Fall Speed Research Articles

Simulated particle evolution within a winter storm: contributions of riming to radar moments and precipitation fallout

Abstract. Remote sensing radars from airborne and spaceborne platforms provide critical observations of clouds to estimate precipitation rates across the globe. The ability of these radars to detect changes in precipitation properties is advanced by Doppler measurements of particle fall speed. Within mixed-phase clouds, precipitation mass and its fall characteristics are especially sensitive to the effects of riming. In this study, we quantified these effects and investigated the distinction of riming from aggregation in Doppler radar vertical profiles using quasi-idealized particle-based model simulations. Observational constraints of a control simulation were determined from airborne in situ and remote sensing measurements collected during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) for a wintry–mixed precipitation event over the northeastern United States on 4 February 2022. From the upper boundary of a one-dimensional column, particle evolution was simulated through vapor deposition, aggregation, and riming processes, producing realistic Doppler radar profiles. Despite a modest observed amount of supercooled liquid water (0.05 g m−3), riming accounted for 55 % of the ice-phase precipitation mass, cumulatively increasing reflectivity by 44 % and Doppler velocity by 68 %. Independent evaluation of process-based sensitivities showed that, while radar reflectivity is comparably sensitive to either riming- or aggregation-based particle morphology, the Doppler velocity profile is uniquely sensitive to particle density changes during riming. Thus, Doppler velocity profiles advance the diagnosis of riming as a dominant microphysical process in stratiform clouds from single-wavelength radars, which has implications for quantitative constraints of particle properties in remote sensing applications.

Turbulence effect on disk settling dynamics

Turbulence can have a strong effect on the fall speed of snowflakes and ice crystals. In this experimental study, the behaviour of thin disks falling in homogeneous turbulence is investigated, in a range of parameters relevant to plate crystals. Disks ranging in diameter from 0.3 to 3 mm, and in Reynolds number $Re = 10\unicode{x2013}435$ , are dispersed in two air turbulence levels, with velocity fluctuations comparable to the terminal velocity. For each case, thousands of trajectories are captured and reconstructed by high-speed laser imaging, allowing for statistical analysis of the translational and rotational dynamics. Air turbulence reduces the disk terminal velocities by up to 35 %, with the largest diameters influenced most significantly, which is primarily attributed to drag nonlinearity. This is evidenced by large lateral excursions of the trajectories, which correlate with cross-flow-induced drag enhancement as reported previously for falling spheres and rising bubbles. As the turbulence intensity is increased, flat-falling behaviour is progressively eliminated and tumbling becomes prevalent. The rotation rates of the tumbling disks, however, remain similar to those displayed in still air. This is due to their large moment of inertia compared to the surrounding fluid, in stark contrast with studies conducted in water. In fact, the observed reduction of settling velocity is opposite to previous findings on disks falling in turbulent water. This emphasizes the importance of the solid-to-fluid density ratio in analogous experiments that aim to mimic the behaviour of frozen hydrometeors.

Thermodynamical impacts on the boundary layer imbalance during secondary eyewall formation

It is well realized that the planetary boundary layer (PBL) imbalance is essential for the secondary eyewall formation (SEF) in tropical cyclones (TCs). The purpose of this study is to investigate the thermodynamic processes in inducing the PBL imbalance. While the control run in an idealized simulation is capable of generating the SEF, simulations with varying fall speeds of raindrops (FSR) in the microphysics resulted in different outcomes for the formation of SEF. The SEF occurs only within a specific range of FSR relative to its default formulation in the model.The gradient wind equation in the PBL is used to diagnose the imbalance leading to SEF. In the case with a formation of SEF, a substantial downdraft induced by TC outer rainbands is observed, leading to positive agradient force (AF). Such downdraft favors the formation of a moat region. Furthermore, the adiabatic warming induced by the downdrafts also modifies the temperature field and the radial gradient of pressure field, contributing to the PBL imbalance. While previous studies have emphasized the importance of the broadening of tangential wind as a trigger for positive AF, our results highlight the importance of the local pressure gradient imbalance within the PBL.

Design and application of high-precision calibration blackbody for space optical remote sensing sensor

Radiation calibration is a crucial step in producing high-quality images for spaceborne infrared cameras. Blackbody radiation sources, as the standard equipment for infrared thermometers, play an increasingly important role in radiation calibration. But as the camera aperture increases, blackbody faces challenges such as poor temperature uniformity, slow heating and cooling rates, large mass, and large volume. This article proposes a design scheme for spaceborne calibration blackbody based on a combination of rope pull fixation and limit block positioning. The temperature uniformity, temperature stability, temperature rise and fall rate, thermal stress characteristics, and anti-emission vibration characteristics of the blackbody under this scheme are analyzed and optimized in detail. The analysis results show that the conduction thermal resistance between the blackbody and the environment is nearly two orders of magnitude higher than that of the conventional scheme. The blackbody has excellent temperature uniformity, temperature stability, wide calibration temperature range, light weight, small volume, and fast temperature rise and fall speed. The blackbody scheme with a thickness of only 1.5 mm was implemented and applied on orbit.

The dynamics of impinging plumes from a moving source

We present the results from a series of experiments investigating the dynamics of gravity currents which form when a dense saline or particle-laden plume issuing from a moving source interacts with a horizontal surface. We define the dimensionless parameter $P$ as the ratio of the source speed, $u_a$ , to the buoyancy speed, $(B_0/z_0)^{1/3}$ , where $B_0$ and $z_0$ are the source buoyancy flux and height above the horizontal surface, respectively. Using our experimental data, we determine that the limiting case in which $P=P_c$ the gravity current only spreads downstream of the initial impact point occurs when $P_c=0.83\pm 0.02$ . For $P< P_c$ , from our experiments we observe that the plume forms a gravity current that spreads out in all directions from the point of impact and the propagation of the gravity current is analogous to a classical constant-flux gravity current. For $P>P_c$ , we observe that the descending plume is bent over and develops a pair of counter-rotating line vortices along the axis of the plume. The ensuing gravity current spreads out downstream of the source, normal to the motion of the source. Analogous processes occur with particle-laden plumes, but there is a second dimensionless parameter $S$ , the ratio of the particle fall speed, $v_s$ , to the vertical speed of a plume in a crossflow, $(B_0/u_a z_0)^{1/2}$ . For $S\ll 1$ , particles remain well mixed in the plume and a particle-driven gravity current develops. For $S\gg 1$ , particles separate from the plume prior to impacting the boundary which leads to a fall deposit and no gravity current. We discuss these results in the context of deep-sea mining.

Measuring Ice Pellets and Refrozen Wet Snow Using a Laser-Optical Disdrometer

Abstract This study aims to characterize the shapes and fall speeds of ice pellets formed in various atmospheric conditions and to investigate the possibility to use a laser-optical disdrometer to distinguish between ice pellets and other types of precipitation. To do so, four ice pellet events were documented using manual observations, macrophotography, and laser-optical disdrometer data. First, various ice pellet fall speeds and shapes, including spherical, bulged, fractured, and irregular particles, were associated with distinct atmospheric conditions. A higher fraction of bulged and fractured ice pellets was observed when solid precipitation was completely melted aloft while more irregular particles were observed during partial melting. These characteristics affected the diameter–fall speed relations measured. Second, the measurements of particles’ fall speed and diameter show that ice pellets could be differentiated from rain or freezing rain. Ice pellets larger than 1.5 mm tend to fall > 0.5 m s−1 slower than raindrops of the same size. In addition, the fall speed of a small fraction of ice pellets was < 2 m s−1 regardless of their size, as compared with a fall speed > 3 m s−1 for ice pellets with diameter > 1.5 mm. Video analysis suggests that these slower particles could be ice pellets passing through the laser-optical disdrometer after colliding with the head of the instrument. Overall, these findings contribute to a better understanding of the microphysics of ice pellets and their measurement using a laser-optical disdrometer. Significance Statement Ice pellets are challenging to forecast and to detect automatically. In this study, we documented the fall speed and physical characteristics of ice pellets during various atmospheric conditions using a combination of a laser-optical disdrometer, manual observations, and macrophotography images. Relationships were found between the shape and fall speed of ice pellets. These findings could be used to refine the parameterization of ice pellets in atmospheric models and, consequently, improve the forecast of impactful winter precipitation types such as freezing rain. Furthermore, they will also help to physically interpret laser-optical disdrometer data during ice pellets and freezing rain.

Vegetation reconstruction based on a modelling approach applied to Holocene pollen records from Lakes Ladoga and Onega

Quantitative reconstruction of vegetation abundance utilising pollen records from Lake Ladoga, Lake Onega, and Lake Lembolovskoye in north-western Russia was conducted using the REVEALS model. Two modelling approaches, integrated with three sets of relative pollen productivities and fall speeds, produced divergent outcomes. The option that most accurately reflected the vegetation composition was selected for further analysis. The comparison of modern vegetation with sub-recent spectra from surface samples in the study region enabled an evaluation of the reliability of the model.

Effects of Riming on Ice‐Phase Precipitation Growth and Transport Over an Orographic Barrier

AbstractThe evolution of ice‐phase particles within precipitating clouds depends on the environmental properties of the cloud and on physical characteristics of the particles themselves, which can be modified by airflow over steep terrain. Through employing a unique Lagrangian particle‐based precipitation model, this study investigates the sensitivities in ice‐phase particle growth and transport due to variabilities in riming processes over an orographic barrier. This analysis is applied to two wintertime stratiform cyclones sampled by in situ aircraft over windward slopes during the Olympic Mountains Experiment. For both events, we simulate the ice‐phase particle evolution and trajectory within a two‐dimensional prescribed state representative of median observed cloud properties. Sensitivity simulations were constructed based on observed variabilities in supercooled liquid water (SLW) properties and its vertical extent above the melting level. Perturbations of SLW concentration equivalent to the 85th and 15th percentiles of observed values, which typically amounted to a change of less than 0.05 g m−3, resulted in respective increases or decreases in the ice‐phase contribution to surface precipitation mass by as much as 50% and horizontal particle trajectories differences exceeding 10 km. Similar sensitivities were found in response to varying the vertical extent of SLW above the melting level and to adjustments in mean SLW droplet size. The significant precipitation response to small variations in cloud properties principally arises from changing rates of rime mass accumulation and correspondingly, increases in particle fall speed. Considerations for the numerical representation of the riming process and its complex effects on precipitation are discussed.

Pengenalan Mengenai Gerak Vertikal Kebawah dengan Mengamati Media Mainan Terjun Payung

Vertical downward motion is a phenomenon in physics that occurs when an object falls freely under the influence of gravity without any external force affecting it. In this article, we will look at how vertical downward motion can be observed through the use of skydiving toys. Parachuting toys are used as a safe simulation to observe vertical downward motion. This research uses a descriptive qualitative approach. This approach explains in detail the subject of vertical downward movement through parachuting. The purpose of this article is to introduce an example of vertical downward motion for elementary school children. With this article in order to introduce and invite children to play and know that what is played is an example of vertical downward motion. These toys are often designed with designs and materials that allow the opening or slowing of the fall speed. This ensures that skydiving toys are safer for children to play with. Through observing skydiving toys, we can understand the basic concepts of vertical downward motion and its characteristics such as constant acceleration, terminal velocity, and the design and material factors that affect it. In conclusion, this article shows the importance of vertical downward motion in physics and how skydiving toys can be used to observe this phenomenon.

A universal scaling law for Lagrangian snowflake accelerations in atmospheric turbulence

We use a novel experimental setup to obtain the vertical velocity and acceleration statistics of snowflakes settling in atmospheric surface-layer turbulence, for Taylor microscale Reynolds numbers (Reλ) between 400 and 67 000, Stokes numbers (St) between 0.12 and 3.50, and a broad range of snowflake habits. Despite the complexity of snowflake structures and the non-uniform nature of the turbulence, we find that mean snowflake acceleration distributions can be uniquely determined from the value of St. Ensemble-averaged snowflake root mean square (rms) accelerations scale nearly linearly with St. Normalized by the rms value, the acceleration distribution is nearly exponential, with a scaling factor for the (exponent) of −3/2 that is independent of Reλ and St; kurtosis scales with Reλ, albeit weakly compared to fluid tracers in turbulence; gravitational drift with sweeping is observed for St < 1. Surprisingly, the same exponential distribution describes a pseudo-acceleration calculated from fluctuations of snowflake terminal fall speed in still air. This equivalence suggests an underlying connection between how turbulence determines the trajectories of particles and the microphysics determining the evolution of their shapes and sizes.

Effect of two-way coupling on clustering and settling of heavy particles in homogeneous turbulence

When inertial particles are dispersed in a turbulent flow at sufficiently high concentrations, the continuous and dispersed phases are two-way coupled. Here, we show via laboratory measurements how, as the suspended particles modify the turbulence, their behaviour is also profoundly changed. In particular, we investigate the spatial distribution and motion of sub-Kolmogorov particles falling in homogeneous air turbulence. We focus on the regime considered in Hassaini & Coletti (J. Fluid Mech., vol. 949, 2022, A30), where the turbulent kinetic energy and dissipation rate were found to increase as the particle volume fraction increases from $10^{-6}$ to $5\times 10^{-5}$ . This leads to strong intensification of the clustering, encompassing a larger fraction of the particles and over a wider range of scales. The settling rate is approximately doubled over the considered range of concentrations, with particles in large clusters falling even faster. The settling enhancement is due in comparable measure to the predominantly downward fluid velocity at the particle location (attributed to the collective drag effect) and to the larger slip velocity between the particles and the fluid. With increasing loading, the particles become less able to respond to the fluid fluctuations, and the random uncorrelated component of their motion grows. Taken together, the results indicate that the concentrated particles possess an effectively higher Stokes number, which is a consequence of the amplified dissipation induced by two-way coupling. The larger relative velocities and accelerations due to the increased fall speed may have far-reaching consequences for the inter-particle collision probability.

Characteristic analysis of a controlled-clearance piston-cylinder assembly up to 1500 MPa using a finite element method

We utilized numerical methods to analyze the characteristics of the piston-cylinder assembly of a controlled-clearance piston gauge. The piston gauge was able to measure liquid pressure from 100 MPa to 1500 MPa with the relative expanded uncertainty of 0.02% (k = 3). We established a finite element model to solve the stress and strain of the structural problem. The effective areas were calculated based on Dadson’s formula using the converged solutions of the clearance and the pressure distribution within the distorted piston-cylinder engagement gap that were iteratively determined by the finite element model and a fluid mechanics model with pressure-dependent fluid’s properties. Results were compared to the effective areas calculated by the modified Heydemann–Welch model based on experimental data, and the relative differences were less than 0.02%. We found sharp declines of the clearance and pressure distribution near the exit of the piston-cylinder engagement gap, which may lead to wearing during long-time operation at high pressures. Numerical results indicated non-linear relationship between jacket pressure and the cubic root of piston fall speed, which was traditionally considered as linear. The stall jacket pressure obtained by cubic (instead of linear) fitting extrapolation was found more close to the ones determined directly by the finite element model. Numerical results also found non-linear relationships among jacket pressure, measuring pressure, jacket pressure distortion coefficient.

ARMing the Edge: Designing Edge Computing–Capable Machine Learning Algorithms to Target ARM Doppler Lidar Processing

Abstract There is a need for long-term observations of cloud and precipitation fall speeds in validating and improving rainfall forecasts from climate models. To this end, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) site at Lamont, Oklahoma, hosts five ARM Doppler lidars that can measure cloud and aerosol properties. In particular, the ARM Doppler lidars record Doppler spectra that contain information about the fall speeds of cloud and precipitation particles. However, due to bandwidth and storage constraints, the Doppler spectra are not routinely stored. This calls for the automation of cloud and rain detection in ARM Doppler lidar data so that the spectral data in clouds can be selectively saved and further analyzed. During the ARMing the Edge field experiment, a Waggle node capable of performing machine learning applications in situ was deployed at the ARM SGP site for this purpose. In this paper, we develop and test four algorithms for the Waggle node to automatically classify ARM Doppler lidar data. We demonstrate that supervised learning using a ResNet50-based classifier will classify 97.6% of the clear-air images and 94.7% of cloudy images correctly, outperforming traditional peak detection methods. We also show that a convolutional autoencoder paired with k-means clustering identifies 10 clusters in the ARM Doppler lidar data. Three clusters correspond to mostly clear conditions with scattered high clouds, and seven others correspond to cloudy conditions with varying cloud-base heights.

Simple Analytical Expressions for Steady-State Vapor Growth and Collision–Coalescence Particle Size Distribution Parameter Profiles

Abstract This study derives simple analytical expressions for the theoretical height profiles of particle number concentrations (Nt) and mean volume diameters (Dm) during the steady-state balance of vapor growth and collision–coalescence with sedimentation. These equations are general for both rain and snow gamma size distributions with size-dependent power-law functions that dictate particle fall speeds and masses. For collision–coalescence only, Nt (Dm) decreases (increases) as an exponential function of the radar reflectivity difference between two height layers. For vapor deposition only, Dm increases as a generalized power law of this reflectivity difference. Simultaneous vapor deposition and collision–coalescence under steady-state conditions with conservation of number, mass, and reflectivity fluxes lead to a coupled set of first-order, nonlinear ordinary differential equations for Nt and Dm. The solutions to these coupled equations are generalized power-law functions of height z for Dm(z) and Nt(z) whereby each variable is related to one another with an exponent that is independent of collision–coalescence efficiency. Compared to observed profiles derived from descending in situ aircraft Lagrangian spiral profiles from the CRYSTAL-FACE field campaign, these analytical solutions can on average capture the height profiles of Nt and Dm within 8% and 4% of observations, respectively. Steady-state model projections of radar retrievals aloft are shown to produce the correct rapid enhancement of surface snowfall compared to the lowest-available radar retrievals from 500 m MSL. Future studies can utilize these equations alongside radar measurements to estimate Nt and Dm below radar tilt elevations and to estimate uncertain microphysical parameters such as collision–coalescence efficiencies. Significance Statement While complex numerical models are often used to describe weather phenomenon, sometimes simple equations can instead provide equally good or comparable results. Thus, these simple equations can be used in place of more complicated models in certain situations and this replacement can allow for computationally efficient and elegant solutions. This study derives such simple equations in terms of exponential and power-law mathematical functions that describe how the average size and total number of snow or rain particles change at different atmospheric height levels due to growth from the vapor phase and aggregation (the sticking together) of these particles balanced with their fallout from clouds. We catalog these mathematical equations for different assumptions of particle characteristics and we then test these equations using spirally descending aircraft observations and ground-based measurements. Overall, we show that these mathematical equations, despite their simplicity, are capable of accurately describing the magnitude and shape of observed height and time series profiles of particle sizes and numbers. These equations can be used by researchers and forecasters along with radar measurements to improve the understanding of precipitation and the estimation of its properties.

Identifying Important Microphysical Properties and Processes for Marine Fog Forecasts

Abstract In this study, a marine fog event that occurred from 0000 to 1800 UTC 7 September 2018 near Canada’s Grand Banks is used to investigate the sensitivity of simulated fog properties to six model parameters found primarily in the microphysics scheme. To do so, we ran a large suite of regional simulations that spanned the life cycle of the fog event using the Regional Atmospheric Modeling System (RAMS). We randomly selected parameter combinations for the simulation suite and used Gaussian process regression to emulate the response of a variety of simulated fog properties to the parameters. We find that the microphysics shape parameter, which controls the relative width of the droplet size distribution, and the aerosol number concentration have the greatest impact on fog in terms of spatial extent, duration, and surface visibility. In general, parameters that reduce mean fall speed of droplets and/or suppress drizzle formation lead to reduced visibility in fog but also delayed onset, shorter lifetimes, and reduced spatial extent. The importance of the distribution width suggests a need for better characterization of this property for fog droplet distributions and better treatment of this property in microphysics schemes.

On particle fountains in a crossflow

We present new experiments of particle-laden turbulent fountains in a uniform horizontal crossflow, $u_a$ , with momentum flux, $M_0$ , and buoyancy flux, $B_0$ . We use the ratio, $P$ , of the crossflow speed to the characteristic fountain speed, $M_0^{-1/4}|B_0|^{1/2}$ , and the ratio $U$ , of the Stokes fall speed of the particles, $v_s$ , to the characteristic fountain speed, to characterise the dynamics of a particle fountain in a crossflow. We find that the dynamics of these particle fountains can be categorised into three distinct regimes. In regime I when the fall speed of the particles is small in comparison with the characteristic fountain speed ( $U\ll 1$ ), the particles remain well-coupled to the fountain fluid and the flow essentially behaves as a single-phase fountain in a crossflow. In the transitional regime II ( $0.1< U<1$ ), when the fall speed of particles is comparable to the characteristic fountain speed, we observe some particles separating from the fountain fluid during the descent of the flow which leaves some fluid neutrally buoyant. As $U>1$ (regime III), we observe particles separating from the fountain as it rises from the source. We measure the average dispersal distance of the particles and the speed of the descending particles as a function of $U$ and $P$ and compare these results with models of a single-phase fountain in a crossflow. We build a regime diagram to describe the effect of $U$ and $P$ on the flow dynamics and consider our work in the context of deep-submarine volcanic eruptions.

Climate Impacts of Convective Cloud Microphysics in NCAR CAM5

Abstract We improved the treatments of convective cloud microphysics in the NCAR Community Atmosphere Model version 5.3 (CAM5.3) by 1) implementing new terminal velocity parameterizations for convective ice and snow particles, 2) adding graupel microphysics, 3) considering convective snow detrainment, and 4) enhancing rain initiation and generation rate in warm clouds. We evaluated the impacts of improved microphysics on simulated global climate, focusing on simulated cloud radiative forcing, graupel microphysics, convective cloud ice amount, and tropical precipitation. Compared to CAM5.3 with the default convective microphysics, the too-strong cloud shortwave radiative forcing due primarily to excessive convective cloud liquid is largely alleviated over the tropics and midlatitudes after rain initiation and generation rate is enhanced, in better agreement with the CERES-EBAF estimates. Geographic distributions of graupel occurrence are reasonably simulated over continents; whereas the graupel occurrence remains highly uncertain over the oceanic storm-track regions. When evaluated against the CloudSat–CALIPSO estimates, the overestimation of convective ice mass is alleviated with the improved convective ice microphysics, among which adding graupel microphysics and the accompanying increase in hydrometeor fall speed play the most important role. The probability distribution function (PDF) of rainfall intensity is sensitive to warm rain processes in convective clouds, and enhancement in warm rain production shifts the PDF toward heavier precipitation, which agrees better with the TRMM observations. Common biases of overestimating the light rain frequency and underestimating the heavy rain frequency in GCMs are mitigated.

Assessment of OTT Parsivel2 Raindrop Fall Speed Measurements

Abstract This study was to assess the raindrop fall speed measurement capabilities of OTT Parsivel2 disdrometer through comparisons with measurements of a collocated High-speed Optical Disdrometer (HOD). Raindrop fall speed is often assumed to be terminal in relevant hydrological and meteorological applications, and generally predicted using terminal speed–raindrop size relationships obtained from laboratory observations. Nevertheless, recent field studies have revealed that other factors (e.g., wind, turbulence, raindrop oscillations, and collisions) significantly influence raindrop fall speed, necessitating accurate fall speed measurements for many applications instead of reliance on laboratory-based terminal speed predictions. Field observations in this study covered rainfall events with a variety of environmental conditions, including light, moderate, and heavy rainfall events. This study also involved rigorous laboratory experiments to faithfully identify the internal filtering and calculation algorithm of OTT Parsivel2. Our assessments revealed that, for the smaller diameter bins, Parsivel2 filters out many of the observed raindrops that fall faster than predicted terminal speeds, bringing down the mean fall speed for those size bins without observational evidence. Furthermore, Parsivel2 fall speed measurements exhibited notable artificial bell-shaped deviations from the predicted terminal speeds toward subterminal fall starting at around 1 mm diameter raindrops with peak deviations around 1.625 mm diameter bin. Such bell-shaped fall speed deviation patterns were not present in collocated HOD measurements. Assessment results along with the faithfully identified Parsivel2 algorithm are presented with discussions on implications on reported raindrop size distributions (DSD) and rainfall kinetic energy.

Numerical Simulation of Spatiotemporal Distribution of Chaff Clouds for Warship Defense using CFD-DEM Coupling

Warships widely spread numerous chaffs using a blast, which form chaff clouds that create false radar cross-sections to deceive enemy radars. In this study, we established a numerical framework based on a one-way coupling of computational fluid dynamics and discrete element method to simulate the spatiotemporal distribution of chaff clouds for warships in the air. Using the framework, we investigated the effects of wind, initial chaff cartridge angle, and blast pressure on the distribution of chaff clouds. We observed three phases for the chaff cloud diffusion: radial diffusion by the explosion, omnidirectional diffusion by turbulence and collision, and gravity-induced diffusion by the difference in the fall speed. The wind moved the average position of the chaff clouds, and the diffusion due to drag force did not occur. The direction of radial diffusion by the explosion depended on the initial angle of the cartridge, and a more vertical angle led to a wider distribution of the chaffs. As the blast pressure increased, the chaff clouds spread out more widely, but the distribution difference in the direction of gravity was not significant.

Thin disks falling in air

We experimentally investigate the settling of millimetre-sized thin disks in quiescent air. The range of physical parameters is chosen to be relevant to plate crystals settling in the atmosphere: the diameter-to-thickness aspect ratio is$\chi =25\unicode{x2013}60$, the Reynolds numbers based on the disk diameter and fall speed are$Re=O(10^2)$and the inertia ratio is$I^*=O(1)$. Thousands of trajectories are reconstructed for each disk type by planar high-speed imaging, using the method developed by Baker & Coletti (J. Fluid Mech., vol. 943, 2022, A27). Most disks either fall straight vertically with their maximum projected area normal to gravity or tumble while drifting laterally at an angle$<20^\circ$. Two of the three disk sizes considered exhibit bimodal behaviour, with both non-tumbling and tumbling modes occurring with significant probabilities, which stresses the need for a statistical characterization of the process. The smaller disks (1 mm in diameter,$Re=96$) have a stronger tendency to tumble than the larger disks (3 mm in diameter,$Re=360$), at odds with the diffused notion that$Re=100$is a threshold below which falling disks remain horizontal. Larger fall speeds (and, thus, smaller drag coefficients) are found with respect to existing correlations based on experiments in liquids, demonstrating the role of the density ratio in setting the vertical velocity. The data supports a simple scaling of the rotational frequency based on the equilibrium between drag and gravity, which remains to be tested in further studies where disk thickness and density ratio are varied.