodal sZh spectrum due to the presence of both pristine ice crystals and dry snow. Next, graupel formation due to riming has been studied, and it is found that the riming process produces sZh values of about 10 dB and corresponding sZdr values of 1 dB. This positive sZdr indicates the presence of needle/columnar secondary ice particles formed by ice multiplication processes in the riming zones. Last, the temporal evolution of a storm is investigated by analyzing changes in hydrometeor types with time and their influence on the spectral polarimetric variables.

Fragmentation of ice particles: laboratory experiments on graupel–graupel and graupel–snowflake collisions

Abstract. Until now, the processes involved in secondary ice production which generate high concentrations of ice crystals in clouds have been poorly understood. However, collisions that involve rimed ice particles or crystal aggregates have the potential to effectively produce secondary ice from their fragmentation. Unfortunately, there have only been a few laboratory studies on ice–ice collision so far, resulting in an inaccurate representation of this process in microphysical schemes. To address this issue, experiments were conducted at the wind tunnel laboratory of the Johannes Gutenberg University, Mainz, on graupel–graupel and graupel–snowflake collisions under still-air conditions at −15 ∘C and water supersaturation. The particles were synthetically generated within a cold room through two distinct methods: by riming and vapor deposition for graupel with diameters of 2 and 4 mm and by manually sticking vapor-grown ice which was generated above a warm bath to form snowflakes with a diameter of 10 mm. All fragments resulting from graupel–graupel collisions were collected and investigated by means of a digital optical microscope, while fragments from graupel–snowflake collisions were observed and recorded instantly after collision using a holographic instrument. From these experiments, distributions were obtained for fragment sizes, cross-sectional areas, and aspect ratios. The results showed a higher number of fragments at lower kinetic energy compared to those presented in the literature. A total of 150 to 600 fragments were observed for graupel–graupel with dendrites collisions, as well as 70 to 500 fragments for graupel–snowflake collisions for collision kinetic energies between 10−7 and 10−5 J. Parameterizations for fragment size distributions are provided with a mode at 75 µm for graupel–graupel with dendrites collisions and at 400 µm for graupel–snowflake collisions. We also propose new coefficients fitted on our experiments to parameterize the number of fragments generated by collisions based on the theoretical formulation of Phillips et al. (2017). These results can be used to improve the representation of ice collision breakup in microphysical schemes.

Light-Scattering Properties for Aggregates of Atmospheric Ice Crystals within the Physical Optics Approximation

This paper presents the light-scattering matrices of atmospheric-aggregated hexagonal ice particles that appear in cirrus clouds. The aggregates consist of the same particles with different spatial orientations and numbers of these particles. Two types of particle shapes were studied: (1) hexagonal columns; (2) hexagonal plates. For both shapes, we studied compact and non-compact cases of particle arrangement in aggregates. As a result, four sets of aggregates were made: (1) compact columns; (2) non-compact columns; (3) compact plates; and (4) non-compact plates. Each set consists of eight aggregates with a different number of particles from two to nine. For practical reasons, the bullet-rosette and the aggregate of hexagonal columns with different sizes were also calculated. The light scattering matrices were calculated for the case of arbitrary spatial orientation within the geometrical optics approximation for sets of compact and non-compact aggregates and within the physical optics approximation for two additional aggregates. It was found that the light-scattering matrix elements for aggregates depend on the arrangement of particles they consist of.

Effect of active ice nucleation bacteria on freezing and the properties of surimi during frozen storage

The effects of active ice nucleation bacteria (INB, Pseudomonas syringae) on freezing, ice crystal formation, and aggregation, and oxidation of surimi from Talang queenfish (Scomberoides commersonnianus) during frozen storage were investigated. The shortest freezing time (225 min) and the highest onset temperature (−7.0 °C), as determined by differential scanning calorimetry (DSC), was found for surimi with 106 colony-forming units of INB mL−1 100−1 g (INB c1). The surimi showed better structure with the lowest inter-fiber space along with finer and more homogenous myofibrillar proteins (MP) surface morphology and a lower root-mean-square (Rq, 142 nm) from atomic force microscopy (AFM) after 90 days of storage at −18 °C, which was associated with the highest ζ-potential (−9.0 mV) than the control (−6.2 mV) which reflected a lowered MP aggregation behavior. Compared to the control, protein carbonyls in surimi with INB c1 decreased significantly, while showing a lower decrease in total sulfhydryl groups (P < 0.05). Overall, INB c1shortened the freezing time and increased freezing rate, while decreasing oxidation and aggregation of surimi proteins.

Colliding Ice Crystals in Turbulent Clouds

Abstract Collisions, resulting in aggregation of ice crystals in clouds, is an important step in the formation of snow aggregates. Here, we study the collision process by simulating spheroid-shaped particles settling in turbulent flows and by determining the probability of collision. We focus on platelike ice crystals (oblate ellipsoids), subject to gravity, and to the Stokes force and torque generated by the surrounding fluid. We also take into account the contributions to the drag and torque due to fluid inertia, which are essential to understand the tendency of crystals to settle with their largest dimension oriented horizontally. We determine the collision rate between identical crystals, of diameter 300 μm, with aspect ratios in the range 0.005 ≤ β ≤ 0.05, and over a range of energy dissipation per unit mass, ε, 1 ≤ ε ≤ 250 cm2 s−3. For all values of β studied, the collision rate increases with the turbulence intensity. The dependence on β is more subtle. Increasing β at low turbulence intensity () diminishes the collision rate, but increases it at higher ε ≈ 250 cm2 s−3. The observed behaviors can be understood as resulting from three main physical effects. First, the velocity gradients in a turbulent flow tend to bring particles together. In addition, differential settling plays a role at small ε when the particles are thin enough (β small), whereas the prevalence of particle inertia at higher ε leads to a strong enhancement of the collision rate.

The Effects of Ice Habit on Simulated Orographic Snowfall

AbstractMany factors are at play in determining the amount and distribution of mountain snowfall that is predicted by weather models; among them is the influence of assumed ice habit on snowfall distribution. Ice habit is necessarily greatly simplified in microphysics schemes and uncertainty remains in how best to model ice processes. In this study we simulate a Sierra Nevada snowfall event driven by an extratropical cyclone in February 2014. We have simulated the storm with four fixed habit types as well as with an ice habit scheme that is variable in time and space. In contrast to some previous studies, we found substantially smaller sensitivity of total accumulated precipitation amount and negligible changes in spatial distribution to the ice habit specification. The reason for smaller sensitivity seems to be linked to strong aggregation of ice crystals in the model. Nonetheless, while changes in total accumulated precipitation were small, changes in accumulated ice hydrometeors were larger. The variable-habit simulation produced up to 37% more ice precipitation than any of the fixed-habit simulations with an average increase of 14%. The variable-habit simulation led to a maximization of ice growth in the atmosphere and, subsequently, ice accumulation at the surface. This result points to the potential importance of accounting for the time and space variation of ice crystal properties in simulations of orographic precipitation.

Anti-freeze effect of Enoki mushroom extract on the quality preservation of frozen whipped cream

The alkaline extract of Enoki mushroom (Flammulina velutipes) has been shown to have ice crystal growth inhibiting activity, and its beneficial effect on the quality preservation of frozen foods is highly expected. The purpose of this study was to investigate the effect of Enoki mushroom extract which has an ice recrystallization inhibiting activity on the quality of frozen whipped creams. Whipping creams with different milk/vegetable fat compositions were prepared. The proportion of % milk fat and % vegetable fat was given as follows; 0:37, 10:28, 20:20 and 40:0, respectively. Whipped foam samples were frozen and stored at −20 °C, then the effect of adding 0.1% Enoki mushroom extract was tested. Fresh dairy flavor and smooth melt in mouth texture was deteriorated during the course of frozen storage for 37 days, and the frequency is higher in whipped creams with high milk fat content. Addition of 0.1% Enoki mushroom extract ameliorated these quality changes and significantly retained moisture content. Microscopic observation of the internal structure of frozen foam samples by cryo-SEM revealed that the ice crystal aggregates grown in the emulsified solid phase were reduced by adding Enoki mushroom extract. GC/MS analysis of the flavor components revealed that the content of furan compounds (furfural and 2-furanmethanol) was increased by 1.7 times in control foam samples during frozen storage, whereas the furan compounds in whipped foam sample containing Enoki mushroom extract did not increase after frozen storage. Based on these findings, it is proposed that ice crystal growth at the emulsified solid phase causes the sublimation of water on the surface of frozen whipped cream and destruction of the network structure of fat globules results in the quality changes after thawing. Enoki mushroom extract was found to retard ice crystal growth in whipped cream, thus supposed to reduce the quality changes during frozen storage.

Improving the Southern Ocean cloud albedo biases in a general circulation model

Abstract. The present generation of global climate models is characterised by insufficient reflection of short-wave radiation over the Southern Ocean due to a misrepresentation of clouds. This is a significant concern as it leads to excessive heating of the ocean surface, sea surface temperature biases and subsequent problems with atmospheric dynamics. In this study, we modify cloud microphysics in a recent version of the Met Office's Unified Model and show that choosing a more realistic value for the shape parameter of atmospheric ice crystals, in better agreement with theory and observations, benefits the simulation of short-wave radiation. In the model, for calculating the growth rate of ice crystals through deposition, the default assumption is that all ice particles are spherical in shape. We modify this assumption to effectively allow for oblique shapes or aggregates of ice crystals. Along with modified ice nucleation temperatures, we achieve a reduction in the annual-mean short-wave cloud radiative effect over the Southern Ocean by up to ∼4 W m−2 and seasonally much larger reductions compared to the control model. By slowing the growth of the ice phase, the model simulates substantially more supercooled liquid cloud.

The Ice Particle and Aggregate Simulator (IPAS). Part I: Extracting Dimensional Properties of Ice–Ice Aggregates for Microphysical Parameterization

AbstractAggregation, the process by which two or more ice particles attach to each other, is typically observed in clouds that span a range of temperatures and is influenced by the crystal shape (habit). In this study, the resulting characteristics of ice–ice two-monomer aggregation is investigated, which is expected to improve microphysical parameterizations through more precise aggregate characteristics and in turn better predict the rate of aggregation and snow development. A systematic way to determine the aspect ratio of the aggregate was developed, which takes into account the expected falling orientations, overlap of each monomer, and any contact angle that may form through so-called constrained randomization. Distributions were used to obtain the most frequent aspect ratio, major axis, and minor axis of aggregated particles with respect to the monomer aspect ratio. Simulations were completed using the Ice Particle and Aggregate Simulator (IPAS), a model that uses predefined three-dimensional geometries, (e.g., hexagonal prisms) to simulate ice crystal aggregation and allows for variation in crystal size, shape, number, and falling orientation. In this study, after collection in a theoretical grid space, detailed information is extracted from the particles to determine the properties of aggregates. It was found that almost all monomer aspect ratios aggregate to less extreme aggregate aspect ratios at nearly the same rate. Newly formed aggregate properties are amenable to implementation into more sophisticated bulk microphysical models designed to predict and evolve particle properties, which is crucial in realistically evolving cloud ice mass distribution and for representing the collection process.

The Geometry of Rimed Aggregate Snowflakes: A Modeling Study

AbstractComputer simulations of the aggregation and riming of ice crystals are performed to investigate the geometry of rimed aggregate snowflakes. Due to the universality of the geometry of aggregates, the conversion to a graupel‐like particle is self‐similar and independent from specific properties of the aggregate, when formulated in properly normalized variables. Hence, the particle habit of the primary crystals, the size of the aggregate or the density of the rime mass, does not lead to a structural change in the transition to graupel. Therefore, this transition can be parameterized by a similarity approach using simulations of many individual rimed aggregates. These parameterizations can replace the classic fill‐in model used in many cloud models. The parameterizations are applied and tested in a one‐dimensional Lagrangian superparticle model to simulate the growth of aggregates in a liquid layer. We find that the similarity model for the geometry of rimed snowflakes leads to a more rapid growth by riming and, hence, an increased precipitation rate compared to the fill‐in model. The main reason for this is that the increase of the maximum dimension during the early stages of riming is properly taken into account by the similarity model, whereas it is neglected by the fill‐in model.

The Life Cycles of Ice Crystals Detrained From the Tops of Deep Convection

AbstractExtensive anvil cirrus clouds generated by deep convection have important impacts on the Earth's radiation budget and climate. We use growth‐sedimentation trajectory calculations to investigate the life cycles of anvil ice crystals as they are advected downwind from their convective source. Temperature, water vapor, and wind fields from a cloud‐resolving model simulation of an isolated cumulonimbus cloud are used to drive the calculations. Ice crystals are initialized in the main upper‐level detrainment zone with a size distribution based on in situ measurements made in a convective core at about 12 km. Advection, deposition growth, and sedimentation of thousands of sample ice crystals are tracked over about 2.5 hr; neither aggregation of ice crystals nor radiative effects are included. Results support the importance of deposition growth and gravitational size sorting in the evolution of the anvil cirrus. Most ice crystals initialized with maximum dimensions larger than about 200 μm fall out of the anvil and sublimate in subsaturated air below within about 2 hr. Few small ice crystals are present in the lower part of the mature anvil. Vapor deposition growth accounts for about 50% of the ice mass remaining after about 2 hr. Ice crystals larger than about 50 μm in the mature anvil have grown substantially by deposition of vapor. This result is consistent with the predominance of bullet rosette habits observed in mature anvils. Variations in ice crystal fall speeds and growth rates associated with ice crystal habit assumptions have little impact on the ice crystal life cycles.

Cirrus Cloud Properties as Seen by the CALIPSO Satellite and ECHAM-HAM Global Climate Model

Cirrus clouds impact the planetary energy balance and upper-tropospheric water vapor transport and are therefore relevant for climate. In this study cirrus clouds at temperatures colder than −40°C simulated by the ECHAM–Hamburg Aerosol Module (ECHAM-HAM) general circulation model are compared to Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO) satellite data. The model captures the general cloud cover pattern and reproduces the observed median ice water content within a factor of 2, while extinction is overestimated by about a factor of 3 as revealed by temperature-dependent frequency histograms. Two distinct types of cirrus clouds are found: in situ–formed cirrus dominating at temperatures colder than −55°C and liquid-origin cirrus dominating at temperatures warmer than −55°C. The latter cirrus form in anvils of deep convective clouds or by glaciation of mixed-phase clouds, leading to high ice crystal number concentrations. They are associated with extinction coefficients and ice water content of up to 1 km−1 and 0.1 g m−3, respectively, while the in situ–formed cirrus are associated with smaller extinction coefficients and ice water content. In situ–formed cirrus are nucleated either heterogeneously or homogeneously. The simulated homogeneous ice crystals are similar to liquid-origin cirrus, which are associated with high ice crystal number concentrations. On the contrary, heterogeneously nucleated ice crystals appear in smaller number concentrations. However, ice crystal aggregation and depositional growth smooth the differences between several formation mechanisms, making the attribution to a specific ice nucleation mechanism challenging.

Ice cream structure modification by ice-binding proteins

Ice-binding proteins (IBPs), also known as antifreeze proteins, were added to ice cream to investigate their effect on structure and texture. Ice recrystallization inhibition was assessed in the ice cream mixes using a novel accelerated microscope assay and the ice cream microstructure was studied using an ice crystal dispersion method. It was found that adding recombinantly produced fish type III IBPs at a concentration 3 mg·L−1 made ice cream hard and crystalline with improved shape preservation during melting. Ice creams made with IBPs (both from winter rye, and type III IBP) had aggregates of ice crystals that entrapped pockets of the ice cream mixture in a rigid network. Larger individual ice crystals and no entrapment in control ice creams was observed. Based on these results a model of ice crystals aggregates formation in the presence of IBPs was proposed.

Collection/aggregation algorithms in Lagrangian cloud microphysical models: rigorous evaluation in box model simulations

Abstract. Recently, several Lagrangian microphysical models have been developed which use a large number of (computational) particles to represent a cloud. In particular, the collision process leading to coalescence of cloud droplets or aggregation of ice crystals is implemented differently in various models. Three existing implementations are reviewed and extended, and their performance is evaluated by a comparison with well-established analytical and bin model solutions. In this first step of rigorous evaluation, box model simulations, with collection/aggregation being the only process considered, have been performed for the three well-known kernels of Golovin, Long and Hall. Besides numerical parameters, like the time step and the number of simulation particles (SIPs) used, the details of how the initial SIP ensemble is created from a prescribed analytically defined size distribution is crucial for the performance of the algorithms. Using a constant weight technique, as done in previous studies, greatly underestimates the quality of the algorithms. Using better initialisation techniques considerably reduces the number of required SIPs to obtain realistic results. From the box model results, recommendations for the collection/aggregation implementation in higher dimensional model setups are derived. Suitable algorithms are equally relevant to treating the warm rain process and aggregation in cirrus.

Microphysical Properties of Ice Crystal Precipitation and Surface-Generated Ice Crystals in a High Alpine Environment in Switzerland

AbstractDuring the Cloud and Aerosol Characterization Experiment (CLACE) 2013 field campaign at the High Altitude Research Station Jungfraujoch, Switzerland, optically thin pure ice clouds and ice crystal precipitation were measured using holographic and other in situ particle instruments. For cloud particles, particle images, positions in space, concentrations, and size distributions were obtained, allowing one to extract size distributions classified by ice crystal habit. Small ice crystals occurring under conditions with a vertically thin cloud layer above and a stratocumulus layer approximately 1 km below exhibit similar properties in size and crystal habits as Antarctic/Arctic diamond dust. Also, ice crystal precipitation stemming from midlevel clouds subsequent to the diamond dust event was observed with a larger fraction of ice crystal aggregates when compared with the diamond dust. In another event, particle size distributions could be derived from mostly irregular ice crystals and aggregates, which likely originated from surface processes. These particles show a high spatial and temporal variability, and it is noted that size and habit distributions have only a weak dependence on the particle number concentration. Larger ice crystal aggregates and rosette shapes of some hundred microns in maximum dimension could be sampled as a precipitating cirrostratus cloud passed the site. The individual size distributions for each habit agree well with lognormal distributions. Fitted parameters to the size distributions are presented along with the area-derived ice water content, and the size distributions are compared with other measurements of pure ice clouds made in the Arctic and Antarctic.

Polarimetric radar and in situ observations of riming and snowfall microphysics during CLACE 2014

Abstract. This study investigates the microphysics of winter alpine snowfall occurring in mixed-phase clouds in an inner-Alpine valley during January and February 2014. The available observations include high-resolution polarimetric radar and in situ measurements of the ice-phase and liquid-phase components of clouds and precipitation. Radar-based hydrometeor classification suggests that riming is an important factor to favor an efficient growth of the precipitating mass and correlates with snow accumulation rates at ground level. The time steps during which rimed precipitation is dominant are analyzed in terms of temporal evolution and vertical structure. Snowfall identified as rimed often appears after a short time period during which the atmospheric conditions favor wind gusts and updrafts and supercooled liquid water (SLW) is available. When a turbulent atmospheric layer persists for several hours and ensures continuous SLW generation, riming can be sustained longer and large accumulations of snow at ground level can be generated. The microphysical interpretation and the meteorological situation associated with one such event are detailed in the paper. The vertical structure of polarimetric radar observations during intense snowfall classified as rimed shows a peculiar maximum of specific differential phase shift Kdp, associated with large number concentrations and riming of anisotropic crystals. Below this Kdp peak there is usually an enhancement in radar reflectivity ZH, proportional to the Kdp enhancement and interpreted as aggregation of ice crystals. These signatures seem to be recurring during intense snowfall.

A Parameterization of Sticking Efficiency for Collisions of Snow and Graupel with Ice Crystals: Theory and Comparison with Observations*

Abstract A new parameterization of sticking efficiency for aggregation of ice crystals onto snow and graupel is presented. This parameter plays a crucial role for the formation of ice precipitation and for electrification processes. The parameterization is intended to be used in atmospheric models simulating the aggregation of ice particles in glaciated clouds. It should improve the ability to forecast snow. Based on experimental results and general considerations of collision processes, dependencies of the sticking efficiency on temperature, surface area, and collision kinetic energy of impacting particles are derived. The parameters have been estimated from some laboratory observations by simulating the experiments and minimizing the squares of the errors of the prediction of observed quantities. The predictions from the new scheme are compared with other available laboratory and field observations. The comparisons show that the parameterization is able to reproduce the thermal behavior of sticking efficiency, observed in published laboratory studies, with a peak around −15°C corresponding to dendritic vapor growth of ice. Finally, a new theory of sticking efficiency is proposed. It explains the empirically derived parameterization in terms of a probability distribution of the work that would be required to separate two contacting particles colliding in all possible ways among many otherwise identical collisions of the same pair with a given initial collision kinetic energy. For each collision, if this work done would exceed the initial collision kinetic energy, then there is no separation after impact. The probability of that occurring equals the sticking efficiency.

Measurements of Differential Reflectivity in Snowstorms and Warm Season Stratiform Systems

AbstractThe organized behavior of differential radar reflectivity (ZDR) is documented in the cold regions of a wide variety of stratiform precipitation types occurring in both winter and summer. The radar targets and attendant cloud microphysical conditions are interpreted within the context of measurements of ice crystal types in laboratory diffusion chambers in which humidity and temperature are both stringently controlled. The overriding operational interest here is in the identification of regions prone to icing hazards with long horizontal paths. Two predominant regimes are identified: category A, which is typified by moderate reflectivity (from 10 to 30 dBZ) and modest +ZDR values (from 0 to +3 dB) in which both supercooled water and dendritic ice crystals (and oriented aggregates of ice crystals) are present at a mean temperature of −13°C, and category B, which is typified by small reflectivity (from −10 to +10 dBZ) and the largest +ZDR values (from +3 to +7 dB), in which supercooled water is dilute or absent and both flat-plate and dendritic crystals are likely. The predominant positive values for ZDR in many case studies suggest that the role of an electric field on ice particle orientation is small in comparison with gravity. The absence of robust +ZDR signatures in the trailing stratiform regions of vigorous summer squall lines may be due both to the infusion of noncrystalline ice particles (i.e., graupel and rimed aggregates) from the leading deep convection and to the effects of the stronger electric fields expected in these situations. These polarimetric measurements and their interpretations underscore the need for the accurate calibration of ZDR.

The Role of Cloud Microphysics Parameterization in the Simulation of Mesoscale Convective System Clouds and Precipitation in the Tropical Western Pacific

Abstract This paper presents a detailed analysis of convection-permitting cloud simulations, aimed at increasing the understanding of the role of parameterized cloud microphysics in the simulation of mesoscale convective systems (MCSs) in the tropical western Pacific (TWP). Simulations with three commonly used bulk microphysics parameterizations with varying complexity have been compared against satellite-retrieved cloud properties. An MCS identification and tracking algorithm was applied to the observations and the simulations to evaluate the number, spatial extent, and microphysical properties of individual cloud systems. Different from many previous studies, these individual cloud systems could be tracked over larger distances because of the large TWP domain studied. The analysis demonstrates that the simulation of MCSs is very sensitive to the parameterization of microphysical processes. The most crucial element was found to be the fall velocity of frozen condensate. Differences in this fall velocity between the experiments were more related to differences in particle number concentrations than to fall speed parameterization. Microphysics schemes that exhibit slow sedimentation rates for ice aloft experience a larger buildup of condensate in the upper troposphere. This leads to more numerous and/or larger MCSs with larger anvils. Mean surface precipitation was found to be overestimated and insensitive to the microphysical schemes employed in this study. In terms of the investigated properties, the performances of complex two-moment schemes were not superior to the simpler one-moment schemes, since explicit prediction of number concentration does not necessarily improve processes such as ice nucleation, the aggregation of ice crystals into snowflakes, and their sedimentation characteristics.