Search NASA⌕ Search

SEARCH · Search NASA

Results for “ice particle”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

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

Abstract Ice particle terminal fall velocity ( V t ) is fundamental for determining microphysical processes, yet remains extremely challenging to measure. Current theoretical best estimates of V t are functions of Reynolds number. The Reynolds number is related to the Best number, which is a function of ice particle mass, area ratio ( A r ), and maximum dimension ( D max ). These estimates are not conducive for use in most models since model parameterizations often take the form , where ( α , β ) depend on habit and D max . A previously developed framework is used to determine surfaces of equally plausible ( α , β ) coefficients whereby ice particle size/shape distributions are combined with V t best estimates to determine mass- ( V M ) or reflectivity-weighted ( V Z ) velocities that closely match parameterized V M ,SD or V Z ,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 A r , D max , and size distribution N ( D ) affect V M or V Z . 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 A r assumptions or D max estimates. The combined uncertainty between A r , D max , 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.

Meteorology & Atmospheric Sciences↗

The Impacts of Single-Scattering and Microphysical Properties of Ice Particles Smaller Than 100 µm on the Bulk Radiative Properties of Tropical Cirrus

There are large uncertainties in the single-scattering (i.e., morphologies) and microphysical (i.e., concentrations) properties of ice particles whose size are less than ~100 µm. Insufficient resolutions of the most advanced cloud probes (e.g., cloud particle imager) cannot resolve the micrometer-scale morphologies of small ice particles. Further, the shattering of large ice particles on probes’ inlets or tips causes uncertainties in the measurement of the concentrations of small ice particles. These uncertainties have large impacts on the single-scattering and microphysical properties of small ice particles that are utilized to quantify the bulk radiative properties of cirrus. In this study, the impacts of uncertainties in the morphologies and concentrations of small ice particles on the bulk radiative properties of tropical cirrus were calculated using measurements acquired during the Tropical Warm Pool-International Cloud Experiment. Five different models (i.e., budding Buckyball, Chebyshev particle, droxtal, Gaussian random sphere, and sphere) that represent the shapes of small ice particles were used to calculate the single-scattering properties. The bulk radiative properties, average phase-function ($\overline{P_{11}}$), and average asymmetry parameter ($\overline{g}$) were computed by combining the measured size/habit distributions and the calculated single-scattering properties of ice particles. The impacts of the selection of varying morphologies of small particles on the bulk radiative properties were quantified. For these calculations, the possible range of the concentrations of small ice particles which depend on the degree of shattered large particles were also used. The impacts of varying the single-scattering properties of small ice particles on the bulk radiative properties were the largest in the upper parts of cirrus (T < –60 °C), while they were the smallest in the lower parts of cirrus (–45 < T < –30 °C). The impacts of uncertainties in the concentrations of small ice particles on the bulk radiative properties were largest in the lower parts of cirrus (–45 < T < –30 °C), whereas they were smallest in the upper parts of cirrus (T < –60 °C). The effect of shattering was maximum in the lower parts of cirrus, whilst it was minimum in the upper parts of cirrus. The combined impacts of uncertainties in the single-scattering (i.e., morphologies) and microphysical (i.e., concentrations) properties of small ice particles revealed variations of up to 11.2% (127.1%; 67.3%) of the integrated intensity in the forward (sideward; backward) angles in $\overline{P_{11}}$ and a corresponding change in $\overline{g}$ by up to 12.61%.

54 ENVIRONMENTAL SCIENCES↗

Project ICEBall: Cryo-SEM images of Captured Cirrus Ice Particles. ARM SGP, October 21-November 1, 2021

This dataset includes a unique set of cryo-SEM images of captured cirrus ice particle from ARM Project ICEBall, which was conducted at and around the Southern Great Plains site from October 21- November 1, 2021. The instrument used for particle collection, Ice Crystal Encapsulation by Ball (ICE-Ball), is described in Magee et al. 2021, 'Captured cirrus ice particles in high definition", Atmos. Chem. Phys. The ice particles were captured on balloon flights directly from cirrus cloud formations between 7-12 km on seven ICEBall flights on these dates: October 21, 23, 24, 25, 26, 31, and Nov. 1.

54 ENVIRONMENTAL SCIENCES↗

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.

54 ENVIRONMENTAL SCIENCES↗

Secondary ice production during the break-up of freezing water drops on impact with ice particles

Abstract. We provide the first dedicated laboratory study of collisions of supercooled water drops with ice particles as a secondary ice production mechanism. We experimentally investigated collisions of supercooled water drops (∼ 5 mm in diameter) with ice particles of a similar size (∼ 6 mm in diameter) placed on a glass slide at temperatures >-12 ∘C. Our results showed that secondary drops were generated during both the spreading and retraction phase of the supercooled water drop impact. The secondary drops generated during the spreading phase were emitted too fast to quantify. However, quantification of the secondary drops generated during the retraction phase with diameters >0.1 mm showed that 5–10 secondary drops formed per collision, with approximately 30 % of the secondary drops freezing over a temperature range between −4 and −12 ∘C. Our results suggest that this secondary ice production mechanism may be significant for ice formation in atmospheric clouds containing large supercooled drops and ice particles.

54 ENVIRONMENTAL SCIENCES↗

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 ϕ ca ≈ 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.

54 ENVIRONMENTAL SCIENCES↗

Next-Generation Video Ice Particle Sampler Field Campaign Report

The next-generation video ice particle sampler (ngVIPS) was operated on the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s tethered balloon system (TBS) during the IFFExO (Ice Fog Field Experiment at Oliktok Point) project in November, 2020. The purpose of the project was to study ice fog microphysics and the environmental conditions during ice fog to enable better predictions during low-visibility conditions. This project was conducted at the site of the third ARM Mobile Facility (AMF3) at Oliktok Point, Alaska. Among a suite of other instruments, the ngVIPS was operated to observe atmospheric ice particles.

47 OTHER INSTRUMENTATION↗

Improved modeling of in-ice particle showers for IceCube event reconstruction

The IceCube Neutrino Observatory relies on an array of photomultiplier tubes to detect Cherenkov light produced by charged particles in the South Pole ice. IceCube data analyses depend on an in-depth characterization of the glacial ice, and on novel approaches in event reconstruction that utilize fast approximations of photoelectron yields. Here, a more accurate model is derived for event reconstruction that better captures our current knowledge of ice optical properties. When evaluated on a Monte Carlo simulation set, the median angular resolution for in-ice particle showers improves by over a factor of three compared to a reconstruction based on a simplified model of the ice. The most substantial improvement is obtained when including effects of birefringence due to the polycrystalline structure of the ice. When evaluated on data classified as particle showers in the high-energy starting events sample, a significantly improved description of the events is observed.

47 OTHER INSTRUMENTATION↗

Global Simulations Suggest Biomass Burning Aerosol Emissions From Grassland Fires Could Be Important Ice Nucleating Particles

Ice nucleating particles (INP) capable of nucleating ice crystals via immersion freezing at temperatures above approximately −35°C may strongly influence cloud glaciation, with implications for global precipitation and climate feedback. In addition to mineral dust, soil dust, and marine organics, laboratory and field measurements suggest biomass burning aerosols (BBA) can act as immersion-mode INP between around −30°C and −15°C. However, the contribution of BBA to the global INP budget remains poorly understood due to poor knowledge of which fuels yield INPs, uncertainties in global coverage of those fuels, and unknown size distributions of the INPs in the BBA. Nonetheless, with some understanding of these uncertainties from sensitivity studies, the relative importance of ice nucleation activity of BBA compared to other INP sources can be quantified. In this work, we investigate the potential global importance of BBA as INP using a global aerosol-climate model, specifically the UK Met Office Unified Model (UM). We evaluate the model using field campaign data sets. We examine potential uncertainties in fuel types and particle sizes on BBA-based INP concentrations. Averaged over June–September between 15°S and 50°S, BBA is a more important INP than dust and marine INP about 30% of the time at altitudes with temperatures between −30°C and −20°C. Our simulations therefore suggest BBA INPs may be at least as important as mineral dust and marine INP over the atmospheric regions and seasons where grassland fires are frequent.

Gohil, Kanishk [Carnegie Mellon University, Pittsb↗

Investigating the Evolution of Ice Particle Distributions in Mixed-Phase Clouds

The goal of this project is to conduct modeling studies that focus on the processes that control the macrophysical and microphysical properties of mixed phase clouds, such as the partitioning of water phase and the processes that promote precipitation and govern cloud evolution. The process specific to this project is the collection of vapor-grown non-spherical ice crystals and snow hydrometeors through aggregation, as uncertainty remains in the evolution of particle properties as they aggregate. To aid in the understanding of ice particle evolution from pristine monomers to aggregates, the aggregation process is depicted using an offline simulator for ice crystal collection, namely the Ice Particle and Aggregate Simulator (IPAS). Of particular interest in the context of this work is the influence of monomer habit on aggregation and subsequently on cloud microphysical structure. This overarching goal has been completed by conducting modeling studies using the Adaptive Habit Model (AHM) in mixed-phase cloud systems, which predicts and evolves ice shape. While the AHM is designed with physical detail in mind, those details may be lost on larger spatial or temporal scales. Hence, how the contributions of particle growth and collection control the evolution of ice particle size distributions (PSDs) and redistribute mass within the cloud and at the surface has been investigated. Analyses include microphysical sensitivity investigations that inform on future improvement capabilities of microphysical parameterizations in larger scale models. Further, improvements of processes within ice clouds have resulted from this work as the environmental processes controlling ice crystal growth, microphysical processes, and precipitation are inherently integrated within this investigation.

54 ENVIRONMENTAL SCIENCES↗

The Abundance and Sources of Ice Nucleating Particles Within Alaskan Ice Fog

Abstract The Alaskan Layered Pollution and Chemical Analysis (ALPACA) field campaign included deployment of a suite of atmospheric measurements in January–February 2022 with the goal of better understanding atmospheric processes and pollution under cold and dark conditions in Fairbanks, Alaska. We report on measurements of particle composition, particle size, ice nucleating particle (INP) composition, and INP size during an ice fog period (29 January–3 February). During this period, coarse particulate matter (PM 10 ) concentrations increased by 150% in association with a decrease in air temperature, a stronger temperature inversion, and relatively stagnant conditions. Results also show a 18%–78% decrease in INPs during the ice fog period, indicating that particles had activated into the ice fog via nucleation. Peroxide and heat treatments performed on INPs indicated that, on average, the largest contributions to the INP population were heat‐labile (potentially biological, 63%), organic (31%), then inorganic (likely dust, 6%). Measurements of levoglucosan and bulk and single‐particle composition corroborate the presence of dust and aerosols from combustion sources. Heat‐labile and organic INPs decreased during the peak period of the ice fog, indicating those were preferentially activated, while inorganic INPs increased, suggesting they remained as interstitial INPs. In general, INP concentrations were unexpectedly high in Fairbanks compared to other locations in the Arctic during winter. The fact that these INPs likely facilitated ice fog formation in Fairbanks has implications for other high latitude locations subject to the hazards associated with ice fog.

Meteorology & Atmospheric Sciences↗

A biogenic secondary organic aerosol source of cirrus ice nucleating particles

Atmospheric ice nucleating particles (INPs) influence global climate by altering cloud formation, lifetime, and precipitation efficiency. The role of secondary organic aerosol (SOA) material as a source of INPs in the ambient atmosphere has not been well defined. Here, we demonstrate the potential for biogenic SOA to activate as depositional INPs in the upper troposphere by combining field measurements with laboratory experiments. Ambient INPs were measured in a remote mountaintop location at –46°C and an ice supersaturation of 30% with concentrations ranging from 0.1 to 70 L –1 . Concentrations of depositional INPs were positively correlated with the mass fractions and loadings of isoprene-derived secondary organic aerosols. Compositional analysis of ice residuals showed that ambient particles with isoprene-derived SOA material can act as depositional ice nuclei. Laboratory experiments further demonstrated the ability of isoprene-derived SOA to nucleate ice under a range of atmospheric conditions. We further show that ambient concentrations of isoprene-derived SOA can be competitive with other INP sources. This demonstrates that isoprene and potentially other biogenically-derived SOA materials could influence cirrus formation and properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗