Fall Speed Research Articles

Relative pollen productivity estimates of savanna taxa from southern Africa and their application to reconstruct shrub encroachment during the last century

To understand the resilience of African savannas to global change, quantitative information on the long-term dynamics of vegetation is required. Past dynamics can be reconstructed with the REVEALS model, which requires pollen productivity estimates (PPE) that are calibrated using surface pollen and vegetation data. Here we calculated PPE values for five savanna taxa using the extended R-value (ERV) model and two pollen dispersal options: the Gaussian plume model (GPM) and the Lagrangian stochastic model (LSM). The ERV calculations failed to produce a reliable PPE for Poaceae. We therefore used Combretaceae as the reference taxon – although values obtained with Poaceae as the reference taxon are presented in the supplement. Our results indicate that Combretaceae is the taxon with the highest pollen productivity and Grewia the taxon with the lowest productivity. Acacia and Dichrostachys are intermediate pollen producers. We find no clear indication of whether the GPM PPEs or the LSM PPEs are more realistic, but the differences between these values confirmed that the pollen fall speed has a greater effect in the modelling of GPM than in the LSM. We also applied REVEALS to the pollen record of Lake Otjikoto (northern Namibia) and obtained the first quantitative reconstruction of the last 130 years of vegetation history in the region. Cover estimates for Poaceae indicate the predominance of a semi-open landscape throughout the 20th century, while cover values below 50% since the 21st century correspond to a thick savanna. This change in grass cover is associated with the spread of Vachellia, Senegalia and Grewia reflecting an encroached state.

Meteorological Electromagnetics: Optical and Radar Measurements, Modeling, and Characterization of Snowflakes and Snow

We introduce the concepts, methodologies, and applications of meteorological electromagnetics with a focus on snow, which currently is the least understood component of the global water cycle. As "no two snowflakes are alike," the intricacies of snowflakes and snowfall are both truly fascinating and extremely challenging to measure, analyze, and predict. We describe a unique approach to the characterization of winter precipitation through the synergistic use of advanced optical instrumentation for in situ microphysical and geometrical measurements of ice and snow particles; image processing techniques to obtain the fall speed, size distribution, 3D shape (mesh), density, and effective dielectric constant of snowflakes; method of moments (MoM) scattering computations of precipitation particles; and state-of-the-art dualpolarization radars for the measurement of polarimetric scattering observables. We discuss the operations, observations, and analyses using this approach during a snow field campaign that took place in Colorado, United States, from 2014 to 2017, and we also introduce an international collaborative field program in association with the 2018 Winter Olympics in South Korea. One goal of this article is to promote meteorological electromagnetics as an interdisciplinary field where nature, science, and technology meet in some of the most fascinating and rewarding ways and where many key areas of interest and endeavors of the antennas and propagation community play an indispensable role.

Settling and clustering of snow particles in atmospheric turbulence

The effect of turbulence on snow precipitation is not incorporated into present weather forecasting models. Here we show evidence that turbulence is in fact a key influence on both fall speed and spatial distribution of settling snow. We consider three snowfall events under vastly different levels of atmospheric turbulence. We characterize the size and morphology of the snow particles, and we simultaneously image their velocity, acceleration and relative concentration over vertical planes approximately$30\ \textrm {m}^2$in area. We find that turbulence-driven settling enhancement explains otherwise contradictory trends between the particle size and velocity. The estimates of the Stokes number and the correlation between vertical velocity and local concentration are consistent with the view that the enhanced settling is rooted in the preferential sweeping mechanism. When the snow vertical velocity is large compared to the characteristic turbulence velocity, the crossing trajectories effect results in strong accelerations. When the conditions of preferential sweeping are met, the concentration field is highly non-uniform and clustering appears over a wide range of scales. These clusters, identified for the first time in a naturally occurring flow, display the signature features seen in canonical settings: power-law size distribution, fractal-like shape, vertical elongation and large fall speed that increases with the cluster size. These findings demonstrate that the fundamental phenomenology of particle-laden turbulence can be leveraged towards a better predictive understanding of snow precipitation and ground snow accumulation. They also demonstrate how environmental flows can be used to investigate dispersed multiphase flows at Reynolds numbers not accessible in laboratory experiments or numerical simulations.

Arctic observations and numerical simulations of surface wind effects on Multi-Angle Snowflake Camera measurements

Abstract. Ground-based measurements of frozen precipitation are heavily influenced by interactions of surface winds with gauge-shield geometry. The Multi-Angle Snowflake Camera (MASC), which photographs hydrometeors in free-fall from three different angles while simultaneously measuring their fall speed, has been used in the field at multiple midlatitude and polar locations both with and without wind shielding. Here, we present an analysis of Arctic field observations – with and without a Belfort double Alter shield – and compare the results to computational fluid dynamics (CFD) simulations of the airflow and corresponding particle trajectories around the unshielded MASC. MASC-measured fall speeds compare well with Ka-band Atmospheric Radiation Measurement (ARM) Zenith Radar (KAZR) mean Doppler velocities only when winds are light (≤5ms-1) and the MASC is shielded. MASC-measured fall speeds that do not match KAZR-measured velocities tend to fall below a threshold value that increases approximately linearly with wind speed but is generally <0.5ms-1. For those events with wind speeds ≤1.5ms-1, hydrometeors fall with an orientation angle mode of 12∘ from the horizontal plane, and large, low-density aggregates are as much as 5 times more likely to be observed. Simulations in the absence of a wind shield show a separation of flow at the upstream side of the instrument, with an upward velocity component just above the aperture, which decreases the mean particle fall speed by 55 % (74 %) for a wind speed of 5 m s−1 (10 m s−1). We conclude that accurate MASC observations of the microphysical, orientation, and fall speed characteristics of snow particles require shielding by a double wind fence and restriction of analysis to events where winds are light (≤5ms-1). Hydrometeors do not generally fall in still air, so adjustments to these properties' distributions within natural turbulence remain to be determined.

Hailstone Shapes

AbstractHailstone growth results in a variety of hailstone shapes. These shapes hold implications for modeling of hail processes, hailstone fall behaviors including fall speeds, and remote sensing signatures of hail. This study is an in-depth analysis of natural hailstone shapes, using a large dataset of hailstones collected in the field over a 6-yr period. These data come from manual measurements with digital calipers and three-dimensional infrared laser scans. Hailstones tend to have an ellipsoidal geometry with minor-to-major axis ratios ranging from 0.4 to 0.8, and intermediate-to-major axis ratios between 0.8 and 1.0. These suggest hailstones are better represented as triaxial ellipsoids as opposed to spheres or spheroids, which is commonly assumed. The laser scans allow for precise sphericity measurements, for the first time. Hailstones become increasingly nonspherical with increasing maximum dimension, with a typical range of sphericity values of 0.57 to 0.99. These sphericity values were used to estimate the drag coefficient, which was found to have a typical range of 0.5 to over 0.9. Hailstone maximum dimension tends to be 20%–50% larger than the equivalent-volume spherical diameter. As a step toward understanding and quantifying hailstone shapes, this study may aid in better parameterizations of hail in models and remote sensing hail detection and sizing algorithms.

Which Combinations of Environmental Conditions and Microphysical Parameter Values Produce a Given Orographic Precipitation Distribution?

AbstractThis study applies an idealized modeling framework, alongside a Bayesian Markov chain Monte Carlo (MCMC) algorithm, to explore which combinations of upstream environmental conditions and cloud microphysical parameter values can produce a particular precipitation distribution over an idealized two-dimensional, bell-shaped mountain. Simulations focus on orographic precipitation produced when an atmospheric river interacts with topography. MCMC-based analysis reveals that different combinations of parameter values produce a similar precipitation distribution, with the most influential parameters being relative humidity (RH), horizontal wind speed (U), surface potential temperature (θsfc), and the snow fall speed coefficient (As). RH, U, and As exhibit interdependence: changes in one or more of these factors can be mitigated by compensating changes in the other(s) to produce similar orographic precipitation rates. The results also indicate that the parameter sensitivities and relationships can vary for spatial subregions and given different environmental conditions. In particular, high θsfc values are more likely to produce the target precipitation rate and spatial distribution, and thus the ensemble of simulations shows a preference for liquid precipitation at the surface. The results presented here highlight the complexity of orographic precipitation controls, and have implications for flood and water management, observational efforts, and climate change.

Linking rain into ice microphysics across the melting layer in stratiform rain: a closure study

Abstract. This study investigates the link between rain and ice microphysics across the melting layer in stratiform rain systems using measurements from vertically pointing multi-frequency Doppler radars. A novel methodology to examine the variability of the precipitation rate and the mass-weighted melted diameter (Dm) across the melting region is proposed and applied to a 6 h long case study, observed during the TRIPEx-pol field campaign at the Jülich Observatory for Cloud Evolution Core Facility and covering a gamut of ice microphysical processes. The methodology is based on an optimal estimation (OE) retrieval of particle size distributions (PSDs) and dynamics (turbulence and vertical motions) from observed multi-frequency radar Doppler spectra applied both above and below the melting layer. First, the retrieval is applied in the rain region; based on a one-to-one conversion of raindrops into snowflakes, the retrieved drop size distributions (DSDs) are propagated upward to provide the mass-flux-preserving PSDs of snow. These ice PSDs are used to simulate radar reflectivities above the melting layer for different snow models and they are evaluated for a consistency with the actual radar measurements. Second, the OE snow retrieval where Doppler spectra are simulated based on different snow models, which consistently compute fall speeds and electromagnetic properties, is performed. The results corresponding to the best-matching models are then used to estimate snow fluxes and Dm, which are directly compared to the corresponding rain quantities. For the case study, the total accumulation of rain (2.30 mm) and the melted equivalent accumulation of snow (1.93 mm) show a 19 % difference. The analysis suggests that the mass flux through the melting zone is well preserved except the periods of intense riming where the precipitation rates were higher in rain than in the ice above. This is potentially due to additional condensation within the melting zone in correspondence to high relative humidity and collision and coalescence with the cloud droplets whose occurrence is ubiquitous with riming. It is shown that the mean mass-weighted diameter of ice is strongly related to the characteristic size of the underlying rain except the period of extreme aggregation where breakup of melting snowflakes significantly reduces Dm. The proposed methodology can be applied to long-term observations to advance our knowledge of the processes occurring across the melting region; this can then be used to improve assumptions underpinning spaceborne radar precipitation retrievals.

Improvements to melting snow behavior in a bulk microphysics scheme

Snow falling into a melting layer will eventually consist of a fraction of meltwater and hence change its characteristics in terms of size, shape, density and fall speed. Most microphysical parameterizations in numerical weather prediction models typically only represent purely solid or liquid hydrometeors. Generally, this has been an acceptable compromise since the melting layer is typically very shallow and adding a mixed solid/liquid particle type would result in increased computational time. This research shows how improvements were made to the treatment of melting snow in a microphysical parameterization within the Weather Research and Forecasting (WRF) model by implementing an approximation of snowflake melted fraction together with a physically-based expression for melting particle terminal velocity. In addition, the more appropriate definition of melting level defined by the wet-bulb temperature was consistently used in various process rates, all while not adding additional prognostic variables that would add computational cost. Multiple events observed during the 2015–2016 Olympic Mountain Experiment (OLYMPEX) were used to compare with the WRF model results. The modified scheme is able to represent disdrometer observations of joint particle size and fall velocity during wet snow events, as well as fall velocity profiles through the melting layer derived from a vertically-pointing radar. The improved scheme removes ‘bulls’ eyes' of snow accumulation in lee-side areas within the melting zone, and should result in better predictions of surface precipitation phase and amount.

Beach classifications in response to south-west monsoon waves: A case study

In scientific literature, classification models of beaches according to numerical and theoretical parameters are abundant. This study shows a case study concerning how a sandy beach responds morphologically to monsoonal waves and how the beach is classified as per energy conditions. The dynamics of sediments besides the related morphological variations are expressed as functions of incident wave’s climate, traits of sediments, and various environmental determiners. This study substantiates quantitative correlations between incident wave’s energy flux, sand grain size, fall speed parameters, and wave’s steepness and as sorts beach as per conditions of energy via multiple empirical functions. Additionally, a criterion corresponding with the direction of motion of sediment according to shifting waves’ climate is also suggested and verified under field environment.

Study of rain classification and the tendency of gamma DSD parameterizations in Mexico

Precipitation is a key component of the hydrologic cycle, so the knowledge and comprehension of its processes of formation and evolution are of paramount importance. This study presents an analysis of microphysical data and drop size distributions (DSD) collected with PWS100 optical disdrometers at four sites in Mexico. Bulk parameters (accumulated water and rainfall intensity) estimated from microphysical data (drop size and fall speed) showed good agreement with observations obtained using rain gauges installed next to the optical devices. Estimates of accumulated water were used to evaluate the efficiency of four different methods of moments for the fitting of the DSD gamma parameters. The outcomes reveal that the second, fourth, and sixth DSD moments method has a better performance (by showing the lowest RMSE value with respect to the measurements) and yields the closest results to those for the Γ–normalized DSD parameterization. Also, a new method for rain classification based on the variation of accumulated water and median volume diameter (D0), which is used as an estimator of the DSD width, is proposed. The method allows for the characterization of rain into three types (convective, stratiform, and shallow), and results can be related to previous observations from DSD parameters (N0 jumps). The study shows that all three gamma DSD parameters (N0, Λ and μ) have large values when the spectra are dominated by large numbers of small and medium-sized drops (low R values), and smaller values when DSD shifts toward large diameters as R increases. Furthermore, the averages of the gamma parameters reveal lower, intermediate and greater values as rain is classified as convective (intense), stratiform or shallow (very light), respectively. The opposite behavior is observed for D0, which agrees with the previous results. These outcomes reveal that continuous research is necessary to refine the tendencies of DSD parameters, even at different places, with rainfall intensity or type of rain and for the improvement of our knowledge of rain processes.

Microwave single-scattering properties of non-spheroidal raindrops

Abstract. Falling raindrops undergo a change in morphology as they grow in size and the fall speed increases. This change can lead to significant effects in passive and active microwave remote sensing measurements, typically in the form of a polarization signal. Because previous studies generally only considered either passive or active measurements and a limited set of frequencies, there exist no general guidelines on how and when to consider such raindrop effects in scientific and meteorological remote sensing. In an attempt to provide an overview on this topic, this study considered passive and active remote sensing simultaneously and a wider set of frequencies than in previous studies. Single-scattering property (SSP) data of horizontally oriented raindrops were calculated using the T-matrix method at a large set of frequencies (34 in total). The shapes of the raindrops were calculated assuming an aerodynamic equilibrium model, resulting in drops with flattened bases. The SSP data are published in an open-access repository in order to promote the usage of realistic microphysical assumptions in the microwave remote sensing community. Furthermore, the SSPs were employed in radiative transfer simulations of passive and active microwave rain observations, in order to investigate the impact of raindrop shape upon observations and to provide general guidelines on usage of the published database. Several instances of noticeable raindrop shape-induced effects could be identified. For instance, it was found that the flattened base of equilibrium drops can lead to an enhancement in back-scattering at 94.1 GHz of 1.5 dBZ at 10 mm h−1, and passive simulations showed that shape-induced effects on measured brightness temperatures can be at least 1 K.

Idealized Model Simulations to Determine Impacts of Storm‐Relative Winds on Differential Reflectivity and Specific Differential Phase Fields

AbstractHydrometeors of varying sizes have different fall speeds; for example, larger raindrops have greater fall speeds than smaller raindrops. The resultant differential sedimentation leads to differences in residence time in a sorting layer where drops can be advected by the storm‐relative winds. The resulting size sorting has an effect on the polarimetric radar variables including specific differential phase KDP and differential reflectivity ZDR. This study uses a simple numerical model of raindrop size sorting to analyze and further elucidate the relationship between the storm‐relative winds and the ZDR and KDP fields. Increased mean storm‐relative winds lead to increased ZDR magnitudes and decreased KDP magnitudes. The separation distance between ZDR and KDP maxima is proportional to the magnitude of the mean storm‐relative wind and the orientation of a vector from ZDR to KDP maxima is aligned with the mean storm‐relative wind over the sorting layer. Further, it is shown that larger values of storm‐relative helicity are associated with greater separation distances and separation orientations approaching orthogonal to the shear vector over the sorting layer.

Визначення придатності пористих пресовок з алюмінію та алюмінієвих сплавів для використання в якості енергопоглинаючих елементів

This work reports the results of experimental studies on the applicability of porous pressings of aluminum alloys to passive safety systems. The porous pressings were made from aluminum and aluminum alloy powders with a particle size up to 200 ?m using a hydraulic press. The porosity was varied by varying the pressure in the press hydrosystem and the pressing force. The specimens were not sintered, and no plasticizer was added. To determine which specimen characteristic, the mass or the porosity, is more important, specimens of the same mass (0.01 kg) were used [the deviation did not exceed (2.7 ? 2.8) % ]. To determine the impact absorption ability of the porous pressings of aluminum and aluminum alloy powders, a vertical impact testing machine was used. The ram mass was 22.5 kg (weight 220 N), the fall speed was 5 m/s, and the fall energy was 300 J. The impact absorption ability of the porous pressings was determined by comparing the accelerations and rebound height of the ram in the presence of a porous pressing with their calculated free-fall values. The experiments showed that the use of specimens of maximum porosity decreases the impact energy by the value of the plastic work of deformation and the fracture energy. A comparison of the performance of different specimens showed that the energy absorption ability increases with porosity. As demonstrated by the experiments, porous pressings of aluminum and aluminum alloys can be used as energy -absorbing elements of passive safety systems for commercial and armored combat vehicles, and the impact absorption ability of porous fillers, in particular porous pressings of aluminum and aluminum alloys, can be determined using vertical impact testing machines. Using porous pressings of aluminum and aluminum alloys as an energy-absorbing material decreases the impact acceleration by a factor of 30 to 85 at an impact speed up to 5 m/s. The ability of a pressing to reduce the impact acceleration depends on its dimensions and porosity to a greater extent than on its mass. The greatest decrease in impact acceleration is provided by porous pressings of maximum porosity, in which the impact energy is converted to the plastic work of deformation and the fracture energy.

Application of holography and automated image processing for laboratory experiments on mass and fall speed of small cloud ice crystals

Abstract. An ice cloud chamber was developed at the Johannes Gutenberg University of Mainz for generating several thousand data points for mass and sedimentation velocity measurements of ice crystals with sizes less than 150 µm. Ice nucleation was initiated from a cloud of supercooled droplets by local cooling using a liquid nitrogen cold finger. Three-dimensional tracks of ice crystals falling through the slightly supersaturated environment were obtained from the reconstruction of sequential holographic images, automated detection of the crystals in the hologram reconstructions, and particle tracking. Through collection of the crystals and investigation under a microscope before and after melting, crystal mass was determined as a function of size. The experimentally obtained mass versus diameter (m(D)) power law relationship resulted in lower masses for small ice crystals than from commonly adopted parameterizations. Thus, they did not support the currently accepted extrapolation of relationships measured for larger crystal sizes. The relationship between Best (X) and Reynolds (Re) numbers for columnar crystals was found to be X=15.3 Re1.2, which is in general agreement with literature parameterizations.

The NASA‐JAXA Global Precipitation Measurement mission – part II: New frontiers in precipitation science

The <scp>NASA‐JAXA</scp> Global Precipitation Measurement mission – part <scp>II</scp>: New frontiers in precipitation science

Linkage among ice crystal microphysics, mesoscale dynamics, and cloud and precipitation structures revealed by collocated microwave radiometer and multifrequency radar observations

Abstract. Ice clouds and falling snow are ubiquitous globally and play important roles in the Earth's radiation budget and precipitation processes. Ice particle microphysical properties (e.g., size, habit and orientation) are not only influenced by the ambient environment's dynamic and thermodynamic conditions, but are also intimately connected to the cloud radiative effects and particle fall speeds, which therefore have an impact on future climate projection as well as on the details of the surface precipitation (e.g., onset time, location, type and strength). Our previous work revealed that high-frequency (&gt; 150 GHz) polarimetric radiance difference (PD) from passive microwave sensors is a good indicator of the bulk aspect ratio of horizontally oriented ice particles that often occur inside anvil clouds and/or stratiform precipitation. In this current work, we further investigate the dynamic and thermodynamic mechanisms and cloud–precipitation structures associated with ice-phase microphysics corresponding to different PD signals. In order to do so, collocated CloudSat radar (W-band) and Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM DPR, Ku–Ka-bands) observations as well as European Centre for Medium-Range Weather Forecasts (ECMWF) atmosphere background profiles are grouped according to the magnitude of PD for only stratiform precipitation and/or anvil cloud scenes. We found that horizontally oriented snow aggregates or large snow particles are likely the major contributor to the high-PD signals at 166 GHz, while low-PD magnitudes can be attributed to small cloud ice, randomly oriented snow aggregates, riming snow or supercooled water. Further, high-PD (low-PD) scenes are found to be associated with stronger (weaker) wind shear and higher (lower) ambient humidity, both of which help promote (prohibit) the growth of frozen particles and the organization of convective systems. An ensemble of squall line cases is studied at the end to demonstrate that the PD asymmetry in the leading and trailing edges of the deep convection line is closely tied to the anvil cloud and stratiform precipitation layers, respectively, suggesting the potential usefulness of PD as a proxy of stratiform–convective precipitation flag, as well as a proxy of convection life stage.

TRAIL part 2: A comprehensive assessment of ice particle fall speed parametrisations

AbstractResults are presented from a comprehensive experimental campaign studying the aerodynamics of 3D‐printed analogues of ice particles. Measurements of the drag coefficient of the analogues were acquired by using a novel experimental approach to digitally reconstruct the analogues' trajectory and orientation as they fall through a quiescent viscous liquid, using images acquired by a series of digital cameras. The data are used to evaluate commonly used parametrisations of ice particle fall speeds. We find that the accuracy of each of the parametrisations reduces at Reynolds numbers greater than approximately 100, as a result of effects associated with the onset of unsteady oscillating, fluttering or tumbling motions as the analogues fall. We propose a new fall speed parametrisation that predicts the measured drag coefficients at high Reynolds number with an accuracy consistent with that of the leading parametrisation at low Reynolds number.

TRAIL: A novel approach for studying the aerodynamics of ice particles

AbstractA novel experimental approach for studying the aerodynamics of ice particles is presented. The Trajectory Reconstruction Algorithm implemented through Image anaLysis (TRAIL) produces digital reconstructions of the trajectory and orientation of 3D‐printed analogues of ice particles that fall through a quiescent viscous liquid. Data extracted from this analysis can be used to test fall speed parametrisations and investigate the preferred orientation of analogues with complex irregular geometries. Experiments using thin circular discs are used to validate this approach. Measurements from a case study in which an analogue of an aggregate ice particle is used are also reported. Data extracted from the analysis clearly demonstrate important, but poorly understood, aspects of the aerodynamics of atmospheric ice particles. For example, the orientation that the analogue adopts in free fall is shown to depend not only on the geometric shape of the particle, but also on the Reynolds number at which it falls. In addition, measurements of the drag coefficient indicate that the accuracy of fall speed parametrisations reduces at high Reynolds number due to the onset of unsteady motions.

Annual and Seasonal Surface Circulation Over the Mid‐Atlantic Bight Continental Shelf Derived From a Decade of High Frequency Radar Observations

AbstractA decade (2007–2016) of hourly 6‐km‐resolution maps of the surface currents across the Mid‐Atlantic Bight (MAB) generated by a regional‐scale High Frequency Radar network are used to reveal new insights into the spatial patterns of the annual and seasonal mean surface flows. Across the 10‐year time series, temporal means and interannual and intra‐annual variability are used to quantify the variability of spatial surface current patterns. The 10‐year annual mean surface flows are weaker and mostly cross‐shelf near the coast, increasing in speed and rotating to more alongshore directions near the shelfbreak, and increasing in speed and rotating to flow off‐shelf in the southern MAB. The annual mean surface current pattern is relatively stable year to year compared to the hourly variations within a year. The 10‐year seasonal means exhibit similar current patterns, with winter and summer more cross‐shore while spring and fall transitions are more alongshore. Fall and winter mean speeds are larger and correspond to when mean winds are stronger and cross‐shore. Summer mean currents are weakest and correspond to a time when the mean wind opposes the alongshore flow. Again, intra‐annual variability is much greater than interannual, with the fall season exhibiting the most interseasonal variability in the surface current patterns. The extreme fall seasons of 2009 and 2011 are related to extremes in the wind and river discharge events caused by different persistent synoptic meteorological conditions, resulting in more or less rapid fall transitions from stratified summer to well‐mixed winter conditions.

Direct observations of a Mt Everest snowstorm from the world's highest surface‐based radar observations

Direct observations of a Mt Everest snowstorm from the world's highest surface‐based radar observations