Falling Snow Particles Research Articles

Snow Particle Analyzer for Simultaneous Measurements of Snow Density and Morphology

AbstractThe detailed characterization of snow particles is critical for understanding the snow settling behavior and modeling the ground snow accumulation for various applications such as prevention of avalanches and snowmelt‐caused floods, etc. In this study, we present a snow particle analyzer for simultaneous measurements of various properties of fresh falling snow, including their size, shape, type, and density. The analyzer consists of a digital inline holography module for imaging falling snow particles in a sample volume of 88 cm3 and a high‐precision scale to measure the weight of the same particles in a synchronized fashion. The holographic images are processed in real‐time using a machine learning model and post‐processing to determine snow particle size, shape, and type. Such information is used to obtain the estimated volume, which is subsequently correlated with the weight of snow particles to estimate their density. The performance of the analyzer is assessed using monodispersed spherical glass and foam beads, irregular salt crystals, and thin disks with various shapes with known density, which shows <10% density measurement errors. In addition, the analyzer was tested in a number of field deployments under different snow and wind conditions. The system is able to achieve measurements of various snow properties at single particle resolution and statistical robustness. The analyzer was also deployed for 4 hr of operation during a snow event with changing snow and wind conditions, demonstrating its potential for long‐term and real‐time monitoring of the time‐varying snow properties in the field.

Relationships between snow depth change and characteristics of falling snow particles in Toyama

Relationships between snow depth change and characteristics of falling snow particles in Toyama

Controls on phase composition and ice water content in a convection-permitting model simulation of a tropical mesoscale convective system

Abstract. Simulations of tropical convection from an operational numerical weather prediction model are evaluated with the focus on the model's ability to simulate the observed high ice water contents associated with the outflow of deep convection and to investigate the modelled processes that control the phase composition of tropical convective clouds. The 1 km horizontal grid length model that uses a single-moment microphysics scheme simulates the intensification and decay of convective strength across the mesoscale convective system. However, deep convection is produced too early, the OLR (outgoing longwave radiation) is underestimated and the areas with reflectivities > 30 dBZ are overestimated due to too much rain above the freezing level, stronger updraughts and larger particle sizes in the model. The inclusion of a heterogeneous rain-freezing parameterisation and the use of different ice size distributions show better agreement with the observed reflectivity distributions; however, this simulation still produces a broader profile with many high-reflectivity outliers demonstrating the greater occurrence of convective cells in the simulations. Examining the phase composition shows that the amount of liquid and ice in the modelled convective updraughts is controlled by the following: the size of the ice particles, with larger particles growing more efficiently through riming and producing larger IWC (ice water content); the efficiency of the warm rain process, with greater cloud water contents being available to support larger ice growth rates; and exclusion or limitation of graupel growth, with more mass contained in slower falling snow particles resulting in an increase of in-cloud residence times and more efficient removal of LWC (liquid water content). In this simulated case using a 1 km grid length model, horizontal mass divergence in the mixed-phase regions of convective updraughts is most sensitive to the turbulence formulation. Greater mixing of environmental air into cloudy updraughts in the region of −30 to 0 °C produces more mass divergence indicative of greater entrainment, which generates a larger stratiform rain area. Above these levels in the purely ice region of the simulated updraughts, the convective updraught buoyancy is controlled by the ice particle sizes, demonstrating the importance of the microphysical processes on the convective dynamics in this simulated case study using a single-moment microphysics scheme. The single-moment microphysics scheme in the model is unable to simulate the observed reduction of mean mass-weighted ice diameter as the ice water content increases. The inability of the model to represent the observed variability of the ice size distribution would be improved with the use of a double-moment microphysics scheme.

Artificial Cloud Seeding Using Liquid Carbon Dioxide: Comparisons of Experimental Data and Numerical Analyses

AbstractAn artificial seeding experiment was carried out over the Genkai Sea, Japan, using liquid carbon dioxide. The seeded cloud was followed by an aircraft and radar at Kyushu University. A radar-echo intensity of 19 dBZ was formed in the seeded cloud where no radar echo was observed previously. The results of the experiment are analyzed using a numerical model [Weather Research and Forecasting Model (WRF), version 3.1] to evaluate the effects of the artificial seeding. The numerically simulated radar echo has a slightly stronger intensity and wider area than that observed. The results of the experiments were similar to those produced by the numerical model, however. Evaporation of cloud liquid water; growth of snow particles that is due to deposition, autoconversion, aggregation, and collection; and convection caused by released latent heat are shown in the numerical results as effects of the seeding experiment. The falling snow particles cause downward flow, which is compensated for by upward flow that causes the formation of new cloud liquid water as a secondary effect of seeding, although this secondary effect is confirmed only in the numerical results.

Dependence of drifting snow saltation lengths on snow surface hardness

Drifting snow experiments were conducted in a cold wind tunnel at a constant temperature of −15 °C to investigate saltation lengths of snow particles over loose and hard snow surfaces. Vertical mass flux of falling snow particles to the snow surface was measured by a box-type snow collector, which was composed of ten metallic boxes, set at the downwind end of the test section. Saltation lengths were calculated from the distributions of the falling mass flux along the snow collector. Mean saltation length over loose snow surfaces increased from 8 to 15 cm with increasing wind velocity from 6 to 15 m s −1. Mean saltation length over hard snow surfaces increased from 40 to 140 cm with increasing wind velocity from 5.5 to 8 m s −1. Mean saltation length over hard snow surfaces was several times as large as that over loose snow surfaces for the same wind velocity. Saltation length distributions were also obtained from analyses of the falling mass flux distributions. Saltation length distributions were shown as exponential functions of length in previous studies for loose snow surfaces. Present results showed that saltation length distributions over hard snow surfaces were well approximated by log-normal distributions.

Image processing of snow particles and classification into snowflakes and graupel

AbstractTo analyze the relationship between the radar reflectivity and the intensity of a snowfall, it is important to know the percentages of snowflakes and graupel in snow particles. This paper proposes an automatic method of classification of falling snow particles. The method consists of two CCD cameras which record each particle simultaneously with different shutter speeds and magnifications. The first CCD camera has a slow shutter speed (1/60 s) and a relatively wide view angle, and records the trailing image and diameter of each falling snow particle so that its fall velocity is obtained, and this camera also records the distribution of diameters of the snow particles. The second CCD camera has a higher shutter speed (1/8000 s) and a narrow view field (1/5 the first CCD camera), and records a binary image and a gray‐level image of each snow particle so that the shape parameter of each particle can be obtained. Each snow particle is classified as a snowflake or a graupel pellet by image processing based on the fall velocity and shape parameter. The proposed method has been successfully tested in snowfall (continuously for 2 weeks), obtaining the percentages of snowflakes and graupel once a minute in real time. © 2002 Scripta Technica, Syst Comp Jpn, 33(2): 43–53, 2002

Measuring the density of snow particles and snowfall rate

AbstractIt is important to measure the quality of falling snow particles as a help in analyzing radio attenuation during snowfalls. Since the quality of snow particles depends almost entirely on their density (the amount of water they contain), the snow particle density reflects their quality. to permit automatic measurement of the average densities of falling snow particles over long periods of time, the diameters and fall velocities of snow particles are measured by means of image processing. Simultaneously, the weight of all snow particles that have fallen to the ground was measured directly by means of an electronic balance. the density of the falling snow particles is calculated by dividing into this total weight the total volume of snow particles that passed through a unit volume (obtained from the diameter and velocity of snow particles). the diameters, velocities, and number of snow particles are determined by image processing. Snowfall rates calculated from the image processing data are compared with those measured directly and are found to agree.

Low brightness temperatures of Martian polar caps: CO2 clouds or low surface emissivity?

One of the major surprises from the spacecraft missions to Mars of the 1970s was the finding of anomalously low brightness temperatures in the winter polar regions, far below the expected CO2 frost point. Since then, many explanations have been advanced for this puzzling behavior, including the low emissivities of carbon dioxide frost and the presence of carbon dioxide clouds, but no conclusion has been reached. We have carefully analyzed the measurements obtained by the Mariner 9 infrared interferometer spectrometer (IRIS) and the Viking infrared thermal mapper (IRTM). Besides their low brightness temperatures, the anomalous areas are characterized by their high variability and their complex spectral signature. Also, there is evidence suggesting that their occurrence is related to the condensation of CO2 in the atmosphere. We have used a combination of data analysis and modeling to compare these observations with simulated spectra obtained with radiative models of CO2 ice clouds and CO2 ice deposits. We show that precipitating CO2 cloud with particle radius larger than 10 μm and CO2 snow deposits with millimeter‐sized grains are able to produce the observed features. In both cases, matching the IRIS spectra requires the CO2 ice particles to be mixed with small amounts of water or dust, as expected for the northern winter cap observed by the Mariner 9 mission. Nonprecipitating CO2 clouds, if they exist, should be transparent in the infrared. On the other hand, CO2 ice deposits composed of large grains or monolithic ice which have directly condensed on the ground could have an emissivity close to unity and in any case much higher than that of small CO2 ice particles originating from atmospheric condensation. We conclude that the low brightness temperatures are likely to be created by CO2 snow falls and that both falling snow particles and fresh snow deposits could contribute to create the observed features.

Oxygen isotopic variation of falling snow particles with time during the lifetime of a convective cloud: observation and modelling

Oxygen isotopic variation of falling snow particles with time during the lifetime of a convective cloud: observation and modelling

Oxygen isotopic variation of falling snow particles with time during the lifetime of a convective cloud: observation and modelling

The δ 18 O (per mille deviation from SMOW) of falling snow particles was observed at two stations 8 km apart along the trajectory of a convective cloud. The comparison of the difference in δ 18 O between the two stations with radar observation reveals the following: (1) the δ 18 O values of snow from a convective cloud decrease with time during its lifetime; the rate of decrease observed in 7 cases of convective radar echoes was 0.2%, to 3.1% during 15 min of movement of radar echoes between two stations, and was large during and after its maximum precipitation intensity; (2) the rate of decrease was large in cells in which precipitation intensity was large in the windward area. A one-dimensional time-dependent model is used to calculate the isotopic variation of falling snow during the lifetime of a convective cloud cell. The calculated results explain the observed results well. In addition, calculated results show that the rate of decrease of δ 18 O is large in cells with high precipitation efficiency, and in cells with large terminal velocity of precipitating particles. DOI: 10.1111/j.1600-0889.1989.tb00138.x

Relationship between δD and δ18O values of falling snow particles from a separate cloud

Relationship between δD and δ¹⁸O values of falling snow particles from a separate cloud

Relationship between δD and δ<sup>18</sup>O values of falling snow particles from a separate cloud

The relationship between δD and δ 18 O values (per mille deviation from SMOW) was investigated on falling snow particles from a separate convective cloud collected at 2 stations along a moving cloud trajectory. Observations were made in 1983 in Hokuriku, Japan and in 1985 and 1986 in Hokkaido, Japan. The δD and δ 18 O values of snow particles from a separate cloud were linearly related. The values of deuterium excess of observed δD-δ 18 0 lines were much greater than 10 and differed with each case, while the slope was 8.5-9.6 in 7 of 9 cases. Such observational results indicated that falling snow particles observed at both stations were produced in a cloud consisting of the air parcels containing initial water vapor having the same isotopic composition and that there was a possibility of kinetic effect in the sublimation process during growth of snow crystals. DOI: 10.1111/j.1600-0889.1988.tb00290.x

Short-term variation of oxygen isotopic composition of falling snow particles

Short-term variation of oxygen isotopic composition of falling snow particles

Short-term variation of oxygen isotopic composition of falling snow particles

Oxygen isotopic composition, crystal types and the degree of riming of falling snow particles were simultaneously observed in order to determine the possible causes of short-term variation of the δ l8 O value together with the formation process of snow in clouds. The results obtained are summarized as follows: (1) Whenever the type and/or degree or riming of snow crystals changed, the δI80 value of falling snow changed. (2) Short-term variation of the δ l8 O value in each case indicated that riming has two opposite effects on the δ l8 0 value of snow crystals, i.e., the δ l8 O value increased (or decreased) by riming. (3) There was good correlation between the maximum precipitation intensity and the range of variation in the δ l8 O value of snow particles from snow bands. (4) The short-term variations of the δ l8 O values are not correlated to the surface air temperature and the precipitation intensity. DOI: 10.1111/j.1600-0889.1986.tb00260.x

Effects of Precipitation on the Isotopic Composition of Falling Snow Particles

Observation on the isotopic composition of falling snow particles was carried out at two points 30 km apart in the coastal area of the Sea of Japan, between 20 January to 25 February 1983. Sampling periods of snow particles were from 10 minutes to several hours. Time variation of 6 hours running mean of δ18O values showed good correlation with the variation of surface air temperature. The δ18O value is maximal at the beginning of a snowfall, except when large graupels were observed at the beginning. Comparison of the results between the two observation points showed that the differences in the δ18O values are great when precipitation is plentiful and precipitation cells are small.

Effects of Precipitation on the Isotopic Composition of Falling Snow Particles

Observation on the isotopic composition of falling snow particles was carried out at two points 30 km apart in the coastal area of the Sea of Japan, between 20 January to 25 February 1983. Sampling periods of snow particles were from 10 minutes to several hours. Time variation of 6 hours running mean of δ18O values showed good correlation with the variation of surface air temperature. The δ18O value is maximal at the beginning of a snowfall, except when large graupels were observed at the beginning. Comparison of the results between the two observation points showed that the differences in the δ18O values are great when precipitation is plentiful and precipitation cells are small.

降雪粒子の空間密度変動よりみた降雪cellの確率論的解析佐粧純男・徳植弘

Photographic observations were carried out on the spatial concentration of falling snow particles. Photographs were taken by 8 mm cine camera at the rate of 16 frames a minute. The main results are described as follows :1) The frequency of each concentration which is classified by 10-particle difference, was obtained in the shower and continuous types of snowfall. The distribution curve of frequency may be explained from a general compound Poisson's distribution in the case of shower, while it is represented approximately as a Gaussian distribution in the cese of continuous one.2) In the case of snow shower, the probability density function of cells that their average spatial concentration lies between λ and λ+dλ was obtained, where λ is the concen-tration averaged on each cell. It may be thought that the probability distribution function consists of two curves : one of them has a steeper and larger maximum value than the other one, which may be thought Gaussian distribution in form, at low concentration. This result illustrates that the former corresponds to the distribution curve of original cells and the latter is due to snow particles blown down from neighbouring trees and roofs of huts.3) Auto-correlations were calculated from the fluctuation of spatial concentration in both cases.

THE ELECTRIFICATION OF ANTENNAE BY SHOW AND RAIN FALLS

It was observed that antennae were electrified during heavy snowfalls and that their potential reached several thousand volts at Mt. Teine. The electrification of the antennae was also observed during rainfalls at Sapporo. From further observations and experiments, it was concluded that the falling snow particles or rain drops play the of an ion collector.

The Electrification of Antennae by Snow and Rain Falls

Abstract It was observed that antennae were electrified during heavy snowfalls and that their potential reached several thousand volts at Mt. Teine. The electrification of the antennae was also observed during rainfalls at Sapporo. From further observations and experiments, it was concluded that the falling snow particles or rain drops play the of an ion collector.