Semi-Analytic Functions to Calculate the Deposition Coefficients for Ice Crystal Vapor Growth in Bin and Bulk Microphysical Models.

2021 ◽  
Author(s):  
Jerry Y. Harrington ◽  
G. Alexander Sokolowsky ◽  
Hugh Morrison
Keyword(s):  
Ice Crystals ◽  
Mixing Ratio ◽  
Ice Crystal ◽  
Surface Attachment ◽  
Vapor Growth ◽  
Diffusion Limited ◽  
Cloud Models ◽  
Variable Surface ◽  
Deposition Coefficient ◽  
Relative Errors

AbstractNumerical cloud models require estimates of the vapor growth rate for ice crystals. Current bulk and bin microphysical parameterizations generally assume that vapor growth is diffusion limited, though some parameterizations include the influence of surface attachment kinetics through a constant deposition coefficient. A parameterization for variable deposition coefficients is provided herein. The parameterization is an explicit function of the ambient ice supersaturation and temperature, and an implicit function of crystal dimensions and pressure. The parameterization is valid for variable surface types including growth by dislocations and growth by step nucleation. Deposition coefficients are predicted for the two primary growth directions of crystals, allowing for the evolution of the primary habits. Comparisons with benchmark calculations of instantaneous mass growth indicate that the parameterization is accurate to within a relative error of 1%. Parcel model simulations using Lagrangian microphysics as a benchmark indicate that the bulk parameterization captures the evolution of mass mixing ratio and fall speed with typical relative errors of less than 10%, whereas the average axis lengths can have errors of up to 20%. The bin model produces greater accuracy with relative errors often less that 10%. The deposition coefficient parameterization can be used in any bulk and bin scheme, with low error, if an equivalent volume spherical radius is provided.

scholarly journals Estimating Surface Attachment Kinetic and Growth Transition Influences on Vapor-Grown Ice Crystals

2020 ◽  
Vol 77 (7) ◽  
pp. 2393-2410
Author(s):  
Gwenore F. Pokrifka ◽  
Alfred M. Moyle ◽  
Lavender Elle Hanson ◽  
Jerry Y. Harrington
Keyword(s):  
Diffusion Chamber ◽  
Ice Crystals ◽  
Growth Theory ◽  
Growth Data ◽  
Surface Attachment ◽  
Mass Growth ◽  
Vapor Growth ◽  
Deposition Coefficient ◽  
Direct Use ◽  
Large Decline

AbstractThere are few measurements of the vapor growth of small ice crystals at temperatures below −30°C. Presented here are mass-growth measurements of heterogeneously and homogeneously frozen ice particles grown within an electrodynamic levitation diffusion chamber at temperatures between −44° and −30°C and supersaturations si between 3% and 29%. These growth data are analyzed with two methods devised to estimate the deposition coefficient α without the direct use of si. Measurements of si are typically uncertain, which has called past estimates of α into question. We find that the deposition coefficient ranges from 0.002 to unity and is scattered with temperature, as shown in prior measurements. The data collectively also show a relationship between α and si, with α rising (falling) with increasing si for homogeneously (heterogeneously) frozen ice. Analysis of the normalized mass growth rates reveals that heterogeneously frozen crystals grow near the maximum rate at low si, but show increasingly inhibited (low α) growth at high si. Additionally, 7 of the 17 homogeneously frozen crystals cannot be modeled with faceted growth theory or constant α. These cases require the growth mode to transition from efficient to inefficient in time, leading to a large decline in α. Such transitions may be, in part, responsible for the inconsistency in prior measurements of α.

scholarly journals On Calculating Deposition Coefficients and Aspect-Ratio Evolution in Approximate Models of Ice Crystal Vapor Growth

2019 ◽  
Vol 76 (6) ◽  
pp. 1609-1625 ◽  
Author(s):  
Jerry Y. Harrington ◽  
Alfred Moyle ◽  
Lavender Elle Hanson ◽  
Hugh Morrison
Keyword(s):  
Aspect Ratio ◽  
Free Fall ◽  
Parametric Models ◽  
Ice Crystal ◽  
Growth Data ◽  
Surface Attachment ◽  
Vapor Growth ◽  
Liquid Saturation ◽  
Cloud Models ◽  
Small Crystals

Abstract Models of ice crystal vapor growth require estimates of the deposition coefficient α when surface attachment kinetics limit growth and when ice crystal shape is predicted. Parametric models can be used to calculate α for faceted growth as long as characteristic supersaturation values are known. However, previously published measurements of are limited to temperatures higher than −40°C. Estimates of at temperatures between −40° and −70°C are provided here through reanalysis of vapor growth data. The estimated follow the same functional temperature dependence as data taken at higher temperatures. Polynomial fits to are used as inputs to a parameterization of α suitable for use in cloud models. Comparisons of the parameterization with wind tunnel data show that growth at liquid saturation and constant temperatures between −3° and −20°C can be modeled by ledge nucleation for larger (hundreds of micrometers) crystals; however, comparisons with free-fall chamber data at −7°C suggest that dislocation growth may be required to model the vapor growth of small crystals (~20 μm) at liquid saturation. The comparisons with free-fall chamber data also show that the parameterization can reproduce the measured pressure dependence of aspect-ratio evolution. Comparisons with a hexagonal growth model indicate that aspect-ratio evolution based on the theory of Chen and Lamb produces unrealistically fast column growth near −7°C that is mitigated if a theory based on faceted growth is used. This result indicates that the growth hypothesis used in habit-evolving microphysical models needs to be revised when deposition coefficients are predicted.

Modeling Ice Crystal Aspect Ratio Evolution during Riming: A Single-Particle Growth Model

2015 ◽  
Vol 72 (7) ◽  
pp. 2569-2590 ◽  
Author(s):  
Anders A. Jensen ◽  
Jerry Y. Harrington
Keyword(s):  
Wind Tunnel ◽  
Growth Model ◽  
Liquid Water ◽  
Single Particle ◽  
Liquid Drop ◽  
Ice Crystals ◽  
Ice Crystal ◽  
Vapor Growth ◽  
Wind Tunnel Data ◽  
Fall Speed

This paper describes and tests a single-particle ice growth model that evolves both ice crystal mass and shape as a result of vapor growth and riming. Columnar collision efficiencies in the model are calculated using a new theoretical method derived from spherical collision efficiencies. The model is able to evolve mass, shape, and fall speed of growing ice across a range of temperatures, and it compares well with wind tunnel data. The onset time of riming and the effects of riming on mass and fall speed between −3° and −16°C are modeled, as compared with wind tunnel data for a liquid water content of 0.4 g m−3. Under these conditions, riming is constrained to the more isometric habits near −10° and −4°C. It is shown that the mass and fall speed of riming dendrites depend on the liquid drop distribution properties, leading to a range of mass–size and fall speed–size relationships. Riming at low liquid water contents is shown to be sensitive to ice crystal habit and liquid drop size. Moreover, very light riming can affect the shape of ice crystals enough to reduce vapor growth and suppress overall mass growth, as compared with those same ice crystals if they were unrimed.

The Effects of Surface Kinetics on Crystal Growth and Homogeneous Freezing in Parcel Simulations of Cirrus

2015 ◽  
Vol 72 (8) ◽  
pp. 2929-2946 ◽  
Author(s):  
Chengzhu Zhang ◽  
Jerry Y. Harrington
Keyword(s):  
Crystal Growth ◽  
Mean Free Path ◽  
Cloud Base ◽  
Ice Crystal ◽  
Surface Kinetics ◽  
Cloud Models ◽  
Cloud Development ◽  
Deposition Coefficient ◽  
Growth Rate Control ◽  
Homogeneous Freezing

Abstract The uptake of water vapor excess by ice crystals is a key process regulating the supersaturation in cold clouds. Both the ice crystal number concentration and depositional growth rate control the vapor uptake rate and are sensitive to the deposition coefficient . The deposition coefficient depends on temperature and supersaturation; however, cloud models either ignore or assume a constant . In this study, the effects of on crystal growth and homogeneous freezing of haze solution drops in simulated cirrus are examined. A Lagrangian parcel model is used with a new ice growth model that predicts the deposition coefficients along two crystal growth axes. Parcel model results indicate that predicting can be critical for predicting ice nucleation and supersaturation at different stages of cloud development. At cloud base, model results show that surface kinetics constrain the homogeneous freezing rate primarily through the growth impact of small particle sizes in comparison to the mean free path. The deposition coefficient has little effect on homogeneous freezing rates, because the high cloud-base supersaturation produces near unity. Above the cloud-base nucleation zone, decreasing supersaturation causes to decrease to values as low as 0.001. These low values of lead to higher steady-state supersaturation. Also, the low values of produce substantial impacts on particle shape evolution and particle size, both of which are dependent on updraft strength.

scholarly journals Evaluation of radar reflectivity factor simulations of ice crystal populations from in situ observations for the retrieval of condensed water content in tropical mesoscale convective systems

2017 ◽  
Vol 10 (6) ◽  
pp. 2239-2252 ◽  
Author(s):  
Emmanuel Fontaine ◽  
Delphine Leroy ◽  
Alfons Schwarzenboeck ◽  
Julien Delanoë ◽  
Alain Protat ◽  
...  
Keyword(s):  
Water Content ◽  
Relative Error ◽  
Number Concentration ◽  
Radar Reflectivity ◽  
Ice Crystals ◽  
Ice Crystal ◽  
Condensed Water ◽  
Relative Errors ◽  
Reflectivity Factor

Abstract. This study presents the evaluation of a technique to estimate cloud condensed water content (CWC) in tropical convection from airborne cloud radar reflectivity factors at 94 GHz and in situ measurements of particle size distributions (PSDs) and aspect ratios of ice crystal populations. The approach is to calculate from each 5 s mean PSD and flight-level reflectivity the variability of all possible solutions of m(D) relationships fulfilling the condition that the simulated radar reflectivity factor (T-matrix method) matches the measured radar reflectivity factor. For the reflectivity simulations, ice crystals were approximated as oblate spheroids, without using a priori assumptions on the mass–size relationship of ice crystals. The CWC calculations demonstrate that individual CWC values are in the range ±32 % of the retrieved average CWC value over all CWC solutions for the chosen 5 s time intervals. In addition, during the airborne field campaign performed out of Darwin in 2014, as part of the international High Altitude Ice Crystals/High Ice Water Content (HAIC/HIWC) projects, CWCs were measured independently with the new IKP-2 (isokinetic evaporator probe) instrument along with simultaneous particle imagery and radar reflectivity. Retrieved CWCs from the T-matrix radar reflectivity simulations are on average 16 % higher than the direct CWCIKP measurements. The differences between the CWCIKP and averaged retrieved CWCs are found to be primarily a function of the total number concentration of ice crystals. Consequently, a correction term is applied (as a function of total number concentration) that significantly improves the retrieved CWC. After correction, the retrieved CWCs have a median relative error with respect to measured values of only −1 %. Uncertainties in the measurements of total concentration of hydrometeors are investigated in order to calculate their contribution to the relative error of calculated CWC with respect to measured CWCIKP. It is shown that an overestimation of the concentration by about +50 % increases the relative errors of retrieved CWCs by only +29 %, while possible shattering, which impacts only the concentration of small hydrometeors, increases the relative error by about +4 %. Moreover, all cloud events with encountered graupel particles were studied and compared to events without observed graupel particles. Overall, graupel particles seem to have the largest impact on high crystal number-concentration conditions and show relative errors in retrieved CWCs that are higher than for events without graupel particles.

The “KIMWIPE” Effect in Ultra-Thin Cryosections

1985 ◽  
Vol 43 ◽  
pp. 458-459
Author(s):  
I. Taylor ◽  
P. Ingram ◽  
J.R. Sommer
Keyword(s):  
Skeletal Muscle ◽  
Electrical Stimulation ◽  
Muscle Fibers ◽  
Ice Crystals ◽  
Crystal Formation ◽  
Ice Crystal ◽  
Thin Sections ◽  
Skeletal Muscle Fibers ◽  
Freeze Dried ◽  
Ice Crystal Formation

In studying quick-frozen single intact skeletal muscle fibers for structural and microchemical alterations that occur milliseconds, and fractions thereof, after electrical stimulation, we have developed a method to compare, directly, ice crystal formation in freeze-substituted thin sections adjacent to all, and beneath the last, freeze-dried cryosections. We have observed images in the cryosections that to our knowledge have not been published heretofore (Figs.1-4). The main features are that isolated, sometimes large regions of the sections appear hazy and have much less contrast than adjacent regions. Sometimes within the hazy regions there are smaller areas that appear crinkled and have much more contrast. We have also observed that while the hazy areas remain still, the regions of higher contrast visibly contract in the beam, often causing tears in the sections that are clearly not caused by ice crystals (Fig.3, arrows).

The Mystery of Ice Crystal Multiplication in a Laboratory Experiment

2013 ◽  
Vol 71 (1) ◽  
pp. 89-97 ◽  
Author(s):  
Gianni Santachiara ◽  
Franco Belosi ◽  
Franco Prodi
Keyword(s):  
Laboratory Experiment ◽  
Supercooled Liquid ◽  
Ice Crystals ◽  
Formation Processes ◽  
Ice Crystal ◽  
Droplet Vaporization ◽  
Ice Nuclei ◽  
Cold Room ◽  
The Mean ◽  
Ice Multiplication

Abstract This paper addresses the problem of the large discrepancies between ice crystal concentrations in clouds and the number of ice nuclei in nearby clear air reported in published papers. Such discrepancies cannot always be explained, even by taking into account both primary and secondary ice formation processes. A laboratory experiment was performed in a cylindrical column placed in a cold room at atmospheric pressure and temperature in the −12° to −14°C range. Supercooled droplets were nucleated in the column, in the absence of aerosol ice nuclei, by injecting ice crystals generated outside in a small syringe. A rapid increase in the ice crystal concentration was observed in the absence of any known ice multiplication. The ratio between the mean number of ice crystals in the column, after complete droplet vaporization, and the number of ice crystals introduced in the column was about 10:1. The presence of small ice crystals (introduced at the top of the column) in the unstable system (supercooled droplets) appears to trigger the transformation in the whole supercooled liquid cloud. A possible explanation could be that the rapidly evaporating droplets cool sufficiently to determine a homogeneous nucleation.

scholarly journals Synthetic insect antifreeze peptides modify ice crystal growth habit

CrystEngComm ◽  
2017 ◽  
Vol 19 (16) ◽  
pp. 2163-2167 ◽  
Author(s):  
Charles H. Z. Kong ◽  
Ivanhoe K. H. Leung ◽  
Vijayalekshmi Sarojini
Keyword(s):  
Crystal Growth ◽  
Small Molecule ◽  
Growth Habit ◽  
Antifreeze Protein ◽  
Ice Crystals ◽  
Ice Crystal ◽  
Antifreeze Peptides ◽  
Antifreeze Activity

Synthetic antifreeze peptides based on the hyperactive antifreeze protein modify the shape of ice crystals and show enhanced antifreeze activity with the addition of a small molecule.

Optimized intelligent algorithm for classifying cloud particles recorded by a Cloud Particle Imager

2021 ◽  
Author(s):  
Zepei Wu ◽  
Shuo Liu ◽  
Delong Zhao ◽  
Ling Yang ◽  
Zixin Xu ◽  
...  
Keyword(s):  
Processing Speed ◽  
Cloud Microphysics ◽  
Parameter Analysis ◽  
Ice Crystals ◽  
Support Vector ◽  
Svm Classifier ◽  
Ice Crystal ◽  
Cloud Particle ◽  
Average Accuracy ◽  
Cloud Particles

AbstractCloud particles have different shapes in the atmosphere. Research on cloud particle shapes plays an important role in analyzing the growth of ice crystals and the cloud microphysics. To achieve an accurate and efficient classification algorithm on ice crystal images, this study uses image-based morphological processing and principal component analysis, to extract features of images and apply intelligent classification algorithms for the Cloud Particle Imager (CPI). Currently, there are mainly two types of ice-crystal classification methods: one is the mode parameterization scheme, and the other is the artificial intelligence model. Combined with data feature extraction, the dataset was tested on ten types of classifiers, and the highest average accuracy was 99.07%. The fastest processing speed of the real-time data processing test was 2,000 images/s. In actual application, the algorithm should consider the processing speed, because the images are in the order of millions. Therefore, a support vector machine (SVM) classifier was used in this study. The SVM-based optimization algorithm can classify ice crystals into nine classes with an average accuracy of 95%, blurred frame accuracy of 100%, with a processing speed of 2,000 images/s. This method has a relatively high accuracy and faster classification processing speed than the classic neural network model. The new method could be also applied in physical parameter analysis of cloud microphysics.

scholarly journals Characterization of Arctic mixed-phase cloud properties at small scale and coupling with satellite remote sensing

2017 ◽  
Author(s):  
Guillaume Mioche ◽  
Olivier Jourdan ◽  
Julien Delanoë ◽  
Christophe Gourbeyre ◽  
Guy Febvre ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Crystal Size ◽  
Mixed Phase ◽  
Ice Crystals ◽  
Small Scale ◽  
Vertical Profiles ◽  
Liquid Droplets ◽  
Ice Crystal ◽  
High Concentration ◽  
Ice Crystal Size

Abstract. This study aims to characterize the microphysical and optical properties of ice crystals and supercooled liquid droplets within low-level Arctic mixed-phase clouds (MPC). We compiled and analyzed cloud in situ measurements from 4 airborne campaigns (18 flights, 71 vertical profiles in MPC) over the Greenland Sea and the Svalbard region. Cloud phase discrimination and representative vertical profiles of number, size, mass and shapes of ice crystals and liquid droplets are assessed. The results show that the liquid phase dominates the upper part of the MPC with high concentration of small droplets (120 cm−3, 15&tinsp;μm), and averaged LWC around 0.2 g m−3. The ice phase is found everywhere within the MPC layers, but dominates the properties in the lower part of the cloud and below where ice crystals precipitate down to the surface. The analysis of the ice crystal morphology highlights that irregulars and rimed are the main particle habit followed by stellars and plates. We hypothesize that riming and condensational growth processes (including the Wegener-Bergeron-Findeisein mechanism) are the main growth mechanisms involved in MPC. The differences observed in the vertical profiles of MPC properties from one campaign to another highlight that large values of LWC and high concentration of smaller droplets are possibly linked to polluted situations which lead to very low values of ice crystal size and IWC. On the contrary, clean situations with low temperatures exhibit larger values of ice crystal size and IWC. Several parameterizations relevant for remote sensing or modeling are also determined, such as IWC (and LWC) – extinction relationship, ice and liquid integrated water paths, ice concentration and liquid water fraction according to temperature. Finally, 4 flights collocated with active remote sensing observations from CALIPSO and CloudSat satellites are specifically analyzed to evaluate the cloud detection and cloud thermodynamical phase DARDAR retrievals. This comparison is valuable to assess the sub-pixel variability of the satellite measurements as well as their shortcomings/performance near the ground.

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