Density Of Ice Particles Research Articles

Estimating Microphysics Properties in Ice-Dominated Clouds from Airborne Ka–W-band Dual-Wavelength Ratio Reflectivity Factor in Close Proximity to In Situ Probes

Abstract Properties of frozen hydrometeors in clouds remain difficult to sense remotely. Estimates of number concentration, distribution shape, ice particle density, and ice water content are essential for connecting cloud processes to surface precipitation. Progress has been made with dual-frequency radars, but validation has been difficult because of lack of particle imaging and sizing observations collocated with the radar measurements. Here, data are used from two airborne profiling (up and down) radars, the W-band Wyoming Cloud Radar and the Ka-band Profiling Radar, allowing for Ka–W-band dual-wavelength ratio (DWR) profiles. The aircraft (the University of Wyoming King Air) also carried a suite of in situ cloud and precipitation probes. This arrangement is optimal for relating the “flight-level” DWR (an average from radar gates below and above flight level) to ice particle size distributions measured by in situ optical array probes, as well as bulk properties such as minimum snow particle density and ice water content. This comparison reveals a strong relationship between DWR and the ice particle median-volume diameter. An optimal range of DWR values ensures the highest retrieval confidence, bounded by the radars’ relative calibration and DWR saturation, found here to be about 2.5–7.5 dB. The DWR-defined size distribution shape is used with a Mie scattering model and an experimental mass–diameter relationship to test retrievals of ice particle concentration and ice water content. Comparison with flight-level cloud-probe data indicate good performance, allowing microphysical interpretations for the rest of the vertical radar transects.

Investigation of Microphysical Properties within Regions of Enhanced Dual-Frequency Ratio during the IMPACTS Field Campaign

Abstract Multifrequency airborne radars have become instrumental in evaluating the performance of satellite retrievals and furthering our understanding of ice microphysical properties. The dual-frequency ratio (DFR) is influenced by the size, density, and shape of ice particles, with higher values associated with the presence of larger ice particles that may have implications regarding snowfall at the surface. The Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign involves the coordination of remote sensing measurements above winter midlatitude cyclones from an ER-2 aircraft to document the fine-scale precipitation structure spanning four radar (X-, Ku-, Ka-, and W-band) frequencies and in situ microphysical measurements from a P-3 aircraft that provide additional insight into the particle size distribution (PSD) behavior and habits of the hydrometeors related to the DFR. A novel approach to identify regions of prominently higher Ku- and Ka-band DFR at the P-3 location for five coordinated flights is presented. The solid-phase mass-weighted mean diameter (Dm) was 58% larger, the effective density (ρe) 37% smaller, and the liquid-equivalent normalized intercept parameter (Nw) 74% lower in regions of prominently higher DFR. Microphysical properties within a triple-frequency framework suggest signatures consistent with aggregation and riming as in previous studies. Last, a pretrained neural network radar retrieval is used to investigate the vertical structure of microphysical properties associated with the larger DFR signatures and provides the spatial context for inferring certain microphysical processes. Significance Statement The purpose of this study is to better understand what radar measurements from multiple frequencies can tell us about the sizes, shapes, and concentrations of ice particles within winter snowstorms, and how these observations are related to banded precipitation structures since they can have implications for snowfall at the surface. Our results show that ice particles are on average larger and less dense when the reflectivity difference between two radars operating at different wavelengths is larger and supports the process by which crystals aggregate to form larger particles. These findings aim to improve how satellites and forecasting models represent precipitation in the cloud and at the surface.

Vertical Structure of Ice Clouds and Vertical Air Motion from Vertically Pointing Cloud Radar Measurements

The vertical structure of ice clouds and vertical air motion (Vair) were investigated using vertically pointing Ka-band cloud radar. The distributions of reflectivity (Z), Doppler velocity (VD), and spectrum width (SW) were analyzed for three ice cloud types, namely, cirrus, anvil, and stratiform clouds. The radar parameters of the cirrus clouds showed narrower distributions than those of the stratiform and anvil clouds. In the vertical structures, the rapid growth of Z and VD occurred in the layer between 8 and 12 km (roughly a layer of −40 °C to −20 °C) for all ice clouds. The prominent feature in the stratiform clouds was an elongated “S” shape in the VD near 7–7.5 km (at approximately −16 °C to −13 °C) due to a significant decrease in an absolute value of VD. The mean terminal fall velocity (Vt) and Vair in the ice clouds were estimated using pre-determined Vt–Z relationships (Vt = aZb) and the observed VD. Although the cirrus clouds demonstrated wide distributions in coefficients a and exponents b depending on cloud heights, they showed a smaller change in Z and Vt values compared to that of the other cloud types. The anvil clouds had a larger exponent than that of the stratiform clouds, indicating that the ice particle density of anvil clouds increases at a faster rate compared with the density of stratiform clouds for the same Z increment. The significant positive Vair appeared at the top of all ice clouds in range up to 0.5 m s−1, and the anvil clouds showed the deepest layer of upward motion. The stratiform and anvil clouds showed a dramatic increase in vertical air motion in the layer of 6–8 km as shown by the rapid decrease of VD. This likely caused increase of supersaturation above. A periodic positive Vair linked with a significant reduction in VD appeared at the height of 7–8 km (approximately −15 °C) dominantly in the stratiform clouds. This layer exhibited a bi-modal power spectrum produced by pre-existing larger ice particles and newly formed numerous smaller ice particles. This result raised a question on the origins of smaller ice particles such as new nucleation due to increased supersaturation by upward motion below or the seeder-feeder effect. In addition, the retrieved Vair with high-resolution data well represented a Kelvin-Helmholtz wave development.

Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model

Abstract The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. The combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

Establishment and Preliminary Application of the Forward Modeling Method for Doppler Spectral Density of Ice Particles

Owing to the various shapes of ice particles, the relationships between fall velocity, backscattering cross-section, mass, and particle size are complicated. This affects the application of cloud radar Doppler spectral density data in the retrieval of the microphysical properties of ice crystals. In this study, under the assumption of six particle shape types, the relationships between particle mass, fall velocity, backscattering cross-section, and particle size were established based on existing research. Variations of Doppler spectral density with the same particle size distribution (PSD) of different ice particle types are discussed. The radar-retrieved liquid and ice PSDs, water content, and mean volume-weighted particle diameter were compared with airborne in situ observations in the Xingtai, Hebei Province, China, in 2018. The results showed the following. (1) For the particles with the same equivalent diameter (De), the fall velocity of the aggregates was the largest, followed by hexagonal columns, hexagonal plates, sector plates, and stellar crystals, with the ice spheres falling two to three times faster than ice crystals with the same De. Hexagonal columns had the largest backscattering cross-section, followed by stellar crystals and sector plates, and the backscattering cross-sections of hexagonal plates and the two types of aggregates were very close to those of ice spheres. (2) The width of the simulated radar Doppler spectral density generated by various ice crystal types with the same PSD was mainly affected by the particle’s falling velocity, which increased with the particle size. Turbulence had different degrees of influence on the Doppler spectrum of different ice crystals, and it also brought large errors to the PSD retrieval. (3) PSD comparisons showed that each ice crystal type retrieved from the cloud radar corresponded well to aircraft observations within a certain scale range, when assuming that only a certain type of ice crystals existed in the cloud, which could fully prove the feasibility of retrieving ice PSDs from the reflectivity spectral density.

Research on small-scale structures of ice particle density and electron density in the mesopause region

Abstract. The formation of ice particle density irregularities with a meter scale in the mesopause region is explored in this paper by developing a growth and motion model of ice particles based on the motion equation of a variable mass object. The growth of particles by water vapor adsorption and the action of gravity and the neutral drag force on particles are considered in the model. The evolution of the radius, velocity, and number density of ice particles is then investigated by solving the growth and motion model numerically. For certain nucleus radii, it is found that the velocity of particles can be reversed at a particular height, leading to a local gathering of particles near the boundary layer, which then forms small-scale ice particle density structures. The spatial scale of the density structures can be affected by vertical wind speed, water vapor density, and altitude, and it remains stable as long as these environmental parameters do not change. The influence of the stable small-scale structures on electron and ion density is further calculated by a charging model, which considers the production, loss, and transport of electrons and ions, along with dynamic particle charging processes. Results show that the electron density is anti-correlated to the charged ice particle density and ion density for particles with radii of 11 nm or less due to plasma attachment by particles and plasma diffusion. This finding is in accordance with most rocket observations. The small-scale electron density structures created by small-scale ice particle density irregularities can produce the polar mesosphere summer echo (PMSE) phenomenon.

A new description of probability density distributions of polar mesospheric clouds

Abstract. In this paper we present a new description of statistical probability density functions (pdfs) of polar mesospheric clouds (PMCs). The analysis is based on observations of maximum backscatter, ice mass density, ice particle radius, and number density of ice particles measured by the ALOMAR Rayleigh–Mie–Raman lidar for all PMC seasons from 2002 to 2016. From this data set we derive a new class of pdfs that describe the statistics of PMC events that is different from previous statistical methods using the approach of an exponential distribution commonly named the g distribution. The new analysis describes successfully the probability distributions of ALOMAR lidar data. It turns out that the former g-function description is a special case of our new approach. In general the new statistical function can be applied to many kinds of different PMC parameters, e.g., maximum backscatter, integrated backscatter, ice mass density, ice water content, ice particle radius, ice particle number density, or albedo measured by satellites. As a main advantage the new method allows us to connect different observational PMC distributions of lidar and satellite data, and also to compare with distributions from ice model studies. In particular, the statistical distributions of different ice parameters can be compared with each other on the basis of a common assessment that facilitates, for example, trend analysis of PMC.

Impacts of Ice Particle Shape and Density Evolution on the Distribution of Orographic Precipitation

Abstract An IMPROVE-2 orographic precipitation case is simulated using the Ice-Spheroids Habit Model with Aspect-Ratio Evolution (ISHMAEL) microphysics. In ISHMAEL, the evolution of ice particle properties such as mass, shape, size, density, and fall speed are predicted. These ice particle properties along with the ice size distributions from ISHMAEL and model-derived spatial distribution of accumulated precipitation are compared to observations. ISHMAEL predicts planar and columnar particles at spatial locations that agree with observations. Sensitivity simulations are used to explore the impact of predicting ice particle shape evolution on orographic cloud properties and precipitation compared to the traditional approach of representing snow and graupel using separate categories with conversion from snow to graupel during riming. High biases in both IWCs aloft and surface precipitation accumulation occur in the Umpqua River valley using separate snow and graupel categories because snow that does not convert to graupel is advected over the Coast Range and precipitates out in the valley. Improvements in IWCs aloft and surface precipitation using ISHMAEL occur from both predicting various vapor-grown habits and predicting the impact of partial riming on ice particle properties. Compared to traditional microphysics schemes, ISHMAEL also produces less spatial variability in accumulated precipitation.

Idealized Simulations of a Squall Line from the MC3E Field Campaign Applying Three Bin Microphysics Schemes: Dynamic and Thermodynamic Structure

The squall-line event on 20 May 2011, during the Midlatitude Continental Convective Clouds (MC3E) field campaign has been simulated by three bin (spectral) microphysics schemes coupled into the Weather Research and Forecasting (WRF) Model. Semi-idealized three-dimensional simulations driven by temperature and moisture profiles acquired by a radiosonde released in the preconvection environment at 1200 UTC in Morris, Oklahoma, show that each scheme produced a squall line with features broadly consistent with the observed storm characteristics. However, substantial differences in the details of the simulated dynamic and thermodynamic structure are evident. These differences are attributed to different algorithms and numerical representations of microphysical processes, assumptions of the hydrometeor processes and properties, especially ice particle mass, density, and terminal velocity relationships with size, and the resulting interactions between the microphysics, cold pool, and dynamics. This study shows that different bin microphysics schemes, designed to be conceptually more realistic and thus arguably more accurate than bulk microphysics schemes, still simulate a wide spread of microphysical, thermodynamic, and dynamic characteristics of a squall line, qualitatively similar to the spread of squall-line characteristics using various bulk schemes. Future work may focus on improving the representation of ice particle properties in bin schemes to reduce this uncertainty and using the similar assumptions for all schemes to isolate the impact of physics from numerics.

Simulated Polarimetric Fields of Ice Vapor Growth Using the Adaptive Habit Model. Part I: Large-Eddy Simulations

Abstract The bulk adaptive habit model (AHM) explicitly predicts ice particle aspect ratio, improving the representation of microphysical processes and properties, including ice–liquid-phase partitioning. With the unique ability to predict ice particle shape and density, the AHM is combined with an offline forward operator to produce fields of simulated polarimetric variables. An evaluation of AHM-forward-simulated dual-polarization radar signatures in an idealized Arctic mixed-phase cloud is presented. Interpretations of those signatures are provided through microphysical model output using the large-eddy simulation mode of the Weather Research and Forecasting Model. Vapor-grown ice properties are associated with distinct observable signatures in polarimetric radar variables, with clear sensitivities to the simulated ice particle properties, including ice number, size, and distribution shape. In contrast, the liquid droplet number has little influence on both polarimetric and microphysical variables in the case presented herein. Polarimetric quantities are sensitive to the dominating crystal habit type in a volume, with enhancements for aspect ratios much lower or higher than unity. This synthesis of a microphysical model and a polarimetric forward simulator is a first step in the evaluation of detailed AHM microphysics.

Density modification of ice particles in ice slurry

One of the characteristic properties of ice slurry is the buoyancy of ice particles, which leads to ice separation in unmixed ice slurries and the necessity to agitate storage vessels if ice slurry is to be extracted. Based on this, an investigation into the density modification of ice particles has been undertaken. Additional particles with higher density than ice should act as ice forming nuclei during ice generation, for which suitable particles have been determined and tested. It was possible to show that not all added particles act as ice forming nuclei in the role of a cell nucleus. Furthermore, it can be assumed that various particles agglomerate on the surface of ice particles; hence the density of ice particles increased more than expected due to the incorporation of several particles in each ice particle. These modified ice particles may sediment to the bottom of the container due to the high density of the numerous heavy foreign particles.

Assimilation of Dual-Polarization Radar Observations in Mixed- and Ice-Phase Regions of Convective Storms: Information Content and Forward Model Errors

Abstract Dual-polarization Doppler radar has proven useful for the estimation of hydrometeor content and the classification of hydrometeor type. Recent studies have leveraged dual-polarization-specific information to produce improved assimilated cloud and precipitation fields from the warm rain (above freezing) portion of deep convective storms. While the strengths of dual-polarization radar observations have been conclusively shown for rain and hail hydrometeors, it is less clear how much information is provided in mixed-phase and ice-only regions. In this paper, a Markov chain Monte Carlo (MCMC) algorithm is used to examine the information content of dual-polarization-specific variables in the ice-phase region of a convective storm. Results are used to quantify how much information is added by specific differential phase and radar correlation coefficient, as well as how this information is degraded when the assumed particle size distribution and particle density are allowed to vary. It is found that dual-polarization-specific observations (Kdp and ρhv) provide significant information on rimed ice content, and moderate information on pristine ice, especially where snow mass is more than 10% of the total volume hydrometeor mass. There is a significant reduction in information content for rain and a near-complete loss of information for graupel–hail and snow when the particle size distribution and ice particle densities are not well known, and there are systematic changes in radar information gain and loss with changes in hydrometeor mass. The results highlight the need for a thorough exploration of forward model sensitivities prior to performing radar data assimilation.

A comparison of ice water content measurement techniques on the FAAM BAe-146 aircraft

Abstract. This paper presents a comparison of ice water content (qi) data from a variety of measurement techniques on the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 research aircraft. Data are presented from a range of cloud types measured during the PIKNMIX field experiment that include mixed-phase stratocumulus, cumulus congestus and cirrus clouds. These measurements cover a broad range of conditions in which atmospheric ice particles are found in nature, such as the low-ice-water-content environments typically found in midlatitude cirrus and the environments with much higher ice water content often observed in cold convective clouds. The techniques include bulk measurements from (i) a Nevzorov hot-wire probe, (ii) the difference between the measured total water content (condensed plus vapour) and the water vapour content of the atmosphere and (iii) a counterflow virtual impactor (CVI) (only for cirrus measurements). We also estimate the qi from integration of the measured particle size distribution (PSD) with assumptions on how the density of ice particles varies as a function of size. The results show that the only bulk ice water content technique capable of measuring high qi values (several g m−3) was the method of total water content minus water vapour. For low ice water contents we develop a new parametrisation of the Nevzorov baseline drift that enables the probe to be sensitive to qi ± 0.002 g m−3. In cirrus clouds the agreement between the Nevzorov and other bulk measurements was typically better than a factor of 2 for the CVI (qi > 0.008 g m−3) and the method of total water content minus water vapour (qi > 0.02 g m−3). Good agreement with the bulk measurements for all cases could be obtained with the estimate from the PSD provided that appropriate a priori assumptions on the mass–dimension relationship were made. This is problematic in the convective clouds sampled because pristine ice particles, heavily rimed particles and supercooled liquid drops were all present. In a cirrus case, we show that using a temperature-dependent mass–dimension relation was required to match the bulk measurement of qi.

Polarimetric Radar Characteristics of Melting Hail. Part I: Theoretical Simulations Using Spectral Microphysical Modeling

AbstractSpectral (bin) microphysics models are used to simulate polarimetric radar variables in melting hail. Most computations are performed in a framework of a steady-state, one-dimensional column model. Vertical profiles of radar reflectivity factor Z, differential reflectivity ZDR, specific differential phase KDP, specific attenuation Ah, and specific differential attenuation ADP are modeled at S, C, and X bands for a variety of size distributions of ice particles aloft. The impact of temperature lapse rate, humidity, vertical air velocities, and ice particle density on the vertical profiles of the radar variables is also investigated. Polarimetric radar signatures of melting hail depend on the degree of melting or the height of the radar resolution volume with respect to the freezing level, which determines the relative fractions of partially and completely melted hail (i.e., rain). Simulated vertical profiles of radar variables are very sensitive to radar wavelength and the slope of the size distribution of hail aloft, which is correlated well with maximal hail size. Analysis of relative contributions of different parts of the hail/rain size spectrum to the radar variables allows explanations of a number of experimentally observed features such as large differences in Z of hail at the three radar wavelengths, unusually high values of ZDR at C band, and relative insensitivity of the measurements at C and X bands to the presence of large hail exceeding 2.5 cm in diameter. Modeling results are consistent with S- and C-band polarimetric radar observations and are utilized in Part II for devising practical algorithms for hail detection and determination of hail size as well as attenuation correction and rainfall estimation in the presence of hail.

PMSE observations with the EISCAT VHF- and UHF-radars: Ice particles and their effect on ambient electron densities

It is now well understood that the occurrence of PMSE is closely connected to the presence of ice particles. These ice particles modify the ambient electron density by electron attachment which occasionally leads to large electron density depletions which have also been called ‘biteouts’. There has been some debate in the literature regarding the relative depth of such depletions which is usually expressed by the parameter Λ=|ZA|NA/ne. Here, |ZA|NA is the charge number density of ice particles and ne is the electron density. In this paper, we present, for the first time, the statistical distribution of Λ using measurements with the EISCAT VHF- and UHF-radars. Based on 25h of simultaneous observations, we derived a total of 757Λ values based on 15min of data each. In each of these cases, PMSE were observed with the EISCAT VHF-radar but not with the UHF-radar and the UHF-measurement were hence used to determine the electron density profile. From these 757 cases, there are 699 cases with Λ⪡1, and only 33 cases with Λ>0.5 (21 cases with Λ>1). A correlation analysis of Λ versus PMSE volume reflectivities further reveals that there is no strong dependence between the two parameters. This is in accordance with current PMSE-theory based on turbulence in combination with a large Schmidt-number. The maxima of Λ from each profile show a negative relationship with the undisturbed electron densities deduced at the same altitudes. This reveals that the variability of Λ mainly depends on the variability of the electron densities. In addition, variations of aerosol number densities may also play a role. Although part of the observations were conducted during the HF heating experiments, the so-called overshoot effects did not significantly bias our statistical results. In order to avoid missing biteouts because of a superposition of coherent and incoherent scatter in the UHF-data, we finally calculated spectral parameters n by applying a simple fit to auto-correlation functions as introduced by Strelnikova and Rapp (2010). Corresponding statistical results of the parameter n indicate that charged ice particles do exist in the vicinity of PMSE (i.e., n<1) but they did not efficiently modify ambient electron densities so that clear ‘biteouts’ are observed.

The effective density of small ice particles obtained from in situ aircraft observations of mid‐latitude cirrus

AbstractThe effective ice‐particle density, parametrized through a mass–dimension relation, is widely used in ice microphysical schemes for weather and climate models. In this study, we use aircraft‐based observations in mid‐latitude cirrus taken during the Constrain field programme in 2010. The low temperatures and a humidity often close to ice saturation meant that the typical ice particles observed were small (maximum dimension 20–800 µm) and ice water contents were low (0.001–0.05 g m−3). Two new instruments are included in this study: the Small Ice Detector Mark‐2 (SID‐2) and the deep‐cone Nevzorov Total Water Content probe. SID‐2 is a new single‐particle light‐scattering instrument and was used to identify and size small ice particles (10–150 µm). The deep‐cone Nevzorov probe is shown to be able to collect small ice masses with sufficient sensitivity. The focus of this article is on the effective density of small ice particles (both pristine ice crystals and small aggregates up to 600 µm maximum dimension). Due to instrument limitations in previous studies, the effective density of small ice particles is questionable.Aircraft flights in six cirrus cases provided ice‐particle measurements throughout the depth of the cirrus. The particle size distribution (PSD) was mostly bimodal. The smaller ice‐crystal mode dominated the PSD near cloud top and the larger ice‐aggregate mode dominated near cloud base. A mass–dimension relation valid for both ice crystals and aggregates was found that provided a best fit to the observations. For small ice particles (less than 70 µm diameter) the density is constant (700 kg m−3), while for larger ice crystals or aggregates the mass–dimension relation is m(D) = 0.0257D2.0. These measurements allow testing of the diagnostic split between ice crystals and aggregates used in the Met Office Unified Model.

A Warm-Bin–Cold-Bulk Hybrid Cloud Microphysical Model*

AbstractThis study describes a newly developed bin–bulk hybrid cloud microphysical model named MSSG-Bin, which has been implemented in the Multi-Scale Simulator for the Geoenvironment (MSSG). In the hybrid approach, a spectral bin scheme is used for liquid droplets, while a bulk scheme is used for solid particles. That is, the expensive but more reliable spectral bin scheme treats the relatively well-understood physics of the liquid phase, and the computationally efficient but less robust bulk scheme is used to treat the poorly understood physics of the ice phase. In the bulk part, the prognostic variables are the mixing ratios of cloud ice, snow, and graupel and the number density of cloud ice particles. The bulk component is consistent with MSSG-Bulk, which is a conventional bulk model implemented in MSSG. One-dimensional kinetic simulations and three-dimensional cloud simulations have confirmed the reliability of MSSG-Bin for warm clouds, free from the approximations made in bulk parameterizations, and its applicability to cold clouds, without the significant additional costs required for a bin treatment of the ice phase. Compared with MSSG-Bulk, MSSG-Bin with 33 bins requires 8.3 times more floating-point operations for a one-dimensional shallow convection case, and 4.9 times more for a three-dimensional shallow convection case. Present results have shown the feasibility of using this model for a 25-m-resolution simulation of shallow cumulus on a 512 × 512 × 200 grid.

Ice in Clouds Experiment—Layer Clouds. Part I: Ice Growth Rates Derived from Lenticular Wave Cloud Penetrations

Abstract Lenticular wave clouds are used as a natural laboratory to estimate the linear and mass growth rates of ice particles at temperatures from −20° to −32°C and to characterize the apparent rate of ice nucleation at water saturation at a nearly constant temperature. Data are acquired from 139 liquid cloud penetrations flown approximately along or against the wind direction. A mean linear ice growth rate of about 1.4 μm s−1, relatively independent of particle size (in the range 100–400 μm) and temperature is deduced. Using the particle size distributions measured along the wind direction, the rate of increase in the ice water content (IWC) is calculated from the measured particle size distributions using theory and from those distributions by assuming different ice particle densities; the IWC is too small to be measured. Very low ice effective densities, &amp;lt;0.1 g cm−3, are needed to account for the observed rate of increase in the IWC and the unexpectedly high linear growth rate. Using data from multiple penetrations through a narrow (along wind) and thin wave cloud with relatively flat airflow streamlines, growth rate calculations are used to estimate where the ice particles originate and whether the ice is nucleated in a narrow band or over an extended period of time. The calculations are consistent with the expectation that the ice formation occurs near the leading cloud edge, presumably through a condensation–freezing process. The observed ice concentration increase along the wind is more likely due to a variation in ice growth rates than to prolonged ice nucleation.

Kinetics of cometary plasma

This paper presents an investigation of the kinetics of a coma, consisting of water vapor plasma and ice grains, illuminated by solar radiation. The photoelectric emission of electrons from ice grains strongly affects the composition of the coma. In deference to the recent emphasis on the character of openness of a complex plasma system, the investigation is based on the balance of the number density of the constituent species and energy of electrons and ions, and the charge neutrality. Accretion of electrons and ionic species by the ice particles, ionization of neutral species by solar radiation, the recombination of electrons and ions, the collisions between electrons, ions and neutral species, charge exchange between atomic ions and neutral molecules and photoelectric emission of electrons by ice grains have been considered in this study; further, the energy exchange associated with these processes has also been taken into account. An interesting conclusion, that the maximum charging of ice particles occurs for an optimum value of number density of ice particles, has been obtained; opposite charging of grains of different sizes has also been predicted in certain conditions. The validity of the theoretical model on the basis of the mean free path of electrons being less than the dimensions of the coma has also been discussed.

Homogeneous nucleation of amorphous solid water particles in the upper mesosphere

Abstract Condensed water particles are known to exist in the high latitude upper mesosphere during the summer months. However, the mechanism or mechanisms through which they nucleate remains uncertain. It is postulated here that particles of amorphous solid water (ASW, condensed water with a non-crystalline structure) may nucleate homogeneously in the summer mesosphere. Using classical nucleation theory and a one-dimensional model, it is shown that more than 10 5 cm −3 amorphous solid water particles can nucleate homogeneously under mesopause conditions. Furthermore, it is shown that homogeneous nucleation competes with heterogeneous nucleation on meteoric smoke particles when the cooling rate is >0.5 K/h. The homogeneous nucleation of amorphous solid water could provide an explanation for the high density of ice particles (many thousands per cm 3 ) thought to be required for electron depletions in the upper mesosphere. A parameterisation for homogeneous nucleation is presented which can be used in other mesospheric cloud models.