Search Results (32)

Pillar-to-pillar dashboards have become common in modern electric vehicles. These dashboards are made of liquid crystal displays (LCDs), of which backlight units (BLUs) are an integral part. Particulate contamination inside BLUs can lead to either an aesthetic or functional failure and is in consequence a part of quality control. Automatic optical inspection (AOI) was used to detect particulate matter to enable a process chain analysis to be carried out. The investigation showed that a high percentage of all contaminants originated from the assembly of the edge/side lightguide. The implementation of an additional cleaning process was the favored countermeasure to reduce the contaminants. The objective (cleanliness requirement) was to remove all contaminants larger than 100 µm from the lightguide with contactless (non-destructive) cleaning methods. The preferred cleaning methods of choice were compressed air and CO₂ snow jet cleaning. This work investigates the cleaning efficacy of both cleaning methods under consideration of the following impact factors: distance, orientation (inclination) and speed. The central question of this paper was as follows: would cleaning with compressed air be sufficient to meet the cleanliness requirements? In order to answer this question, a cleaning validation was carried out, based on a Box–Behnken design of experiments (DoE). To do so, representative test contaminants had to be selected in step one, followed by the selection of an appropriate measurement technology to be able to count the contaminants on the lightguide. In the third step, a test rig had to be designed and built to finally carry out the experiments. The data revealed that CO₂ was able to achieve a cleaning efficacy of 100% in five of the experiments, while the best cleaning efficacy of compressed air was 89.87%. The cleaning efficacy of compressed air could be improved by a parameter optimization to 94.19%. In contrast, a 100% cleaning efficacy is achievable with CO₂ after parameter optimization, which is what is needed to meet the cleanliness requirements. Full article

Ice is a common natural phenomenon in cold areas, which plays an important role in the construction of cold areas and the design of artificial ice rinks. To supplement our knowledge of ice mechanics, this paper investigates the mechanical properties of granular snow ice. The factors influencing the flexural strength of granular snow ice are analyzed through a three-point bending test. It is found that flexural strength is affected by strain rate. At low strain rates, flexural strength increases with increasing strain rate, whereas at high strain rates, flexural strength decreases with increasing strain rate. As temperature decreases, the flexural strength value of ice increases, but its brittleness becomes more pronounced, indicating that the strain rate corresponding to the maximum flexural strength is lower. Within the test temperature range, the tough-brittle transition range is from 6.67 × 10⁻⁵ s⁻¹ to 3.11 × 10⁻⁴ s⁻¹. At −5 °C, the strain rate corresponding to the maximum bending strength is 3.11 × 10⁻⁴ s⁻¹, while at −10 °C, it is only 6.67 × 10⁻⁵ s⁻¹. Flexural strength is influenced by crystal structure. At −20 °C, the average flexural strength of granular snow ice is 2.85 MPa, compared to 1.93 MPa for columnar ice at the same temperature. Through observation, we found that there are straight cracks and oblique cracks. The fracture toughness of granular snow ice was investigated by cutting prefabricated cracks at the bottom of the ice beam and employing a three-point bending device. It is found that fracture toughness decreases with increasing strain rate. Temperature also affects granular snow ice. At −15 °C, fracture toughness is 181.60 kPa·m^1/2, but at −6 °C, it decreases to 147.28 kPa·m^1/2. However, at varying temperatures and strain rates, there is no significant difference in the fracture patterns of ice samples, which predominantly develop upward along the prefabricated cracks. Full article

In their natural state, snow crystals are influenced by the atmosphere during formation and multiple factors after landing, resulting in varying particle sizes and unstable particle morphologies that are challenging to quantify. The current research mainly focuses on the relationship between the porosity of compacted snow samples or qualitatively describes snow crystals and their macroscopic physical properties, ignoring that the significant differences in the morphology of snow crystals also affect their physical properties. To quantitatively evaluate the morphology of snow crystals, we employed optical microscopy to obtain digital images of snow crystals in Harbin, utilizing the Sobel and Otsu algorithms to determine the equivalent particle size and fractal dimension of individual snow particles. In addition, the hardness of snow with a density of 0.4 g/cm³ was measured through a penetration test, with an analysis of its correlation relative to particle size and fractal dimension. The results indicated the fractal dimension as an effective parameter for characterizing particle shape, which decreased rapidly over time and then fluctuated within the range of 1.10 to 1.15. During the initial period, natural snow crystals broke down rapidly, leading to an increase in the percentage of natural snow crystals with an equivalent particle size of 0.2–0.4 mm up to 51.86%. After three days, the sintering effect between snow crystals was enhanced, resulting in an even distribution of the equivalent particle size. Finally, multiple linear regression analysis showed a positive correlation between compacted snow hardness and fractal dimension, with a negative correlation between compacted snow hardness and equivalent particle size. These findings offer valuable technical support and data reference for exploring the relationship between snow’s mechanical properties and its microscopic particle shape. Full article

To study the snow microstructure at various metamorphism times and extract the snow neck area, a constant density (200 kg/m³) snow metamorphism experiment was conducted. The findings show that the neck region is mostly influenced by temperature, sun radiation, snow density and specific humidity, with wind speed having little effect. Additionally, we developed a multiple linear regression equation for the neck area under atmospheric forcing: “S = 288T + 2E + 189ρ + 12,194V − 20,443RH − 42,729”. This equation accounts for solar radiation (E), temperature (T), snow density (ρ), specific humidity (RH) and wind speed (V). Notably, the above five factors can account for 84% of the factors affecting the neck area, making it a crucial factor. The relationship between snow hardness and neck area is correlated at 71%, and in later stages of metamorphism, the correlation may increase to 91%. Based on the neck area, the following hardness value prediction is made: “H = 0.002764S + 67.922837”. This study documents the growth variations in the neck region of the metamorphic snow cover and elucidates the process by which outside factors impact the microstructure and macroscopic physical characteristics of the snow cover. Full article

For artificial snowfall, snow particle size can have a direct impact on snow quality. The operating conditions of the snow-makers and environmental factors will influence the atomization and crystallization processes of artificial snow making, which consequently affect snow particle size. This paper investigates the size distribution of snow particles during artificial snow making under different operating conditions and environmental parameters. For this purpose, an environmental chamber is designed and structured. The laser scattering method was used to measure the size distribution of snow under different parameters in the room. The results show that the distribution of snow crystal particle size aligns closely with the Rosin–Rammler (R-R) distribution. The higher the height of the snowfall, the longer the snow crystals grow and the larger the snow crystal particle size. It has been found that a higher air pressure favors atomization, while the opposite is true for water pressure, which results in a higher air–water pressure ratio, producing smaller snow particle sizes. Additionally, an ambient temperature in the range of −5 °C to −15 °C contributes to the snow crystal form transforming from plates to columns and then back to plates; the snow particle size first decreases and then increases. Snow crystal particles at −10 °C have the smallest size. Outdoor snow-makers should be operated at the highest possible air–water pressure ratio and snow height, and at a suitable ambient temperature. Full article

This study selected three heavy-rainfall events of different types in Taiwan’s Mei-yu season for high-resolution simulations at a grid size of 1 km and assessed the model’s capability to reproduce their morphology and characteristics. The three cases include a pre-frontal squall line, a mesoscale convective system (MCS) embedded in southwesterly flow, and a local convection near the front in southern Taiwan during the South-West Monsoon Experiment (SoWMEX) in 2008, chosen mainly because of the availability of the S-band polarimetric (S-Pol) radar observations, and especially the particle identification results. The simulations using the Cloud-Resolving Storm Simulator (CReSS) could reproduce all three corresponding rainfall systems at roughly the correct time and location, including their kinematic structures such as system-relative flows with minor differences, although the cells appeared to be coarser and wider than the S-Pol observations. The double-moment cold-rain microphysics scheme of the model could also capture the general distributions of hydrometeors, such as heavy rainfall below the updraft core with lighter rainfall farther away below the melting level, and graupel and mixed-phase particles in the upper part of the updraft with snow and ice crystals in stratiform areas between updrafts above the melting level. Near the melting level, the coexistence of rain and snow corresponds to wet snow in the observations. Differences in cloud characteristics in the events are also reflected in the model results to some extent. Overall, the model’s performance in the simulation of hydrometeors exhibits good agreement with the observation and appears reasonable. Full article

Aircraft cloud seeding refers to the use of equipment on aircraft to release chemicals into clouds, changing their physical and chemical properties to increase rainfall or snowfall. The purpose of precipitation enhancement is to alleviate drought and water scarcity issues. Due to the complexity of the technology, the precise control of factors such as cloud characteristics and chemical release amounts is necessary. Therefore, a scientific evaluation of the potential of aircraft cloud seeding can help to improve the effectiveness of the process, and is currently a technical challenge in weather modification. This study used the mesoscale numerical model WRF coupled with a catalytic process to simulate and evaluate the seven aircraft cloud seeding operations conducted in Hunan Province in 2021. The results show that WRF can effectively evaluate the effectiveness of cloud seeding. When the water vapor conditions are suitable, the airborne dispersion of silver iodide (AgI) can significantly increase the content of large particles of high-altitude ice crystals, snow, and graupel, resulting in an increase in low-level rainwater content and, correspondingly, an increase in ground precipitation. When the water vapor conditions are insufficient, the dispersion of AgI does not trigger effective precipitation, consistent with the results of station observations and actual flight evaluations. This study provides an effective method for scientifically evaluating the potential and effectiveness of aircraft cloud seeding operations. Full article

Based on the Morrison Two-Moment Scheme coupled with the non-inductive electrification mechanism and the discharge parameterization scheme in the Weather Research and Forecasting (WRF) model, a thunderstorm process was simulated by using the WRF electrical coupling model in Sichuan Basin on 21 July 2019, in this paper. Through analysis and discussion of the macroscopic and microscopic characteristics of the thunderstorm activity and the microphysical and dynamic processes, respectively, the study shows that the simulation results of radar echo and lightning are well consistent with the meteorological observation which indicates the WRF model has a certain ability to reproduce the thunderstorm process in Sichuan Basin, there is a good correspondence between the main electrification area and the distribution position of the ice-phase particles in the thunderstorm. The simulated charge structure of the thunderstorm is that the graupel particles are mainly negatively charged, the ice crystals and snow particles are mainly positively charged, and the thunderstorm shows a dipole charge structure with an upper positive charge center and a lower negative charge center. It also shows that the updrafts greatly influence ice-graupel and snow-graupel collisions during the thunderstorm discharge process, the higher the updraft speed, the stronger the electrical activity, and, especially, the stronger the discharge process of ice-particle collisions and separation. Full article

Aerosol concentration, size and composition are fundamental in hydrometeor formation processes. Meteorological models often use prescribed aerosol concentrations and a single substance. In this study, we analyze the role of aerosol concentration, acting both as CCN and IN, in the development of precipitation in a mixed phase system in numerical weather simulations. To this end, Storm Filomena was selected as the case study. In such a mixed-phase system, the coexistence of supercooled water with ice crystals, as well as the particular existence of a thermal inversion, led to the formation of precipitation in the form of rain, snow and graupel. Several high resolution experiments varying the fixed background aerosol concentration as well as a simulation with an interactive aerosol calculation were performed by means of the WRF-Chem model, using the same physics suite, domain and driving conditions. Results show that the total precipitation remains basically unaltered, with maximum changes of 5%; however, the production of snow is heavily modified. The simulation with maximum prescribed aerosol concentration produced 27% more snow than the interactive aerosol simulation, and diminished the graupel (74%) and rain production (28%). This redistribution of precipitation is mainly linked to the fact that under fixed ice crystal population the variation of aerosol concentration translates into changes in the liquid water content and droplet size and number concentration, thus altering the efficiency of precipitation production. In addition, while modifying the prescribed aerosol concentration produces the same precipitation pattern with the concentration modulating the precipitation amount, interactive aerosol calculation leads to a different precipitation pattern due to the spatial and temporal variability induced in the dynamical aerosol distribution. Full article

New observations of anomalously high cloud ice crystal concentrations at the Jungfraujoch research station (Switzerland, 3.5 km a.s.l.) are presented. High-resolution measurements of these ice crystals using a high-speed 2D imaging cloud particle spectrometer confirm that the concentrations far exceed those expected from any known primary ice production mechanisms and are at temperatures well below those for known secondary ice production processes to contribute. The most likely explanation is due to a strong surface source generated by the interaction of turbulent deposition of supercooled droplets to fragile ice-covered snow surfaces. This process enhances the detachment of crystal fragments wherein the smaller size mode is turbulently re-suspended even at low wind speeds below expected blowing snow thresholds. These then continue to grow, adding significantly to the ice crystal number concentrations whose size and habit is determined by the transport time between the ice crystal source and measurement location and liquid water profile within the cloud. We confirm, using eddy covariance measurements of ice particle number fluxes, that the likely source is significantly far upwind to preclude flow distortion effects such that the source plume has homogenised by the time they are measured at the mountain top summit. Full article

This paper explores the potential of ground-penetrating radar (GPR) monitoring for an advanced understanding of snow cover processes and structure. For this purpose, the study uses the Hansbreen (SW Spitsbergen) records that are among the longest and the most comprehensive snow-cover GPR monitoring records available on Svalbard. While snow depth (HS) is frequently the only feature derived from high-frequency radio-echo sounding (RES), this study also offers an analysis of the physical characteristics (grain shape, size, hardness, and density) of the snow cover structure. We demonstrate that, based on GPR data (800 MHz) and a single snow pit, it is possible to extrapolate the detailed features of snow cover to the accumulation area. Field studies (snow pits and RES) were conducted at the end of selected accumulation seasons in the period 2008–2019, under dry snow conditions and HS close to the maximum. The paper shows that although the snow cover structure varies in space and from season to season, a single snow pit site can represent the entire center line of the accumulation zone. Numerous hard layers (HLs) (up to 30% of the snow column) were observed that reflect progressive climate change, but there is no trend in quantity, thickness, or percentage contribution in total snow depth in the study period. HLs with strong crystal bonds create a “framework” in the snowpack, which reduces compaction and, consequently, the ice formation layers slow down the rate of snowpack metamorphosis. The extrapolation of snow pit data through radar profiling is a novel solution that can improve spatial recognition of snow cover characteristics and the accuracy of calculation of snow water equivalent (SWE). Full article

Aerosols, through cloud condensation nuclei (CCN) or ice nuclei (IN), affect cloud microphysics. With increasing concentrations of aerosols, it is important to consider the impact of IN along with CCN on clouds and precipitation in numerical simulations; further, aerosols may also affect the weather-modification seeding effect. On the basis of the observation of natural IN concentration and cloud-drop number concentrations, numerical sensitivity experiments for a snowfall case were designed to study the effects of parameters of IN and cloud number concentrations at the cloud base to consider the CCN effects on clouds and precipitation as well as weather-modification seeding effects. Generally, with smaller cloud-drop number concentration, the mass contents were much lower. With more ice nuclei, more ice crystals were able to nucleate, and additional snow particles were generated through ice crystals. Cloud-drop number concentrations heavily affected the location and amount of snowfall. During the 1e9 test, 2.4 mm was the highest reduction in the amount of snowfall; additionally, the amount of snowfall from the combined impacts of increased IN and cloud-drop number decreased in wide areas, and its maximum precipitation reduction exceeded 2.7 mm as well as up to 15% of the daily amount of snowfall. More IN reduced the artificial seeding effect, lowered the increase in snowfall in the center of the seeding, and lowered the reduction of snowfall in the reduction center of the seeding. With more IN, the seeding effect was able to shift approximately 0.6% from the 3.9% seeding effect of the control simulation. Full article

Based on the concept of band topology in phonon dispersion, we designed a topological phononic crystal in a thin plate for developing an efficient elastic waveguide. Despite that various topological phononic structures have been actively proposed, a quantitative design strategy of the phononic band and its robustness assessment in an elastic regime are still missing, hampering the realization of topological acoustic devices. We adopted a snowflake-like structure for the crystal unit cell and determined the optimal structure that exhibited the topological phase transition of the planar phononic crystal by changing the unit cell structure. The bandgap width could be adjusted by varying the length of the snow-side branch, and a topological phase transition occurred in the unit cell structure with threefold rotational symmetry. Elastic waveguides based on edge modes appearing at interfaces between crystals with different band topologies were designed, and their transmission efficiencies were evaluated numerically and experimentally. The results demonstrate the robustness of the elastic wave propagation in thin plates. Moreover, we experimentally estimated the backscattering length, which measures the robustness of the topologically protected propagating states against structural inhomogeneities. The results quantitatively indicated that degradation of the immunization against the backscattering occurs predominantly at the corners in the waveguides, indicating that the edge mode observed is a relatively weak topological state. Full article

The theoretical studies on the flow fields around falling cloud and precipitation particles are briefly reviewed. The hydrodynamics of these particles, collectively called hydrometeors, are of central importance to cloud development and dissipation, which impact both the short-term weather and long-term climate processes. This review focuses on the solutions of the appropriate Navier–Stokes equations around the falling hydrometeor, particularly those obtained by numerical methods. The hydrometeors reviewed here include cloud drops, raindrops, cloud ice crystals, snow aggregates, conical graupel, and smooth and lobed hailstones. The review is made largely in chronological order so that readers can obtain a sense of how the research in this field has progressed over time. Although this review focuses on theoretical studies, brief summaries of laboratory experiments and field observations on this subject are also provided so as to substantiate the calculation results. An outlook is given at the end to describe future works necessary to improve our knowledge in this area. Full article

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development. Full article