Ice Aggregates Research Articles

Sensitivity of Arctic Clouds to Ice Microphysical Processes in the NorESM2 Climate Model

Abstract Ice formation remains one of the most poorly represented microphysical processes in climate models. While primary ice production (PIP) parameterizations are known to have a large influence on the modeled cloud properties, the representation of secondary ice production (SIP) is incomplete and its corresponding impact is therefore largely unquantified. Furthermore, ice aggregation is another important process for the total cloud ice budget, which also remains largely unconstrained. In this study, we examine the impact of PIP, SIP, and ice aggregation on Arctic clouds, using the Norwegian Earth System Model, version 2 (NorESM2). Simulations with both prognostic and diagnostic PIP show that heterogeneous freezing alone cannot reproduce the observed cloud ice content. The implementation of missing SIP mechanisms (collisional breakup, drop shattering, and sublimation breakup) in NorESM2 improves the modeled ice properties, while improvements in liquid content occur only in simulations with prognostic PIP. However, results are sensitive to the description of collisional breakup. This mechanism, which dominates SIP in the examined conditions, is very sensitive to the treatment of the sublimation correction factor, a poorly constrained parameter that is included in the utilized parameterization. Finally, variations in ice aggregation treatment can also significantly impact cloud properties, mainly through their impact on collisional breakup efficiency. Overall, enhancement in ice production through the addition of SIP mechanisms and the reduction in ice aggregation (in line with radar observations of shallow Arctic clouds) result in enhanced cloud cover and decreased TOA radiation biases, compared to satellite measurements, especially during the cold months. Significance Statement Arctic clouds remain a large source of uncertainty in projections of the future climate due to the poor representation of the microphysical processes that govern their life cycle. Ice formation is among the least understood processes. While it is widely recognized that better constraints on primary ice production (PIP) are needed to improve existing parameterizations, we show that secondary ice production (SIP) and ice aggregation can have also a significant impact on ice number concentrations. Constraining ice formation through the addition of missing SIP mechanisms and reducing ice aggregation can improve the representation of the cloud macrophysical properties and enhance total cloud cover in the Arctic region, which in turn contributes to decreased TOA radiation biases in the cold months.

The strength of outgassed porous dust aggregates

Context. Outgassing of dust-ice aggregates plays an important role on the surfaces of cometary nuclei as well as for snow-line crossings in protoplanetary disks. Aims. To assess the stability of desiccated dust aggregates, we measured the tensile strength of silica dust samples over a wide range of volume filling factors. Methods. We produced these silica dust samples over a wide range of volume filling factors by gently evaporating dust-ice mixtures with various dust-to-ice mass ratios under vacuum conditions. The tensile strengths of these samples were then measured using the standardized Brazilian disk test. Experiments were performed in a vacuum and at room temperature but were also compared to measurements in air at room temperature and in a vacuum at elevated temperatures. Results. For spherical amorphous silica dust, we find no influence of the environmental conditions (air, vacuum, or heating) on the measured tensile strength. However, for angular crystalline silica dust we see a strong increase in tensile strength in a vacuum compared to air and an even higher increase when the samples are heated in a vacuum. For the spherical silica dust samples, we find a characteristic increase in the tensile strength with decreasing particle size. The tensile strength of samples with identical particle sizes increases strongly with an increasing volume filling factor. Extrapolation of our data to a volume filling factor of 0.1 (90% porosity) shows that a tensile strength as low as 1 Pa can be reached. Conclusions. Numerical simulations show that evaporating water ice in the subsurface layers of comets can reach gas pressures of ~1 Pa. Thus, a desiccated dust layer with a 10% volume filling factor should be detachable and released into the cometary coma. Using a relation between the tensile strength and the critical fragmentation energy, we predict the break-up speed of dust aggregates in mutual collisions as a function of the volume filling factor. Furthermore, we discuss the susceptibility of the aggregates to ram pressure. These values are relevant for protoplanetary disk research and for meteoroids entering planetary atmospheres.

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.

An application of the boundary element method (BEM) to the calculation of the single-scattering properties of very complex ice crystals in the microwave and sub-millimetre regions of the electromagnetic spectrum

To improve the prediction of weather and climate models there is a need for the accurate computation of the single-scattering properties of randomly oriented complex atmospheric ice crystals. Here, we apply BEM to calculate these properties in the microwave and sub-millimetre region of the electromagnetic spectrum for the purposes of all-sky data assimilation. The properties are calculated at the frequencies of 50, 183, 243 and 664 GHz for the temperatures of −83 °C, −43 °C, and −3 °C. The particles are assumed to be complex aggregates of bullet rosettes with maximum dimensions that vary between 10 and 10,000μm. Moreover, the rosette-aggregates are constructed to follow an observed mass-dimension power law that is consistent with an ice microphysics scheme in a weather model. To solve efficiently the BEM linear matrix equation, random orientation is simulated by fixing the particle with respect to the incident plane wave with the latter rotated about the particle. This representation is shown to replicate T-matrix solutions found for hexagonal columns to within a few percent for size parameters between 0.05 and 10. We further show that we can simulate the single-scattering properties with errors less than a few percent, using only 14 and up to 302 incident waves for the smallest and largest size parameters respectively. The errors grow larger only for some of the largest size parameters considered. We find that BEM can be applied to compute accurately the scattering properties of complex ice aggregates of importance to weather and climate models.

The Macro- and Microphysical Response Characteristics of the Multicell Hailstorm Hail-Suppression Operation: Case Study

Abstract This study analyzed the macro- and microphysical response characteristics of a typical multicell hailstorm after seeding on 27 April 2019 in Weining, China, using X-band dual-polarization radar (YLD1-D) data. An improved X-pol hydrometeor identification algorithm was employed for hydrometeor identification. According to the diffusion of the seeding agents, the seeded hailstorm was graded into three study regions, and the evolution of the seeded hailstorm was divided into four periods. The response characteristics of the seeded hailstorm in each region and period were compared and analyzed. The results show that 1) macroscopically, the decrease in the reflectivity and the height of strong echo mainly occurred in the seeded period, whereas the decrease in the echo top and the height of the storm was mainly in the postseeded period; the echo height variation of the unseeded hailstorm is obviously different from that of the seeded hailstorm; and 2) from the microscopic perspective, the decrease in low-density graupel and supercooled water and the increase in ice crystals and aggregates in the seeded region mainly occurred in the seeded period, which was consistent with the time required for the “benefit competition” after the silver iodide completed nucleation. When compared with the seeded region, the hydrometeors in the unseeded region had an opposite trend (or an in-phase trend with an obviously lower changing rate), which further indicated the impact of the artificial ice nuclei on microphysical processes in the seeded region. For hailstorms with a high content of supercooled droplets and graupel, the key mechanisms of hail suppression are “cloud water glaciation,” “beneficial competition,” and “early rainout.”

A Thermal Insulation and UV-Resistant System based on Aerogel for Settlements on the Moon and Mars

Abstract: This paper presents a novel design for a habitable outpost on both the Moon and Mars that leverages the exceptional properties of aerogel - a material composed of 99% air, offering outstanding thermal insulation and UV protection. The outpost is engineered to withstand extreme temperature variations on Mars (-153°C to 20°C) and the Moon (-173°C to 127°C) using a single material. Protection against harmful UV rays is crucial for sustaining human life as prolonged exposure can lead to DNA damage and cancer. To safeguard the aerogel layer from meteoroids, Martian soil is utilized on Mars, and lunar soil on the Moon. The interior features a fiber composite layer, supported by a mechanical structure made from Martian concrete (ice, calcium oxide, and Martian aggregate) or lunar concrete (ice, calcium oxide, and lunar aggregate). The composite can be assembled on Earth with an inflatable system or sent to Mars in multiple missions for on-site assembly. Light transmission with radiation resistance is achieved using translucent silica aerogel filters for glass windows. The paper also includes heat transfer calculations between the internal and external environments of the habitat, as well as strength assessments of the habitat, taking into account the insulation and UV resistance provided by the protective soil layer.

Effect of active ice nucleation bacteria on freezing and the properties of surimi during frozen storage

The effects of active ice nucleation bacteria (INB, Pseudomonas syringae) on freezing, ice crystal formation, and aggregation, and oxidation of surimi from Talang queenfish (Scomberoides commersonnianus) during frozen storage were investigated. The shortest freezing time (225 min) and the highest onset temperature (−7.0 °C), as determined by differential scanning calorimetry (DSC), was found for surimi with 106 colony-forming units of INB mL−1 100−1 g (INB c1). The surimi showed better structure with the lowest inter-fiber space along with finer and more homogenous myofibrillar proteins (MP) surface morphology and a lower root-mean-square (Rq, 142 nm) from atomic force microscopy (AFM) after 90 days of storage at −18 °C, which was associated with the highest ζ-potential (−9.0 mV) than the control (−6.2 mV) which reflected a lowered MP aggregation behavior. Compared to the control, protein carbonyls in surimi with INB c1 decreased significantly, while showing a lower decrease in total sulfhydryl groups (P < 0.05). Overall, INB c1shortened the freezing time and increased freezing rate, while decreasing oxidation and aggregation of surimi proteins.

Improvements of the Double-Moment Bulk Cloud Microphysics Scheme in the Nonhydrostatic Icosahedral Atmospheric Model (NICAM)

Abstract This study revises the collisional growth, heterogeneous ice nucleation, and homogeneous ice nucleation processes in a double-moment bulk cloud microphysics scheme implemented in the Nonhydrostatic Icosahedral Atmospheric Model (NICAM). The revised cloud microphysical processes are tested by 10-day global simulations with a horizontal resolution of 14 km. It is found that both the aggregation of cloud ice with smaller diameters and the graupel production by riming are overestimated in the current schemes. A new method that numerically integrates the collection kernel solves this issue, and consequently, the lifetime of cloud ice is reasonably extended in reference to satellite observations. In addition, the results indicate that a reduction in graupel modulates the convective intensity, particularly in intense rainfall systems. The revision of both heterogeneous and homogeneous ice nucleation significantly increases the production rate of cloud ice number concentration. With these revisions, the new version of the cloud microphysics scheme successfully improves outgoing longwave radiation, particularly over the intertropical convergence zone, in reference to satellite observations. Therefore, the revisions are beneficial for both long-term climate simulations and representing the structure of severe storms. Significance Statement Very high-resolution global atmospheric models have been developed to simultaneously address global climate and regional weather. In general, cloud microphysics schemes used in such global models are introduced from regional weather forecasting models to realistically represent mesoscale cloud systems. However, a cloud microphysics scheme that was originally developed with the aim of weather forecasting can cause unexpected errors in global climate simulations because such a cloud microphysics scheme is not designed for interdisciplinary usage across spatiotemporal scales. This study focuses on systematic model biases in evaluating the terminal velocity of ice cloud particles and proposes a method to accurately calculate the growth rate of ice cloud particles. Improvements in ice cloud modeling successfully reduce model biases in the global energy budget. In addition, the internal structure of intense rainfall systems is modified using the new cloud model. Therefore, improvements in ice cloud modeling could further increase the reliability of weather forecasting, seasonal prediction, and climate projection.

Ice microphysical processes in the dendritic growth layer: a statistical analysis combining multi-frequency and polarimetric Doppler cloud radar observations

Abstract. The dendritic growth layer (DGL), defined as the temperature region between −20 and −10 ∘C, plays an important role for ice depositional growth, aggregation and potentially secondary ice processes. The DGL has been found in the past to exhibit specific observational signatures in polarimetric and vertically pointing radar observations. However, consistent conclusions about their physical interpretation have often not been reached. In this study, we exploit a unique 3-months dataset of mid-latitude winter clouds observed with vertically pointing triple-frequency (X-, Ka-, W-band) and polarimetric W-band Doppler radars. In addition to standard radar moments, we also analyse the multi-wavelength and polarimetric Doppler spectra. New variables, such as the maximum of the spectral differential reflectivity (ZDR) (sZDRmax), allows us to analyse the ZDR signal of asymmetric ice particles independent of the presence of low ZDR producing aggregates. This unique dataset enables us to investigate correlations between enhanced aggregation and evolution of small ice particles in the DGL. For this, the multi-frequency observations are used to classify all profiles according to their maximum average aggregate size within the DGL. The strong correlation between aggregate class and specific differential phase shift (KDP) confirms the expected link between ice particle concentration and aggregation. Interestingly, no correlation between aggregation class and sZDRmax is visible. This indicates that aggregation is rather independent of the aspect ratio and density of ice crystals. A distinct reduction of mean Doppler velocity in the DGL is found to be strongest for cases with largest aggregate sizes. Analyses of spectral edge velocities suggest that the reduction is the combined result of the formation of new ice particles with low fall velocity and a weak updraft. It appears most likely that this updraft is the result of latent heat released by enhanced depositional growth. Clearly, the strongest correlations of aggregate class with other variables are found inside the DGL. Surprisingly, no correlation between aggregate class and concentration or aspect ratio of particles falling from above into the DGL could be found. Only a weak correlation between the mean particle size falling into the DGL and maximum aggregate size within the DGL is apparent. In addition to the correlation analysis, the dataset also allows study of the evolution of radar variables as a function of temperature. We find the ice particle concentration continuously increasing from −18 ∘C towards the bottom of the DGL. Aggregation increases more rapidly from −15 ∘C towards warmer temperatures. Surprisingly, KDP and sZDRmax are not reduced by the intensifying aggregation below −15 ∘C but rather reach their maximum values in the lower half of the DGL. Also below the DGL, KDP and sZDRmax remain enhanced until −4 ∘C. Only there, additional aggregation appears to deplete ice crystals and therefore reduce KDP and sZDRmax. The simultaneous increase of aggregation and particle concentration inside the DGL necessitates a source mechanism for new ice crystals. As primary ice nucleation is expected to decrease towards warmer temperatures, secondary ice processes are a likely explanation for the increase in ice particle concentration. Previous laboratory experiments strongly point towards ice collisional fragmentation as a possible mechanism for new particle generation. The presence of an updraft in the temperature region of maximum depositional growth might also suggest an important positive feedback mechanism between ice microphysics and dynamics which might further enhance ice particle growth in the DGL.

A Characterization of Clouds and Precipitation Over the Southern Ocean From Synoptic to Micro Scales During the CAPRICORN Field Campaigns

AbstractThe persistent Southern Ocean (SO) shortwave radiation biases in climate models and reanalyses have been associated with the poor representation of clouds, precipitation, aerosols, the atmospheric boundary layer, and their intrinsic interactions. Capitalizing on shipborne observations collected during the Clouds Aerosols Precipitation Radiation and atmospheric Composition Over the Southern Ocean 2016 and 2018 field campaigns, this research investigates and characterizes cloud and precipitation processes from synoptic to micro scales. Distinct cloud and precipitation regimes are found to correspond to the seven thermodynamic clusters established using a K‐means clustering technique, while less distinctions are evident using the cyclone and (cold) front compositing methods. Cloud radar and disdrometer data reveal that light precipitation is common over the SO with higher intensities associated with cyclonic and warm frontal regions. Multiple lines of evidence suggest the presence of diverse microphysical features in several cloud regimes, including the likely dominance of ice aggregation in deep precipitating clouds. Signatures of mixed phase, and in some cases, riming were detected in shallow convective clouds away from the frontal conditions. Two of the K‐means clusters with contrasting cloud and precipitation properties are observed over the high‐latitude SO and coastal Antarctica, suggesting distinct physical processes therein. Through a single case study, in‐situ and remote‐sensing data collected by an overflight of the Southern Ocean Clouds Radiation Aerosol Transport Experimental Study were also evaluated and complement the ship‐based analysis.

Ice Aggregation in Low‐Level Mixed‐Phase Clouds at a High Arctic Site: Enhanced by Dendritic Growth and Absent Close to the Melting Level

AbstractLow‐level mixed‐phase clouds (MPCs) occur extensively in the Arctic, and are known to play a key role for the energy budget. While their characteristic structure is nowadays well understood, the significance of different precipitation‐formation processes, such as aggregation and riming, is still unclear. Using a 3‐year data set of vertically pointing W‐band cloud radar and K‐band Micro Rain Radar (MRR) observations from Ny‐Ålesund, Svalbard, we statistically assess the relevance of aggregation in Arctic low‐level MPCs. Combining radar observations with thermodynamic profiling, we find that larger snowflakes (mass median diameter larger than 1 mm) are predominantly produced in low‐level MPCs whose mixed‐phase layer is at temperatures between −15 and −10°C. This coincides with the temperature regime known for favoring aggregation due to growth and subsequent mechanical entanglement of dendritic crystals. Doppler velocity information confirms that these signatures are likely due to enhanced ice particle growth by aggregation. Signatures indicative of enhanced aggregation are however not distributed uniformly across the cloud deck, and only observed in limited regions, suggesting a link with dynamical effects. Low Doppler velocity values further indicate that significant riming of large particles is unlikely at temperatures colder than −5°C. Surprisingly, we find no evidence of enhanced aggregation at temperatures warmer than −5°C, as is typically observed in deeper cloud systems. Possible reasons are discussed, likely connected to the ice habits that form at temperatures warmer than −10°C, increased riming, and lack of particle populations characterized by broader size distributions precipitating from higher altitudes.

Effects of secondary ice processes on a stratocumulus to cumulus transition during a cold-air outbreak

The representation of boundary layer clouds during marine Cold-Air Outbreaks (CAO) remains a great challenge for weather prediction models. Recent studies have shown that the representation of the transition from closed stratocumulus clouds to convective cumulus open cells largely depends on microphysical and precipitation processes, which secondary ice production (SIP) may strongly modulate. In this study we use the Weather Research and Forecasting model to investigate the impact of the most well-known SIP mechanisms (Hallett-Mossop, mechanical break-up upon collisions between ice particles and drop-shattering) on a CAO case observed north of the United Kingdom in 2013. While Hallett-Mossop is the only SIP process extensively implemented in atmospheric models, our results indicate that the other two SIP mechanisms are also favored in the examined conditions. Activation of drop-shattering and especially collisional break-up can result in enhanced riming, ice depositional growth and/or ice aggregation. The first two processes quicken liquid depletion in the stratocumulus cloud, while along with aggregation, they enhance precipitation. The increased precipitation results in enhanced evaporation/sublimation in the sub-cloud layer, promoting boundary-layer decoupling, which further accelerates the onset of the stratocumulus break-up. However, the strong sensitivity to the expression of terminal velocity of the precipitating particles and the rimed fraction of cloud ice/snow suggests that the robust implementation of SIP to improve CAO predictions requires data from a large number of CAO events.

The Ice Particle and Aggregate Simulator (IPAS). Part III: Verification and Analysis of Ice–Aggregate and Aggregate–Aggregate Collection for Microphysical Parameterization

Abstract The Ice Particle and Aggregate Simulator (IPAS) is used to theoretically represent the aggregation process of ice crystals. Aggregates have a variety of formations based on initial ice particle size, shape, and falling orientation, all of which influence water phase partitioning. Aggregate dimensional properties and density changes are calculated for monomer–monomer (MON–MON), monomer–aggregate (MON–AGG), and aggregate–aggregate (AGG–AGG) collection to be used by ice-microphysical models for improvement in aggregation parameterizations. Aggregates are chosen from a database of 9 744 000 preformed combinations to be further collected (see Part II). AGG–AGG collection results in more extreme and a smaller range of aggregate aspect ratios than MON–AGG collection. A majority of aggregates are closer to prolate than oblate spheroids, regardless of collection type, except for quasi-horizontally oriented particles that have extreme aspect ratios to begin with. MON–AGG collection frequently results in an increase in density upon collection, whereas MON–MON and AGG–AGG collection almost always result in particle density decreases, with extreme reductions near 99% for MON–MON collection. MON–MON collection results in the greatest decreases in density but then quickly becomes unaffected by the addition of more monomers due to inherent size differences between monomers and aggregates. Finally, a holistic analysis to in situ observations of cloud particle images is presented. IPAS 2D aspect ratios surround a median value of 0.6 and closely follow that of previous studies while varying by no more than ≈12% on average from observed aggregates.

The Ice Particle and Aggregate Simulator (IPAS). Part II: Analysis of a Database of Theoretical Aggregates for Microphysical Parameterization

Abstract Bulk ice-microphysical models parameterize the dynamic evolution of ice particles from advection, collection, and sedimentation through a cloud layer to the surface. Frozen hydrometeors can grow to acquire a multitude of shapes and sizes, which influence the distribution of mass within cloud systems. Aggregates, defined herein as the collection of ice particles, have a variety of formations based on initial ice particle size, shape, falling orientation, and the number of particles that collect. This work focuses on using the Ice Particle and Aggregate Simulator (IPAS) as a statistical tool to repetitively collect ice crystals of identical properties to derive bulk aggregate characteristics. A database of 9 744 000 aggregates is generated with resulting properties analyzed. After 150 single ice crystals (monomers) collect, the most extreme aggregate aspect ratio calculations asymptote toward and ϕca ≈ 0.50 for aggregates composed of quasi-horizontally oriented and randomly oriented monomers, respectively. The results presented are largely consistent with both a previous theoretical study and estimates derived from ground-based observations from two different geographic locations. Particle falling orientation highly influences newly formed aggregate aspect ratios from the collection of particles with extreme aspect ratios; quasi-horizontally oriented particles can produce aggregate aspect ratios an order of magnitude more extreme than randomly oriented particles but can also produce near-spherical aggregates as the number of monomers comprising the aggregate reach approximately 100. Finally, a majority of collections result in aggregates that are closer to prolate than oblate spheroids.

Can changes in deformation regimes be inferred from crystallographic preferred orientations in polar ice?

Abstract. Creep due to ice flow is generally thought to be the main cause for the formation of crystallographic preferred orientations (CPOs) in polycrystalline anisotropic ice. However, linking the development of CPOs to the ice flow history requires a proper understanding of the ice aggregate's microstructural response to flow transitions. In this contribution the influence of ice deformation history on the CPO development is investigated by means of full-field numerical simulations at the microscale. We simulate the CPO evolution of polycrystalline ice under combinations of two consecutive deformation events up to high strain, using the code VPFFT (visco-plastic fast Fourier transform algorithm) within ELLE. A volume of ice is first deformed under coaxial boundary conditions, which results in a CPO. The sample is then subjected to different boundary conditions (coaxial or non-coaxial) in order to observe how the deformation regime switch impacts the CPO. The model results indicate that the second flow event tends to destroy the first, inherited fabric with a range of transitional fabrics. However, the transition is slow when crystallographic axes are critically oriented with respect to the second imposed regime. Therefore, interpretations of past deformation events from observed CPOs must be carried out with caution, particularly in areas with complex deformation histories.

Highly Productive Ice Algal Mats in Arctic Melt Ponds: Primary Production and Carbon Turnover

Arctic summer sea ice extent is decreasing and thinning, forming melt ponds that cover more than 50% of the sea ice area during the peak of the melting season. Despite of this, ice algal communities in melt ponds are understudied and so are their contribution to the Arctic Ocean primary production and carbon turnover. While melt ponds have been considered as low productive, recent studies suggest that accumulated ice algal potentially facilitate high and yet overlooked rates of carbon turnover. Here we report on ice algal communities forming dense mats not previously described, collected from melt ponds in the northern Barents Sea in July. We document on distinct layered and brown colored mats with high carbon assimilation and net primary production rates compared to ice algal communities and aggregates, in fact comparable to benthic microalgae at temperate tidal flats. Rates of gross and net primary production, as well as community respiration rates were obtained from oxygen micro profiling, and carbon assimilation calculations were supported by 14C incubations, pigment analysis and light microscopy examinations. The melt pond algal mats consisted of distinct colored layers and differed from aggregates with a consisted layered structure. We accordingly propose the term melt pond algal mats, and further speculate that these dense ice algal mats may provide an important yet overlooked source of organic carbon in the Arctic food-web. A foodweb component likely very sensitive to climate driven changes in the Arctic Ocean and pan-Arctic seas.

Erratum: [Collisional properties of cm-sized high-porosity ice and dust aggregates and their applications to early planet formation

Erratum: [Collisional properties of cm-sized high-porosity ice and dust aggregates and their applications to early planet formation

A novel method for the quantitative morphometric characterization of soluble salts on volcanic ash

Formation of soluble sulfate and halide salts on volcanic ash particles via syn-eruptive interactions between ash surfaces and magmatic gases is a ubiquitous phenomenon in explosive eruptions. Surficial salts may be rapidly mobilized into their depositional environment undermining the quality of drinking water, harming aquatic life, and damaging soil and vegetation. Assessment of the potential for salt formation on ash and related environmental impacts have been based almost exclusively on bulk mineralogical or chemical analyses of ash; similarly, quantification of surficial salts has been made via leachate analysis only. However, it is the ash surface state and salt crystal properties that exert the predominant control on its reactivity, thus in determining their immediate environmental impact. Here, using scanning electron microscope (SEM) images, we present a novel image analysis protocol for the quantitative characterization of surficial salts, together with chemical analyses of resulting leachates. As volcanic ash proxies, we used synthetic rhyolitic glass particles (with systematic variations in FeOT and CaO content) and a crushed obsidian. Using an ash-gas reactor, we artificially surface-loaded samples with CaSO4 and NaCl crystals, the most common crystal phases found on volcanic ash surfaces. Analogous variations were found using both methods: for CaSO4 crystals, higher temperature treatments or increasing FeOT content at the same temperature led to higher concentrations of salt leachate and higher salt volumes; unexpectedly, increasing the CaO content caused only a minor increase in salt formation. In addition to bulk salt formation, morphometric results provided insight into formation processes, nucleation and growth rates, and limiting factors for salt formation. Higher temperatures increased CaSO4 crystal size and surface coverage which we infer to result from higher element mobility in the glasses driving crystal growth. Increasing FeOT content of the glasses yielded increased salt surface coverage and leachate concentrations, but decreased crystal size (i.e., the salt number density increased). This latter effect likely relates to the role of iron as an electron-donor to charge balance salt-forming cation migration to the ash surface, indicating the importance of iron in determining surface reaction site density and, consequently, environmental reactivity. The controlling roles of ash composition and temperature on salt formation observed here can improve estimations for surface salt formation, volatile scavenging, and environmental impact for eruptions producing glass-rich ash. Our characterization protocol can therefore become a useful tool for the investigation of solid–gas reactions for terrestrial and planetary processes, and it also appears to be a powerful complement to research into atmospheric processes mediated by ash surfaces, such as ash aggregation and nucleation of water or ice on ash.

Collisional properties of cm-sized high-porosity ice and dust aggregates and their applications to early planet formation

ABSTRACT In dead zones of protoplanetary discs, it is assumed that micrometre-sized particles grow Brownian, sediment to the mid-plane and drift radially inward. When collisional compaction sets in, the aggregates collect slower and therefore dynamically smaller particles. This sedimentation and growth phase of highly porous ice and dust aggregates is simulated with laboratory experiments in which we obtained mm- to cm-sized ice aggregates with a porosity of 90 per cent as well as cm-sized dust agglomerates with a porosity of 85 per cent. We modelled the growth process during sedimentation in an analytical calculation to compute the agglomerate sizes when they reach the mid-plane of the disc. In the mid-plane, the dust particles form a thin dense layer and gain relative velocities by, e.g. the streaming instability or the onset of shear turbulence. To investigate these collisions, we performed additional laboratory drop tower experiments with the high-porosity aggregates formed in the sedimentary-growth experiments and determined their mechanical parameters, including their sticking threshold velocity, which is important for their further collisional evolution on their way to form planetesimals. Finally, we developed a method to calculate the packing-density-dependent fundamental properties of our dust and ice agglomerates, the Young’s modulus, the Poisson ratio, the shear viscosity, and the bulk viscosity from compression measurements. With these parameters, it was possible to derive the coefficient of restitution which fits our measurements. In order to physically describe these outcomes, we applied a collision model. With this model, predictions about general dust-aggregate collisions are possible.

Retrieving microphysical properties of concurrent pristine ice and snow using polarimetric radar observations

Abstract. Ice and mixed-phase clouds play a key role in our climate system because of their strong controls on global precipitation and radiation budget. Their microphysical properties have been characterized commonly by polarimetric radar measurements. However, there remains a lack of robust estimates of microphysical properties of concurrent pristine ice and aggregates because larger snow aggregates often dominate the radar signal and mask contributions of smaller pristine ice crystals. This paper presents a new method that separates the scattering signals of pristine ice embedded in snow aggregates in scanning polarimetric radar observations and retrieves their respective abundances and sizes for the first time. This method, dubbed ENCORE-ice, is built on an iterative stochastic ensemble retrieval framework. It provides the number concentration, ice water content, and effective mean diameter of pristine ice and snow aggregates with uncertainty estimates. Evaluations against synthetic observations show that the overall retrieval biases in the combined total microphysical properties are within 5 % and that the errors with respect to the truth are well within the retrieval uncertainty. The partitioning between pristine ice and snow aggregates also agrees well with the truth. Additional evaluations against in situ cloud probe measurements from a recent campaign for a stratiform cloud system are promising. Our median retrievals have a bias of 98 % in the total ice number concentration and 44 % in the total ice water content. This performance is generally better than the retrieval from empirical relationships. The ability to separate signals of different ice species and to provide their quantitative microphysical properties will open up many research opportunities, such as secondary ice production studies and model evaluations for ice microphysical processes.