Fall Velocity Of Particles Research Articles

Quantifying uncertainty in simulations of the West African monsoon with the use of surrogate models

Abstract. Simulating the West African monsoon (WAM) system using numerical weather and climate models suffers from large uncertainties, which are difficult to assess due to nonlinear interactions between different components of the WAM. Here we present a fundamentally new approach to the problem by approximating the behavior of a numerical model – here the Icosahedral Nonhydrostatic (ICON) model – through a statistical surrogate model based on universal kriging, a general form of Gaussian process regression, which allows for a comprehensive global sensitivity analysis. The main steps of our analysis are as follows: (i) identify the most important uncertain model parameters and their probability density functions, for which we employ a new strategy dealing with non-uniformity in the kriging process. (ii) Define quantities of interest (QoIs) that represent general meteorological fields, such as temperature, pressure, cloud cover and precipitation, as well as the prominent WAM features, namely the tropical easterly jet, African easterly jet, Saharan heat low (SHL) and intertropical discontinuity. (iii) Apply a sampling strategy with regard to the kriging method to identify model parameter combinations which are used for numerical modeling experiments. (iv) Conduct ICON model runs for identified model parameter combinations over a nested limited-area domain from 28° W to 34° E and from 10° S to 34° N. The simulations are run for August in 4 different years (2016 to 2019) to capture the peak northward penetration of rainfall into West Africa, and QoIs are computed based on the mean response over the whole month in all years. (v) Quantify sensitivity of QoIs to uncertain model parameters in an integrated and a local analysis. The results show that simple isolated relationships between single model parameters and WAM QoIs rarely exist. Changing individual parameters affects multiple QoIs simultaneously, reflecting the physical links between them and the complexity of the WAM system. The entrainment rate in the convection scheme and the terminal fall velocity of ice particles show the greatest effects on the QoIs. Larger values of these two parameters reduce cloud cover and precipitation and intensify the SHL. The entrainment rate primarily affects 2 m temperature and 2 m dew point temperature and causes latitudinal shifts, whereas the terminal fall velocity of ice mostly affects cloud cover. Furthermore, the parameter that controls the evaporative soil surface has a major effect on 2 m temperature, 2 m dew point temperature and cloud cover. The results highlight the usefulness of surrogate models for the analysis of model uncertainty and open up new opportunities to better constrain model parameters through a comparison of the model output with selected observations.

Turbulence as a Key Driver of Ice Aggregation and Riming in Arctic Low‐Level Mixed‐Phase Clouds, Revealed by Long‐Term Cloud Radar Observations

AbstractTurbulence in clouds is known to enhance particle collision rates, as widely demonstrated for warm rain formation. A similar impact on ice growth processes is expected but a solid observational basis is missing. A statistical analysis of a 15‐month data set of cloud radar observations allows for the first time to quantify the impact of turbulence on ice aggregation and riming in Arctic low‐level mixed‐phase clouds. Increasing eddy dissipation rate (EDR), from below 10−4 to above 10−3 m2 s−3, yields larger ice aggregates, and higher particle concentration, likely caused by increasing fragmentation. In conditions more favorable to riming, higher EDR is associated with dramatically higher particle fall velocities (by up to 125%), under similar liquid water paths, indicative of markedly higher degrees of riming. Our findings thus reveal the key role of turbulence for cold precipitation formation, and highlight the need for an improved understanding of turbulence‐hydrometeor interactions in cold clouds.

Quantifying Uncertainty in Ice Particle Velocity–Dimension Relationships Using MC3E Observations

Abstract Ice particle terminal fall velocity (Vt) is fundamental for determining microphysical processes, yet remains extremely challenging to measure. Current theoretical best estimates of Vt are functions of Reynolds number. The Reynolds number is related to the Best number, which is a function of ice particle mass, area ratio (Ar), and maximum dimension (Dmax). These estimates are not conducive for use in most models since model parameterizations often take the form , where (α, β) depend on habit and Dmax. A previously developed framework is used to determine surfaces of equally plausible (α, β) coefficients whereby ice particle size/shape distributions are combined with Vt best estimates to determine mass- (VM) or reflectivity-weighted (VZ) velocities that closely match parameterized VM,SD or VZ,SD calculated using the (α, β) coefficients using two approaches. The first uses surfaces of equally plausible (a, b) coefficients describing mass (M)–dimension relationships (i.e., ) to calculate mass- or reflectivity-weighted velocity from size/shape distributions that are then used to determine (α, β) coefficients. The second investigates how uncertainties in Ar, Dmax, and size distribution N(D) affect VM or VZ. For seven of nine flight legs flown on 20 and 23 May 2011 during the Mesoscale Continental Convective Clouds Experiment (MC3E), uncertainty from natural parameter variability—namely, the variability in ice particle parameters in similar meteorological conditions—exceeds uncertainties arising from different Ar assumptions or Dmax estimates. The combined uncertainty between Ar, Dmax, and N(D) produced smaller variability in (α, β) compared to varying M(D), demonstrating M(D) must be accurately quantified for model fall velocities. Primary sources of uncertainty vary considerably depending on environmental conditions. Significance Statement Ice particle fall velocity is fundamental for numerous processes within clouds, and hence is a critical property that must be accurately represented in weather and climate models. Using aircraft observations of ice particle shapes and sizes obtained in clouds behind midlatitude thunderstorms, this work develops a new framework for estimating ice particle fall velocities and their uncertainty, including quantifying the importance of different uncertainty sources from cloud microphysics measurements. Natural parameter variability contributes the most uncertainty in ice particle fall velocity estimates, although other sources can also be important contributors to uncertainty in certain conditions. Additional work examining ice particle data is needed to further understand how dependent uncertainty in certain ice particle properties are to local environmental conditions.

Development of a New Particle Imaging Radiosonde with Particle Fall Velocity Measurements in Clouds

Development of a New Particle Imaging Radiosonde with Particle Fall Velocity Measurements in Clouds

Gravitational Collision of Small Nonspherical Particles: Swept Volumes of Prolate and Oblate Spheroids in Calm Air

Abstract The aggregation rate of ice crystals depends on their shape and intercrystal relative velocity. Unlike spherical particles, the nonspherical ones can have various orientations relative to the gravitational force in the vertical direction and can approach each other at many different angles. Furthermore, the fall velocity of such particles could deviate from the vertical direction velocity. These properties add to the computational complexity of nonspherical particle collisions. In this study, we derive general mathematical expressions for gravity-induced swept volumes of spheroidal particles. The swept volumes are shown to depend on the particles’ joint orientation distribution and relative velocities. Assuming that the particles are Stokesian prolate and oblate spheroids of different sizes and aspect ratios, the swept volumes were calculated and compared to those of equivalent volume spheres. Most calculated swept volumes were larger than the swept volumes of equivalent spherical particles, sometimes by several orders of magnitude. This was due to both the complex geometry and the side drift, experienced by spheroids falling with their major axes not parallel to gravity. We expect that the collision rate between nonspherical particles is substantially higher than that of equivalent volume spheres because the collision process is nonlinear. These results suggest that the simplistic approach of equivalent spheres might lead to serious errors in the computation of the collision rate.

Model estimates of microplastic potential contamination pattern of the eastern Gulf of Finland in 2018

The work is focused on the assessment of microplastics transport and distribution in the eastern part of the Gulf of Finland by means of numerical modeling. In the present study only the riverine sources of microplastics are taken into account. The presented model also accounts for possible sink of suspended microplastic particles into sediments due to simple parameterization of biogeochemical processes such as biofouling and ingestion by zooplankton. Two basic scenarios with different initial fall velocities of suspended microplastic particles, 0.2 m/day and 1.2 m/day, are discussed. The distribution of microplastics coming with the riverine waters of the Neva, Luga, and Narva rivers has been investigated, based on a numerical hydrodynamical hindcast of the year 2018. Model simulations show that the transport of suspended microplastics occurs along the northern coast of the considered area more intensively compared to the southern coast, especially in the easternmost shallow part of the gulf. The results are in a good agreement with other studies focused on the microplastic pollution of the Neva Bay, and with available observational data. The presented results and developed model can be useful tools aimed to assess the intensity and mechanisms of microplastic pollution of the eastern Gulf of Finland. The results can be used in the selection of areas for future environmental monitoring of microplastics pollution of the eastern part of the Gulf of Finland.

Calibration of non‐catching precipitation measurement instruments: A review

AbstractNon‐catching type gauges are the emerging class of in situ precipitation measurement instruments. For these instruments, rigorous testing and calibration are more challenging than for traditional gauges. Hydrometeors characteristics like particle size, shape, fall velocity and density must be reproduced in a controlled environment to provide the reference precipitation, instead of the equivalent water flow used for catching‐type gauges. They are generally calibrated by the manufacturers using internal procedures developed for the specific technology employed. No agreed methodology exists, and the adopted procedures are rarely traceable to internationally recognized standards. The EURAMET project 18NRM03 ‘INCIPIT’ on ‘Calibration and accuracy of non‐catching instruments to measure liquid/solid atmospheric precipitation’, funded by the European Metrology Programme for Innovation and Research (EMPIR), was initiated in 2019 to investigate calibration and accuracy issues of non‐catching measuring instruments used for liquid/solid atmospheric precipitation measurement. A survey of the existing models of non‐catching type instruments was initially performed and this paper provides an overview and a description of their working principles and the adopted calibration procedures. Both literature works and technical manuals disclosed by manufacturers are summarized and discussed, while current limitations and metrological requirements are identified.

Assessing the Effect of Riming on Snow Microphysics: The First Observational Study in East China

AbstractThrough the collision and freezing of supercooled droplets on the surface of snow particles, riming can change the density, fall velocity and aspect ratio of snow particles. Riming plays an important role in the formation of precipitation in cold clouds. To our knowledge, the impact of riming on snow microphysics is yet well understood, and there is a lack of observations obtained in China addressing this issue. For the first time in East China, the connection between riming and snow microphysical properties was investigated quantitatively during snow events in two winters. To quantify the degree of riming, the rime mass fraction (FR) is derived using the combination of a 2‐D video disdrometer (2DVD) and a weighing gauge. FR is added to the density‐diameter and fall velocity‐diameter relations, and a quantitative relation between riming and shapes of snowflakes is established based on the in situ observation of the 2DVD. The results show that riming can well explain the variability in the density and fall velocity of snowflakes. The changes in the shape of snowflakes can be divided into two distinct stages with increasing riming: in the initial stage (FR < 0.5), the aspect ratio increases very slowly, while in the later stage (FR > 0.5), the aspect ratio increases rapidly. Direct observations of the continuous changes in the shapes of snowflakes with riming are in good agreement with the retrieval results of radar.

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.

Empirical, Numerical, and Soft Modelling Approaches for Non-Cohesive Sediment Transport

This paper reviews the modelling approaches and outstanding issues with regard to non-cohesive sediment transport which has been experimentally and numerically studied for many decades owing to its importance to hydraulic structures, morphology and related areas. About 311 papers are reviewed that included laboratory experiments, field observations, and analytical and numerical modelling studies. The reviewed papers cover the period 1938–2020. Of 311, 95 papers are included in this paper. The modeling approaches include empirical, physics-based, spatially averaged, and soft methods. The empirical models have oversimplified the process while the physics-based models are indispensable when the detailed analysis is required. On the other hand, when the objective is to obtain cumulative sediment loads, it would be advantageous to employ the spatial averaging modelling and/or the soft computing methods due to less computational burden and data requirements. The outstanding issues are related to the particle fall velocity, particle velocity, incipient motion, and transport function that require further experimental investigations especially for unsteady non-uniform transport processes.

Model Development for Estimation of Sediment Removal Efficiency of Settling Basins Using Group Methods of Data Handling

Settling basins are generally used as sediment removal structures in which flow velocity is reduced, resulting in surplus settlement of sediment particles. The accuracy of the available empirical equations for sediment removal efficiency is checked using data available in the literature. The existing relationships of removal efficiency were not found to yield satisfactory results. Therefore, the data were reanalyzed and new models were developed using nonlinear regression and the group method of data handling (GMDH). On the basis of various performance parameters, it was observed that the proposed nonlinear regression model had the highest accuracy compared with other available relationships. It was also observed that the efficiency estimated using the GMDH model (R=0.960, AAD=14.698, and RMSE=0.094) was more accurate than that estimated by the regression model (R=0.863, AAD=30.675, and RMSE=0.171). Sensitivity analysis indicated that the ratio of particle fall velocity to average flow velocity in the basin was the most effective parameter for sediment removal efficiency. This work will help in quantifying and subsequently improving the management of surplus sediment in canals.

Establishment and Preliminary Application of the Forward Modeling Method for Doppler Spectral Density of Ice Particles

Owing to the various shapes of ice particles, the relationships between fall velocity, backscattering cross-section, mass, and particle size are complicated. This affects the application of cloud radar Doppler spectral density data in the retrieval of the microphysical properties of ice crystals. In this study, under the assumption of six particle shape types, the relationships between particle mass, fall velocity, backscattering cross-section, and particle size were established based on existing research. Variations of Doppler spectral density with the same particle size distribution (PSD) of different ice particle types are discussed. The radar-retrieved liquid and ice PSDs, water content, and mean volume-weighted particle diameter were compared with airborne in situ observations in the Xingtai, Hebei Province, China, in 2018. The results showed the following. (1) For the particles with the same equivalent diameter (De), the fall velocity of the aggregates was the largest, followed by hexagonal columns, hexagonal plates, sector plates, and stellar crystals, with the ice spheres falling two to three times faster than ice crystals with the same De. Hexagonal columns had the largest backscattering cross-section, followed by stellar crystals and sector plates, and the backscattering cross-sections of hexagonal plates and the two types of aggregates were very close to those of ice spheres. (2) The width of the simulated radar Doppler spectral density generated by various ice crystal types with the same PSD was mainly affected by the particle’s falling velocity, which increased with the particle size. Turbulence had different degrees of influence on the Doppler spectrum of different ice crystals, and it also brought large errors to the PSD retrieval. (3) PSD comparisons showed that each ice crystal type retrieved from the cloud radar corresponded well to aircraft observations within a certain scale range, when assuming that only a certain type of ice crystals existed in the cloud, which could fully prove the feasibility of retrieving ice PSDs from the reflectivity spectral density.

Characterization of snowfall estimated by in situ and ground-based remote-sensing observations at Terra Nova Bay, Victoria Land, Antarctica

AbstractKnowledge of the precipitation contribution to the Antarctic surface mass balance is essential for defining the ice-sheet contribution to sea-level rise. Observations of precipitation are sparse over Antarctica, due to harsh environmental conditions. Precipitation during the summer months (November–December–January) on four expeditions, 2015–16, 2016–17, 2017–18 and 2018–19, in the Terra Nova Bay area, were monitored using a vertically pointing radar, disdrometer, snow gauge, radiosounding and an automatic weather station installed at the Italian Mario Zucchelli Station. The relationship between radar reflectivity and precipitation rate at the site can be estimated using these instruments jointly. The error in calculated precipitation is up to 40%, mostly dependent on reflectivity variability and disdrometer inability to define the real particle fall velocity. Mean derived summer precipitation is ~55 mm water equivalent but with a large variability. During collocated measurements in 2018–19, corrected snow gauge amounts agree with those derived from the relationship, within the estimated errors. European Centre for the Medium-Range Weather Forecasts (ECMWF) and the Antarctic Mesoscale Prediction System (AMPS) analysis and operational outputs are able to forecast the precipitation timing but do not adequately reproduce quantities during the most intense events, with overestimation for ECMWF and underestimation for AMPS.

Characteristics of tephra fall from eruptions at Sakurajima volcano, revealed by optical disdrometer measurements

We investigated the main characteristics of tephra fall from the eruptions at Sakurajima volcano in southern Kyushu, Japan, by using an optical disdrometer for simultaneous measurement of particle size and fall velocity. Measurements were carried out for 2 years at one station located 2.5 km south of the active crater. This made it possible to detect 76 tephra fall events, with the detection rate of the tephra events from these south-directed eruption clouds being about 25%. From the relationship between particle diameter and fall velocity, we were able to estimate morphological parameters of volcanic particles. Measurements of temporal change in the tephra fall for each minute revealed that both the tephra diameter and fall velocity gradually decrease with time during each event, where the ranges of the diameter and velocity for the events with south-directed eruption clouds were 0.336–2.04 mm and 1.40–6.24 m s−1, respectively. By using temporal changes in the diameter and velocity, we estimated travel time and distance for the tephra falling from a release point in the eruption cloud to the station, and found a positive correlation between the travel distance and column height for the south-directed clouds, with a determination coefficient of 0.498 for linear fitting. The comparison between tephra data and seismic data revealed that episodic increases in the tephra diameter and fall velocity were correlated with a drastic increase in amplitude of explosion earthquake or tremor. These results indicate that disdrometer measurements can provide valuable information about the quantitative features of the tephra fall and are useful for detecting changes in the magnitude of eruption if a number of suitably placed instruments are deployed.

A three-dimensional numerical model to estimate the fall velocity of sediment particles

The fall velocity of sediment particles plays a key role in sediment transport studies. Researchers have attempted to determine the terminal fall velocity, and most of the studies in this regard have been based on experimental, quasi-experimental, and in-situ measurements. The present study aimed to use a numerical model to estimate the fall velocity of a single sediment particle in distilled and motionless water. We used spherical quartz particles with the diameters of 0.77, 1.09, 2.18, and 4.36 millimeters and density of 2,650 kg/m3. The Flow-3D software was applied to estimate the fall velocity based on the environment of experiment by Ferguson and Church (2004) using the void of flow method. The main objective of this research was to demonstrate the power of the numerical model to simulate the fall velocity of sediment particles. To validate the results of the model, they were compared with the experimental results and 26 well-known publications during 1933-2016 using the root-square-mean and mean-absolute-percentage errors. The results showed good agreement between the experimental and numerical data. Therefore, the proposed numerical model could be used to determine the fall velocity of sediment particles with a wide range of diameters in the proposed environment and particle types.

Dual-wavelength radar technique development for snow rate estimation: a case study from GCPEx

Abstract. quantitative precipitation estimation (QPE) of snowfall has generally been expressed in power-law form between equivalent radar reflectivity factor (Ze) and liquid equivalent snow rate (SR). It is known that there is large variability in the prefactor of the power law due to changes in particle size distribution (PSD), density, and fall velocity, whereas the variability of the exponent is considerably smaller. The dual-wavelength radar reflectivity ratio (DWR) technique can improve SR accuracy by estimating one of the PSD parameters (characteristic diameter), thus reducing the variability due to the prefactor. The two frequencies commonly used in dual-wavelength techniques are Ku- and Ka-bands. The basic idea of DWR is that the snow particle size-to-wavelength ratio is falls in the Rayleigh region at Ku-band but in the Mie region at Ka-band. We propose a method for snow rate estimation by using NASA D3R radar DWR and Ka-band reflectivity observations collected during a long-duration synoptic snow event on 30–31 January 2012 during the GCPEx (GPM Cold-season Precipitation Experiment). Since the particle mass can be estimated using 2-D video disdrometer (2DVD) fall speed data and hydrodynamic theory, we simulate the DWR and compare it directly with D3R radar measurements. We also use the 2DVD-based mass to compute the 2DVD-based SR. Using three different mass estimation methods, we arrive at three respective sets of Z–SR and SR(Zh, DWR) relationships. We then use these relationships with D3R measurements to compute radar-based SR. Finally, we validate our method by comparing the D3R radar-retrieved SR with accumulated SR directly measured by a well-shielded Pluvio gauge for the entire synoptic event.

Linear inverse problem for inferring eruption source parameters from sparse ash deposit data as viewed from an atmospheric dispersion modeling perspective

Determination of the volcanic eruption source parameters—total grain-size distribution and vertical ash mass distribution (VMD) within the source—is carried out on a collection of measured-area samples and granulometry data. For this, the geophysical inverse methods and Hybrid Particle and Concentration Transport Model (HYPACT) driven by wind and turbulence fields simulated with the Regional Atmospheric Modeling System (RAMS) are used. A two-step inversion procedure is proposed to obtain approximate but physically meaningful solution when the total number of ashfall samples is small and it is not possible to make a good initial guess of the source parameters. First, a spectrum of particle fall velocities is estimated by selecting a best-fit subset of aerodynamically distinct subpopulations of free and aggregate particles from the trial set used to simulate a polycomponent ashfall. The singular value decomposition (SVD) analysis is then employed to identify spatial components of the ash emissions’ vertical distribution, as resolvable by the observations. Model validation experiments are conducted for the January 12, 2011, short-duration vulcanian explosion at Kizimen and paroxysmal phase of the December 24, 2006, sub-Plinian eruption at Bezymianny. The derived VMDs exhibit high variability in fine ash content (~ 60–100 wt%) as well as strong secondary maxima in the lower troposphere, likely reflecting the contribution of ash particles fallen out of co-pyroclastic flow ash clouds and partially collapsing eruption columns.

Comparative Evaluation of Snowfall Retrievals from the CloudSat W-band Radar Using Ground-Based Weather Radars

AbstractInstantaneous liquid-equivalent snowfall rates S retrieved from CloudSat W-band cloud radar reflectivity Ze measurements are compared to estimates of S from operational Weather Surveillance Radar-1988 Doppler (WSR-88D) systems when the CloudSat satellite overflew the ground-based radar sites during spatially extensive nimbostratus snowfall events. For these comparisons, the ground-based radar measurements are interpolated to closely match in space and time spaceborne radar resolution volumes above ground clutter, thus avoiding uncertainties in deriving near-surface snowfall rates from measurements aloft by both radar types. Although typical uncertainties of both ground-based and spaceborne snowfall-rate retrieval approaches are quite high, the results from the standard optimal estimation CloudSat 2C-SNOW-PROFILE algorithm are on average in good agreement with the WSR-88D default snowfall algorithm results with correlation coefficients being around 0.8–0.85. The CloudSat standard optimal estimation snowfall-rate products are also shown to be in satisfactory agreement with retrievals from several simple W-band Ze–S relations suggested earlier. The snowfall rate and snow/ice water content (IWC) parameters from the CloudSat 2C-SNOW-PROFILE algorithm are highly interdependent. A tight relation between S and IWC is apparently introduced through the ice particle fall velocity assumption that is made in the reflectivity-based snowfall retrieval algorithm. This suggests that ice sedimentation rate estimates can also be deduced from applications of numerous empirical IWC–reflectivity relations derived previously for different cloud conditions when appropriate assumptions about fall velocities are made. Intercomparisons between different CloudSat snow/ice water content products indicated significant discrepancies in IWC values from different standard CloudSat retrieval algorithms.

The impact of particle shape on fall velocity: Implications for volcanic ash dispersion modelling

Modelling atmospheric volcanic ash dispersion is a critical tool in mitigating the impact of large explosive eruptions; it is also useful for understanding and reconstructing past events. Most atmospheric dispersion models include a sedimentation velocity term that is sensitive to the physical properties of the particle, but many do not use particle shape as an input parameter; instead particles are assumed to be spherical. There are many empirical and semi-empirical shape-dependent drag laws. We measure the velocity of scaled analogue particles over the range of flow conditions anticipated for volcanic ash dispersion to test published formulae against an independent dataset. We use a semi-empirical formula we determined to be accurate for non-spheres to investigate the sensitivity of the modelled transport of an ash cloud to particle shape, using the atmospheric dispersion model NAME and a shape parameter we measure for non-spherical ash particles from Katla volcano, Iceland. We find that model particle trajectories are sensitive to particle shape for particles >1–3 μm diameter; the sedimentation velocity of smaller particles is low compared to atmospheric vertical velocities. Sensitivity to shape increases with size such that 100 μm particles can travel 44% further from the source when they are highly non-spherical (sphericity = 0.5). Despite the sensitivity of the fall velocity of large particles to their shape, however, forecasts of distal ash concentration using particle size distributions of 0.1–100 μm and 0.1–250 μm show relatively good agreement between a spherical and non-spherical case for the first 36 h after an eruption. The vertical structure of an ash cloud is more sensitive to particle shape than the horizontal extent. Model particle trajectories are also sensitive to particle size, and we find a discrepancy between different particle size parameters for non-spherical ash: particle long axis L, used in cryptotephra studies, was on average twice the equivalent-volume sphere diameter dv, used in dispersion modelling, for tephra samples from Katla volcano, Iceland. This discrepancy in size measurements could explain the observed travel distance of large distal cryptotephra shards.

Laboratory study and mathematical modeling of a novel marsh shoreline protection technology for sand collection

Erosion along shorelines is a major cause in the conversion of shoreline wetlands to open water bodies. Conventional shoreline protection structures are expensive to construct and may impede environmental exchanges essential for connectivity and functionality. A novel marsh shoreline protection technology, the Wave Suppressor and Sediment Collection (WSSC) system, addresses these issues. Laboratory studies were conducted on three WSSC units to determine the governing parameters of sediment collection efficiency of this technology. The three units had varying open areas and pipe sizes which enabled those parameters to be directly compared. Two types of sands with median particle diameters (d50) of 0.43 and 0.34 mm were used to evaluate the effects of particle size on the collection efficiency of the units. A new mathematical model was developed to predict the sediment collection efficiency using Van Rijn’s equation for particle fall velocity, and Ribberink and Al-Salem’s equation for sand concentration distribution in a water column. Results showed that the Unit 1, Unit 2 and Unit 3 are capable of collecting sand at 0.30, 0.21 and 0.21 (kg/h) for sand 1, and at 0.39, 0.29, 0.39 (kg/h) for sand 2 respectively. The mathematical model fit the experimental data well and from the model, mass accumulation coefficient (α) alpha was calculated. Mass accumulation coefficients (α) for sand 1 and sand 2 were- 0.94 and 0.97 for Unit 1, 0.63 and 0.70 for Unit 2 and 0.32 and 0.22 for Unit 3 respectively. A sensitivity study of the mathematical model was also performed to determine the governing factors behind the sand collection. The sensitivity study found that water depth, wave height and particle diameter affected the sand collection efficiency the most. The amount of open area on the units, frequency and wavelength were also found to have some effect on collection efficiency.