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Carl G. Schmitt, Martin Schnaiter, Andrew J. Heymsfield, Ping Yang, Edwin Hirst, and Aaron Bansemer

Abstract

A reliable understanding of the microphysical properties of ice particles in atmospheric clouds is critical for assessing cloud radiative forcing effects in climate studies. Ice particle microphysical properties such as size, shape, and surface roughness all have substantial effects on the single-scattering characteristics of the particles. A recently developed ice particle probe, the Small Ice Detector-3 (SID-3), measures the two-dimensional near-forward light-scattering patterns of sampled ice particles. These scattering patterns provide a wealth of information for understanding the microphysical and radiative characteristics of ice particles. The SID-3 was operated successfully on 12 aircraft flights during the NASA Midlatitude Airborne Cirrus Properties Experiment (MACPEX) field campaign in April 2011. In this study, SID-3 measurements are used to investigate the frequency of occurrence of a number of ice particle properties observed during MACPEX. Individual scattering patterns (7.5°–23°) are used to infer properties of the observed particles as well as to calculate partial scattering functions (PSFs) for ensembles of particles in the measured size range (~5–100 μm). PSFs are compared to ray-tracing-based phase functions to infer additional properties of the particles. Two quantitative values—halo ratio and steepness ratio—are used to characterize PSFs. The MACPEX dataset suggests that most atmospheric ice particles have rough surfaces or are complex in nature. PSFs calculated for particles that were characterized as having smooth surfaces also appeared to more closely resemble rough crystal PSFs. PSFs measured with SID-3 compare well with those calculated for droxtals with rough surfaces.

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Sergey Y. Matrosov, Carl G. Schmitt, Maximilian Maahn, and Gijs de Boer

Abstract

A remote sensing approach to retrieve the degree of nonsphericity of ice hydrometeors using scanning polarimetric Ka-band radar measurements from a U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program cloud radar operated in an alternate transmission–simultaneous reception mode is introduced. Nonsphericity is characterized by aspect ratios representing the ratios of particle minor-to-major dimensions. The approach is based on the use of a circular depolarization ratio (CDR) proxy reconstructed from differential reflectivity Z DR and copolar correlation coefficient ρ linear polarization measurements. Essentially combining information contained in Z DR and ρ , CDR-based retrievals of aspect ratios are fairly insensitive to hydrometeor orientation if measurements are performed at elevation angles of around 40°–50°. The suggested approach is applied to data collected using the third ARM Mobile Facility (AMF3), deployed to Oliktok Point, Alaska. Aspect ratio retrievals were also performed using Z DR measurements that are more strongly (compared to CDR) influenced by hydrometeor orientation. The results of radar-based retrievals are compared with in situ measurements from the tethered balloon system (TBS)-based video ice particle sampler and the ground-based multiangle snowflake camera. The observed ice hydrometeors were predominantly irregular-shaped ice crystals and aggregates, with aspect ratios varying between approximately 0.3 and 0.8. The retrievals assume that particle bulk density influencing (besides the particle shape) observed polarimetric variables can be deduced from the estimates of particle characteristic size. Uncertainties of CDR-based aspect ratio retrievals are estimated at about 0.1–0.15. Given these uncertainties, radar-based retrievals generally agreed with in situ measurements. The advantages of using the CDR proxy compared to the linear depolarization ratio are discussed.

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Carl G. Schmitt, Kara Sulia, Zachary J. Lebo, Andrew J. Heymsfield, Vanessa Przybyo, and Paul Connolly

Abstract

The terminal velocity (V t) of ice hydrometeors is of high importance to atmospheric modeling. V t is governed by the physical characteristics of a hydrometeor, including mass and projected area, as well as environmental conditions. When liquid hydrometeors coalesce to form larger hydrometeors, the resulting hydrometeor can readily be characterized by its spherical or near-spherical shape. For ice hydrometeors, it is more complicated because of the variability of ice shapes possible in the atmosphere as well as the inherent randomness in the aggregation process, which leads to highly variable characteristics. The abundance of atmospheric processes affecting ice particle dimensional characteristics creates potential for highly variable V t for ice particles that are predicted or measured to be of the “same size.” In this article we explore the variability of ice hydrometeor V t both theoretically and through the use of experimental observations. Theoretically, the variability in V t is investigated by analyzing the microphysical characteristics of randomly aggregated hexagonal shapes. The modeled dimensional characteristics are then compared to aircraft probe measurements to constrain the variability in atmospheric ice hydrometeor V t. Results show that the spread in V t can be represented with Gaussian distributions relative to a mean. Variability expressed as the full width at half maximum of the normalized Gaussian probability distribution function is around 20%, with somewhat higher values associated with larger particle sizes and warmer temperatures. Field campaigns where mostly convective clouds were sampled displayed low variability, while Arctic and midlatitude winter campaigns showed broader V t spectra.

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Vanessa M. Przybylo, Kara J. Sulia, Carl G. Schmitt, Zachary J. Lebo, and William C. May

Abstract

Aggregation, the process by which two or more ice particles attach to each other, is typically observed in clouds that span a range of temperatures and is influenced by the crystal shape (habit). In this study, the resulting characteristics of ice–ice two-monomer aggregation is investigated, which is expected to improve microphysical parameterizations through more precise aggregate characteristics and in turn better predict the rate of aggregation and snow development. A systematic way to determine the aspect ratio of the aggregate was developed, which takes into account the expected falling orientations, overlap of each monomer, and any contact angle that may form through so-called constrained randomization. Distributions were used to obtain the most frequent aspect ratio, major axis, and minor axis of aggregated particles with respect to the monomer aspect ratio. Simulations were completed using the Ice Particle and Aggregate Simulator (IPAS), a model that uses predefined three-dimensional geometries, (e.g., hexagonal prisms) to simulate ice crystal aggregation and allows for variation in crystal size, shape, number, and falling orientation. In this study, after collection in a theoretical grid space, detailed information is extracted from the particles to determine the properties of aggregates. It was found that almost all monomer aspect ratios aggregate to less extreme aggregate aspect ratios at nearly the same rate. Newly formed aggregate properties are amenable to implementation into more sophisticated bulk microphysical models designed to predict and evolve particle properties, which is crucial in realistically evolving cloud ice mass distribution and for representing the collection process.

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Kara J. Sulia, Zachary J. Lebo, Vanessa M. Przybylo, and Carl G. Schmitt

Abstract

A novel methodology for modeling ice–ice aggregation is presented. This methodology combines a modified hydrodynamic collection algorithm with bulk aggregate characteristic information from an offline simulator that collects ice particles, namely, the Ice Particle and Aggregate Simulator, and has been implemented into the Adaptive Habit Microphysics scheme in the Weather Research and Forecasting Model. Aggregates, or snow, are formed via collection of cloud ice particles, where initial ice characteristics and the resulting geometry determine aggregate characteristics. Upon implementation, idealized squall-line simulations are performed to examine the new methodology in comparison with commonly used bulk microphysics schemes. It is found that the adaptive habit aggregation parameterization develops snow and reduces ice mass and number concentrations compared to other schemes. The development of aggregates through the new methodology cascades into other interesting effects, including enhancements in ice and snow growth, as well as homogeneous freezing. Further microphysical analyses reveal varying sensitivities, where snow processes are most sensitive to the new parameterization, followed by ice, then cloud, rain, and graupel processes. Further, the new scheme results in enhancements in surface precipitation due to the persistence of snow at lower altitudes. This persistence is a result of shape-dependent melting and sublimation, increasing the residence time. Moreover, these low-level enhancements are reflected in increases in radar reflectivity at the surface and its spatial distribution. Finally, the ability to predict snow shape and density allows for the simulation of polarimetric radar quantities, resulting in signature enhancements compared to schemes that do not consider spatial and temporal variations in snow shape and density.

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Bryan A. Baum, Ping Yang, Andrew J. Heymsfield, Carl G. Schmitt, Yu Xie, Aaron Bansemer, Yong-Xiang Hu, and Zhibo Zhang

Abstract

This study summarizes recent improvements in the development of bulk scattering/absorption models at solar wavelengths. The approach combines microphysical measurements from various field campaigns with single-scattering properties for nine habits including droxtals, plates, solid/hollow columns, solid/hollow bullet rosettes, and several types of aggregates. Microphysical measurements are incorporated from a number of recent field campaigns in both the Northern and Southern Hemisphere. A set of 12 815 particle size distributions is used for which T cld ≤ −40°C. The ice water content in the microphysical data spans six orders of magnitude. For evaluation, a library of ice-particle single-scattering properties is employed for 101 wavelengths between 0.4 and 2.24 μm. The library includes the full phase matrix as well as properties for smooth, moderately roughened, and severely roughened particles. Habit mixtures are developed for generalized cirrus, midlatitude cirrus, and deep tropical convection. The single-scattering properties are integrated over particle size and wavelength using an assumed habit mixture to develop bulk scattering and absorption properties. In comparison with global Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) data, models built with severely roughened particles compare best for all habit mixtures. The assumption of smooth particles provided the largest departure from CALIOP measurements. The use of roughened rather than smooth particles to infer optical thickness and effective diameter from satellite imagery such as the Moderate Resolution Imaging Spectroradiometer (MODIS) will result in a decrease in optical thickness and an increase in particle size.

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Romy Ullrich, Corinna Hoose, Daniel J. Cziczo, Karl D. Froyd, Joshua P. Schwarz, Anne E. Perring, Thaopaul V. Bui, Carl G. Schmitt, Bernhard Vogel, Daniel Rieger, Thomas Leisner, and Ottmar Möhler

Abstract

The contribution of heterogeneous ice nucleation to the formation of cirrus cloud ice crystals is still not well quantified. This results in large uncertainties when predicting cirrus radiative effects and their role in Earth’s climate system. The goal of this case study is to simulate the composition, and thus activation conditions, of ice nucleating particles (INPs) to evaluate their contribution to heterogeneous cirrus ice formation in relation to homogeneous ice nucleation. For this, the regional model COSMO—Aerosols and Reactive Trace Gases (COSMO-ART) was used to simulate a synoptic cirrus cloud over Texas on 13 April 2011. The simulated INP composition was then compared to measured ice residual particle (IRP) composition from the actual event obtained during the NASA Midlatitude Airborne Cirrus Properties Experiment (MACPEX) aircraft campaign. These IRP measurements indicated that the dominance of heterogeneous ice nucleation was mainly driven by mineral dust with contributions from a variety of other particle types. Applying realistic activation thresholds and concentrations of airborne transported mineral dust and biomass-burning particles, the model implementing the heterogeneous ice nucleation parameterization scheme of Ullrich et al. is able to reproduce the overall dominating ice formation mechanism in contrast to the model simulation with the scheme of Phillips et al. However, the model showed flaws in reproducing the IRP composition.

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