Images Of Ice Crystals Research Articles

Classification of Ice Crystal Images from Airborne Cloud Particle Imager Probe (CPI) Using Convolutional Neural Networks (CNN)

Classification of Ice Crystal Images from Airborne Cloud Particle Imager Probe (CPI) Using Convolutional Neural Networks (CNN)

Quantitative Analysis of Ice Crystal Growth During Freezing of Dimethyl Sulfoxide Solutions Under Alternating Current Electric Fields.

During cryopreservation, the growth of ice crystals can cause mechanical damage to samples, which is one of the important factors limiting the quality of preserved samples. To enhance the preservation quality of biological samples, scholars have tried various engineering methods. Among them, an electric field is an essential factor affecting solution freezing. Dimethyl sulfoxide, as a commonly used cryoprotectant, can cause mechanical damage to cells due to ice crystals even when freezing at the optimal freezing rate. Water is a strongly polar dielectric material, and the applied alternating current (AC) electric field will affect the water freezing performance. Therefore, a quantitative study of ice crystal nucleation and growth during freezing of dimethyl sulfoxide solutions under different AC electric field conditions is needed to try to reduce ice crystal damage. We created a liquid-film device to approximate the ice crystal growth process as a two-dimensional image. The frequency of the AC voltage was set from 0 to 50 kHz. We measured the supercooling of the dimethyl sulfoxide solution under AC electric field conditions. As an objective and accurate quantitative analysis of the ice crystal growth process, we propose a Dilated Convolutional Segmentation Transformer for semantic segmentation of ice crystal images. It is concluded that the average area and the growth rate of single ice crystals decrease with increasing electric field frequency at a certain concentration of dimethyl sulfoxide solution. Lower concentrations of dimethyl sulfoxide solution in combination with an AC electric field can achieve similar ice suppression effects as when higher concentrations of dimethyl sulfoxide solution act alone. We believe that AC electric fields are expected to be an aid to cryopreservation and provide some theoretical basis and experimental foundation for its development.

Conditions favorable for secondary ice production in Arctic mixed-phase clouds

Abstract. The Arctic is very susceptible to climate change and thus is warming much faster than the rest of the world. Clouds influence terrestrial and solar radiative fluxes and thereby impact the amplified Arctic warming. The partitioning of thermodynamic phases (i.e., ice crystals and water droplets) within mixed-phase clouds (MPCs) especially influences their radiative properties. However, the processes responsible for ice crystal formation remain only partially characterized. In particular, so-called secondary ice production (SIP) processes, which create supplementary ice crystals from primary ice crystals and the environmental conditions that they occur in, are poorly understood. The microphysical properties of Arctic MPCs were measured during the Ny-Ålesund AeroSol Cloud ExperimENT (NASCENT) campaign to obtain a better understanding of the atmospheric conditions favorable for the occurrence of SIP processes. To this aim, the in situ cloud microphysical properties retrieved by a holographic cloud imager mounted on a tethered balloon system were complemented by ground-based remote sensing and ice-nucleating particle measurements. During the 6 d investigated in this study, SIP occurred during about 40 % of the in-cloud measurements, and high SIP events with number concentrations larger than 10 L−1 of small pristine ice crystals occurred in 4 % of the in-cloud measurements. This demonstrates the role of SIP for Arctic MPCs. The highest concentrations of small pristine ice crystals were produced at temperatures between −5 and −3 ∘C and were related to the occurrence of supercooled large droplets freezing upon collision with ice crystals. This suggests that a large fraction of ice crystals in Arctic MPCs are produced via the droplet-shattering mechanism. From evaluating the ice crystal images, we could identify ice–ice collision as a second SIP mechanism that dominated when fragile ice crystals were observed. Moreover, SIP occurred over a large temperature range and was observed in up to 80 % of the measurements down to −24 ∘C due to the occurrence of ice–ice collisions. This emphasizes the importance of SIP at temperatures below −8 ∘C, which are currently not accounted for in most numerical weather models. Although ice-nucleating particles may be necessary for the initial freezing of water droplets, the ice crystal number concentration is frequently determined by secondary production mechanisms.

Atomic force microscopy imaging of ice crystal surfaces formed in aqueous solutions containing ice-binding proteins

Ice-binding proteins (IBPs) allow organisms to survive below the freezing point by modulating ice crystal growth. These proteins act by binding to ice surfaces, thus inhibiting ice growth. Until now, high-resolution imaging of ice growing in the presence of IBPs has not been possible. We developed a unique in-situ technique that enables atomic force microscopy (AFM) imaging of ice formation and growth in the ice-IBP system. The new technique enables controlling the growth of ice crystals under a strong and focused thermal gradient. We present images of ice crystals with sub-ten nanometer resolution. Ice was grown in the presence of two different IBPs that exhibit specific and unique structures. This development opens the path for fine elucidation of the interaction of IBPs with growing ice surfaces as well as with other frozen systems at unprecedented high resolution. Furthermore, with the exception of crystals growing in thin films, this is the first demonstration for imaging a growing crystal immersed in its own melt with AFM.

Ice crystal images from optical array probes: classification with convolutional neural networks

Abstract. Although airborne optical array probes (OAPs) have existed for decades, our ability to maximize extraction of meaningful morphological information from the images produced by these probes has been limited by the lack of automatic, unbiased, and reliable classification tools. The present study describes a methodology for automatic ice crystal recognition using innovative machine learning. Convolutional neural networks (CNNs) have recently been perfected for computer vision and have been chosen as the method to achieve the best results together with the use of finely tuned dropout layers. For the purposes of this study, The CNN has been adapted for the Precipitation Imaging Probe (PIP) and the 2DS Stereo Probe (2DS), two commonly used probes that differ in pixel resolution and measurable maximum size range for hydrometeors. Six morphological crystal classes have been defined for the PIP and eight crystal classes and an artifact class for the 2DS. The PIP and 2DS classifications have five common classes. In total more than 8000 images from both instruments have been manually labeled, thus allowing for the initial training. For each probe the classification design tries to account for the three primary ice crystal growth processes: vapor deposition, riming, and aggregation. We included classes such as fragile aggregates and rimed aggregates with high intra-class shape variability that are commonly found in convective clouds. The trained network is finally tested through human random inspections of actual data to show its real performance in comparison to what humans can achieve.

Effect of ι-carrageenan and its acidic and enzymatic hydrolysates on ice crystal structure changes in model sucrose solution

The aim of the study was to compare the effects of ɩ-carrageenan and its hydrolysates on ice recrystallisation inhibition (IRI) in model solutions. Acid hydrolysis of ɩ-carrageenan was carried out using hydrochloric acid (HCl). Enzymatic hydrolysis was conducted using the enzymes β-galactosidase and commercial lactase. Hydrolysates were used as a stabiliser in model system solutions. The recrystallisation process was analysed on the basis of images of ice crystals in 50% sucrose and 50% sucrose with the addition of sodium caseinate after 24, 48, 72 and 96 h of storage at − 8 °C. The molecular mass after hydrolysis of ɩ-carrageenan was decreased by around 16% after hydrolysis with β-galactosidase use, around 3% after hydrolysis with commercial lactase use and 24% after acid hydrolysis. Furthermore, using the hydrolysates of ɩ-carrageenan had a strong impact on the recrystallisation process. Significant retardation of recrystallisation in the sucrose solution was observed for the addition of both types of hydrolysates (after acid and enzymatic hydrolysis). However, in sucrose with the addition of sodium caseinate, the oligosaccharides obtained after hydrolysis with commercial lactase use were more effective in recrystallisation inhibition – the average diameter of ice crystals was 16.92 µm. The spectra obtained with Fourier Transform Infrared Spectroscopy (FTIR) show changes in the absorption bands, which confirms that functional groups changes could lead to the IRI activity of gained hydrolysates.

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

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.

Neural Network Classification of Ice-Crystal Images Observed by an Airborne Cloud Imaging Probe

ABSTRACT In the atmosphere, cloud particles have different shapes. The study of cloud particle shapes plays an important role in understanding cloud precipitation processes, radiative transfer, and weather modification. The image resolution and data quality of cloud probes affect the accuracy of the classification of particle shapes. To solve the occlusion of the photosensitive edge of the particle image and achieve automatic, high-precision ice-crystal classification of airborne Cloud Imaging Probe (CIP) ice-crystal images, this study uses a traditional image processing algorithm for data quality control and applies artificial intelligence algorithms to classify ice-crystal images. At present, there are mainly two types of ice-crystal classification methods, one classifies the shape of ice crystals using a pattern parameterization scheme, and the other uses an artificial intelligence network model to classify the shape. Combined with data quality control, the dataset was tested on eight models, and the TL-EfficientNet-b6 model was found to be the most accurate. Therefore, the TL-EfficientNet-b6 classifier model was used in this study, which is a newly developed convolutional neural network (CNN) based on a transfer learning method. Experimental results show that the TL-EfficientNet-b6 model can reach 100% in the single-class precision of tiny and hexagonal ice crystals, and the average precision can reach 98%. These results are more accurate than those using traditional classification methods. This method could be valuable in cloud microphysics research and weather modification.

Classification of Ice Crystal Habits Observed From Airborne Cloud Particle Imager by Deep Transfer Learning

AbstractIce clouds are mostly composed of different ice crystal habits. It is of great importance to classify ice crystal habits seeing as they could greatly impact single‐scattering properties of ice crystal particles. The single‐scattering properties play an important role in the study of cloud remote sensing and the Earth's atmospheric radiation budget. However, there are countless ice crystals with different shapes in ice clouds, and the task of empirical classification based on naked‐eye observations is unreliable, time consuming and subjective, which leads to classification results having obvious uncertainties and biases. In this paper, the images of ice crystals observed from airborne Cloud Particle Imager in China are used to establish an ice crystal data set called Ice Crystals Database in China, which consists of 10 habit categories containing over 7,000 images. We propose an automatic classification model of ice crystal habits, called TL‐ResNet152, which is a deep convolutional neural network based on the newly developed method of transfer learning. The results show that the TL‐ResNet152 model could achieve reliable performance in ice crystal habits classification with the accuracy of 96%, which is far more accurate than traditional classification methods. Achieving high‐precision automatic classification of ice crystal habits will help us better understand the radiation characteristics of ice clouds.

Effects of extremely low frequency electromagnetic field on the freezing processes of two liquid systems

Freezing process assisted by electromagnetic field is one of the emerging novel food freezing technologies. The present study investigated the effects of extremely low frequency electromagnetic field (ELF-EMF) on the freezing process of two aqueous solutions with different solutes of 9 g/L sodium chloride (physiological saline) and 10 mmol/L PDADMAC (poly dimethyl diallyl ammonium chloride). Freezing parameters such as supercooling degree were determined in different frequency bands, and some parameters of thawed samples were also measured. Results showed that the supercooling degree of physiological saline was decreased and that of PDADMAC solution increased first and then decreased, while the images of ice crystals showed more and deeper cracks created in some treated samples. The surface tension and contact angle indicated that the energy balance of samples was disturbed under ELF-EMF, and the infrared and Raman spectra of the treated PDADMAC solution showed that the polarized feature and dipole moments of macromolecular groups were enhanced, which might contribute to the change of the freezing process.

Ice Crystal Sizes in High Ice Water Content Clouds. Part II: Statistics of Mass Diameter Percentiles in Tropical Convection Observed during the HAIC/HIWC Project

AbstractHigh ice water content (IWC) regions in mesoscale convective systems (MCSs) are a potential threat to commercial aviation, as they are suspected to cause in-service engine power-loss events and air data probe malfunctions. To investigate this, the high-altitude ice crystals (HAIC)/high ice water content (HIWC) projects set up a first field campaign in Darwin (Australia) in 2014. The airborne instrumentation was selected to provide the most accurate measurements of both the bulk total water content (TWC), using a specially developed isokinetic evaporator, and the individual ice crystals properties, using particle imaging probes.This study focuses on determining the size ranges of ice crystals responsible for the mass in high IWC regions, defined here as cloud regions with IWC greater than 1.5 g m−3. It is shown that for high IWC areas in most of the encountered MCSs, median mass diameters (MMDs) of ice crystals range from 250 to 500 μm and decrease with increasing TWC and decreasing temperature. At the same time, the mass contribution of the smallest crystals (below 100 μm) remains generally low (below 15%).In contrast, data from two flight missions in a long-lasting quasi-stationary tropical storm reveal that high IWC values can also be associated with MMDs in the range 400–800 μm and peak values of up to 2 mm. Ice crystal images suggest a major growth contribution by vapor deposition (columns, capped columns) even for such larger MMD values.

Modification of kappa carrageenan by β-galactosidase as a new method to inhibit recrystallization of ice

The effects of κ-carrageenan and its hydrolysates on inhibition of recrystallization of ice in sucrose solutions during storage were compared. Enzymatic hydrolysis of κ-carrageenan was carried out using β-galactosidase. The recrystallization process was analyzed on the basis of images of ice crystals in 50% sucrose solution at 24, 48, 72 and 96 h of storage at −8 °C.Enzymatic hydrolysis compared to non-degraded κ-carrageenan caused a slight (about 16%) reduction in molecular mass. Furthermore, the use of the hydrolysates (after 48 and 72 h of hydrolysis) effectively inhibited the recrystallization process, wherein the diameter of the crystals after 96 h storage was 6 μm and was more than three times smaller than that measured for a solution containing kappa carrageenan (19 μm).

Three-Dimensional Measurement of Ice Crystals in Frozen Materials by Near-Infrared Imaging Spectroscopy

A novel technique was developed to recognize ice crystals in biological materials and to analyze their three-dimensional morphology using a Cryogenic Micro-Slicer Spectral Imaging System with a micro-slicer unit and a near-infrared spectral imaging unit. Consecutive cross-sections of a frozen sample were exposed by the multi-slicing operations with a minimum thickness of 1 µm, and their images were taken by the imaging unit. Spectroscopic analysis using a near-infrared spectrum meter showed an absorption peak at 1460 nm for pure water. Based on the observations of the absorption band of ice crystals in the wavelength range of 1450–1570 nm and its peak at 1495 nm, a commodity-type bandpass filter with a central wavelength of 1500 nm was adopted to identify ice crystals in near-infrared images. The absorption peak of water exhibited a tendency to move toward longer wavelengths with decreasing sample temperature from 25 °C to −15 °C. The filtered images of ice crystals in frozen samples were darker than the other components at the peak wavelength of ice crystals. The three-dimensional reconstructed morphology of ice crystals revealed that they were formed along the direction of heat transfer while freezing. The proposed method provides a novel tool to investigate the effects of freezing conditions on the size, morphology and distribution of ice crystals.

The influence of kappa carrageenan and its hydrolysates on the recrystallization process in sorbet

The aim of this research study was to investigate the recrystallization process during freezing and storage of strawberry sorbet with the addition of new “poligeenan” as a final product of κ-carrageenan acid hydrolysis. The recrystallization process was analyzed based on the images of ice crystals taken after one hour, one week and one month of sorbets storage at the temperature of −18°C and using a microscope and camera (Nikon) adapted to work at temperature below zero. The images were then analyzed using the program NIS Elements D.Based on the performed experiments, it was found that the addition of the new “poligeenan” to sorbets had a stronger inhibiting effect on the recrystallization process than the addition of κ-carrageenan. After one month of storage of sorbet with added κ-carrageenan, the diameter of ice crystals was 25.04μm, while in sorbet with the new “poligeenan” added it was less than 12μm.

Dimensions and aspect ratios of natural ice crystals

Abstract. During the 2006 Tropical Warm Pool International Cloud Experiment (TWP-ICE) in the tropics, the 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC) in the Arctic, and the 2010 Small PARTicles In CirrUS (SPARTICUS) campaign at mid-latitudes, high-resolution images of ice crystals were recorded by a Cloud Particle Imager at temperatures (T) between −87 and 0 °C. The projected maximum dimension (D'), length (L'), and width (W') of pristine columns, plates, and component bullets of bullet rosettes were measured using newly developed software, the Ice Crystal Ruler. The number of bullets in each bullet rosette was also measured. Column crystals were further distinguished as either horizontally oriented columns or columns with other orientations to eliminate any orientation effect on the measured dimensions. The dimensions and aspect ratios (AR, the dimension of the major axis divided by the dimension of the minor axis) of crystals were determined as functions of temperature, geophysical location, and type of cirrus. Dimensions of crystals generally increased with temperature. Columns and bullets had larger dimensions (i.e., W') of the minor axis (i.e., a axis) for a given dimension (i.e., D' orL') of the major axis (i.e., c axis), and thus smaller AR, as T increased, whereas this trend did not occur for plate crystals. The average number of branches in bullet rosettes was 5.50 ± 1.35 during three campaigns and 6.32 ± 1.34 (5.46 ± 1.34; 4.95 ± 1.01) during TWP-ICE (SPARTICUS; ISDAC). The AR of bullets increased with the number of branches in bullet rosettes. Most dimensions of crystals and ARs of columnar crystals measured during SPARTICUS were larger than those measured during TWP-ICE and ISDAC at −67 < T < -35 °C and at −40 < T < −15 °C, respectively. The relative occurrence of varying pristine habits depended strongly on cirrus type (i.e., anvil or non-anvil clouds), with plates especially occurring more frequently in anvils. The L–W relationships of columns derived using current data exhibited a strong dependence on temperature; similar relationships determined in previous studies were within the range of the current data.

Balloon-borne and Raman lidar observations of Asian dust and cirrus cloud properties over Tsukuba, Japan

The vertical distributions of the microphysical and optical properties of tropospheric aerosols and cirrus cloud were measured using an instrumented balloon and a ground-based Raman lidar over Tsukuba, Japan (36°N, 140°E), during the Asian dust events on 9 and 21 May 2007 to investigate the influence of Asian mineral dust on ice cloud formation in the upper troposphere. The instrumented balloon measured the particle size distribution, ice crystal images, dew/frost point, relative humidity, and temperature. The Raman lidar measured the particle backscattering and extinction coefficients and the depolarization ratio at a wavelength of 532 nm. The results of the balloon measurements showed that supermicrometer (0.7 to 2.8 µm in optical-equivalent radius) dust particles and ice crystals (10 to 400 µm in maximum dimension) were present in the upper troposphere (8 to 12 km in altitude), with number concentrations varying from 5 × 10−3 to 0.6 cm−3 for dust and from 5 × 10−3 to 0.15 cm−3 for ice crystals. The Raman lidar measurement indicated that the particle depolarization ratios were 15 to 35% in the altitude range of 6 to 12 km, indicating the predominance of nonspherical particles in the region. The temperature ranged from −33 to −63°C, and the relative humidity with respect to ice (RHi), estimated from the total (vapor plus condensate) water content obtained with the Snow White hygrometer in the cloud, was 130% at maximum on 9 May, which was close to the activation point of Asian mineral dust as ice nuclei to form ice crystals.

Ice particle growth in the presence of nitric oxide

An experimental study was undertaken to examine the effects of nitric oxide (NO) on ice crystal growth. This study focused on growth rates and ice crystal habit. A chamber was used to grow ice at controlled temperature and supersaturation, and images of ice crystals were obtained using a video camera. Ice crystals grow more quickly when NO concentrations are elevated above background to 370 and 710 ppb and lengthen (c‐axis growth) more quickly than they thicken (a‐axis growth). The results have implications for ice crystal growth in thunderstorms and may aid in determining whether an air parcel in a thunderstorm originated from an electrically active region.

Particle Habit Imaging Using Incoherent Light: A First Step toward a Novel Instrument for Cloud Microphysics

Abstract The imaging unit of the novel cloud particle instrument Particle Habit Imaging and Polar Scattering (PHIPS) probe has been developed to image individual ice particles produced inside a large cloud chamber. The PHIPS produces images of single airborne ice crystals, illuminated with white light of an ultrafast flashlamp, which are captured at a maximum frequency of ∼5 Hz by a charge-coupled device (CCD) camera with microscope optics. The imaging properties of the instrument were characterized by means of crystalline sodium hexafluorosilicate ice analogs, which are stable at room temperature. The optical resolving power of the system is ∼2 μm. By using dedicated algorithms for image processing and analysis, the ice crystal images can be analyzed automatically in terms of size and selected shape parameters. PHIPS has been operated at the cloud simulation chamber facility Aerosol Interaction and Dynamics in the Atmosphere (AIDA) of the Karlsruhe Institute of Technology at different temperatures between −17° and −4°C in order to study the influence of the ambient conditions, that is, temperature and ice saturation ratio, on ice crystal habits. The area-equivalent size distributions deduced from the PHIPS images are compared with the retrieval results from Fourier transform infrared (FTIR) extinction spectroscopy in case of small (<20 μm) and with single particle data from the cloud particle imager in case of larger (>20 μm) ice particles. Good agreement is found for both particle size regimes.

Optical properties of pristine ice crystals in mid-latitude cirrus clouds: a case study during CIRCLE-2 experiment

Abstract. In this paper, we describe in situ observations of mid-latitude cirrus cloud band carried out on 16 May 2007 during the CIRCLE-2 experiment. The Polar Nephelometer and the Cloud Particle Imager (CPI) instruments with PMS FSSP-300 and 2D-C probes were used for the description of the optical and microphysical cloud properties. Two selected cloud regions are compared and discussed in detail. Significant differences in optical properties are evidenced in terms of 22° halo occurrences even though prevalent planar-plate ice crystals are observed in both cloud regions. Featureless scattering phase functions are measured in the first cloud region located near the trailing edge of the cirrus-band at about 11 800 m/−57 °C. In contrast, well pronounced 22° halo peaks are observed with predominant similar-shaped ice crystals near the cirrus-band leading edge at 7100 m/−27 °C. CPI ice crystal images with Polar Nephelometer observations are carefully analysed and interpreted from a theoretical light scattering model in order to explain occurrence and non-occurrence of the 22° halo feature. The results highlight that the halo peaks are inherent only in perfect plate ice crystals (or pristine crystals). On the basis of previous datasets in mid-latitude cirrus, it is found that simple pristine crystals are uncommon whereas particles with imperfect or complex shapes are prevalent. As a result, phase functions that are smooth and featureless best represent cirrus scattering properties.

Microphysical and Optical Properties of Atmospheric Ice Crystals at South Pole Station

Abstract In early February 2001 (during the austral summer), over 900 000 digital images of ice crystals were recorded at the South Pole using two ground-based cloud particle imagers (CPIs). Of these, 721 572 crystals >50 μm were classified into crystal habits. When sorted by number, 30% of the crystals were rosette shaped (mixed-habit rosettes, platelike polycrystals, and rosette shapes with side planes), 45% were diamond dust (columns, thick plates, and plates), and 25% were irregular. When sorted by area, rosette shapes comprised 50%, diamond dust 30% and irregular 20%. By mass, the percentages were 57% rosette shapes, 23% diamond dust, and 20% irregular. Particle size distributions as a function of maximum dimension and equivalent radius are compared with previous studies. Particles are generally found to be slightly larger than previous austral wintertime studies. In 2002, a polar nephelometer (PN) that measures scattering phase function was incorporated with one of the CPIs. Correlated measurements between the two instruments showed that 22° and 46° peaks in the phase function were present when diamond dust was recorded by the CPI, but not when rosette shapes were present. Visual observations confirmed the presence of 22° and 46° atmospheric halos in some, but not all, of the diamond dust events. No visual halos were observed when rosette shapes were precipitating. Average PN phase functions are presented for diamond dust and rosette shapes. The diamond dust and rosette-shaped ice crystals appear to be very similar in shape to those observed by CPIs in cirrus clouds. Cloud conditions at the South Pole that were associated with various crystal types are discussed, as are some effects of blowing snow.