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Greg M. McFarquhar, Darrel Baumgardner, and Andrew J. Heymsfield
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Andrew J. Heymsfield, Martina Krämer, Anna Luebke, Phil Brown, Daniel J. Cziczo, Charmaine Franklin, Paul Lawson, Ulrike Lohmann, Greg McFarquhar, Zbigniew Ulanowski, and Kristof Van Tricht

Abstract

The goal of this chapter is to synthesize information about what is now known about one of the three main types of clouds, cirrus, and to identify areas where more knowledge is needed. Cirrus clouds, composed of ice particles, form in the upper troposphere, where temperatures are generally below −30°C. Satellite observations show that the maximum-occurrence frequency of cirrus is near the tropics, with a large latitudinal movement seasonally. In situ measurements obtained over a wide range of cirrus types, formation mechanisms, temperatures, and geographical locations indicate that the ice water content and particle size generally decrease with decreasing temperature, whereas the ice particle concentration is nearly constant or increases slightly with decreasing temperature. High ice concentrations, sometimes observed in strong updrafts, result from homogeneous nucleation. The satellite-based and in situ measurements indicate that cirrus ice crystals typically differ from the simple, idealized geometry for smooth hexagonal shapes, indicating complexity and/or surface roughness. Their shapes significantly impact cirrus radiative properties and feedbacks to climate. Cirrus clouds, one of the most uncertain components of general circulation models (GCM), pose one of the greatest challenges in predicting the rate and geographical pattern of climate change. Improved measurements of the properties and size distributions and surface structure of small ice crystals (about 20 μm) and identifying the dominant ice nucleation process (heterogeneous versus homogeneous ice nucleation) under different cloud dynamical forcings will lead to a better representation of their properties in GCM and in modeling their current and future effects on climate.

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D. Baumgardner, S. J. Abel, D. Axisa, R. Cotton, J. Crosier, P. Field, C. Gurganus, A. Heymsfield, A. Korolev, M. Krämer, P. Lawson, G. McFarquhar, Z. Ulanowski, and J. Um

Abstract

Understanding the formation and evolution of ice in clouds requires detailed information on the size, shape, mass, and optical properties of individual cloud hydrometeors and their bulk properties over a broad range of atmospheric conditions. Since the 1960s, instrumentation and research aircraft have evolved, providing increasingly more accurate and larger quantities of data about cloud particle properties. In this chapter, the current status of electrical powered, in situ measurement systems are reviewed with respect to their strengths and weaknesses and their limitations and uncertainties are documented. There remain many outstanding challenges. These are summarized and accompanied by recommendations for moving forward through new developments that fill the remaining information gaps. Closing these gaps will remove the obstacles that continue to hinder our understanding of cloud processes in general and the evolution of ice in particular.

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Ismail Gultepe, Andrew J. Heymsfield, Martin Gallagher, Luisa Ickes, and Darrel Baumgardner

Abstract

Ice fog is a natural, outdoor cloud laboratory that provides an excellent opportunity to study ice microphysical processes. Ice crystals in fog are formed through similar pathways as those in elevated clouds; that is, cloud condensation or ice nuclei are activated in an atmosphere supersaturated with respect to liquid water or ice. The primary differences between surface and elevated ice clouds are related to the sources of water vapor, the cooling mechanisms and dynamical processes leading to supersaturation, and the microphysical characteristics of the nuclei that affect ice fog crystal physical properties. As with any fog, its presence can be a hazard for ground or airborne traffic because of poor visibility and icing. In addition, ice fog plays a role in climate change by modulating the heat and moisture budgets. Ice fog wintertime occurrence in many parts of the world can have a significant impact on the environment. Global climate models need to accurately account for the temporal and spatial microphysical and optical properties of ice fog, as do weather forecast models. The primary handicap is the lack of adequate information on nucleation processes and microphysical algorithms that accurately represent glaciation of supercooled water fog. This chapter summarizes the current understanding of ice fog formation and evolution; discusses operating principles, limitations, and uncertainties associated with the instruments used to measure ice fog microphysical properties; describes the prediction of ice fog by the numerical forecast models and physical parameterizations used in climate models; identifies the outstanding questions to be resolved; and lists recommended actions to address and solve these questions.

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I. Gultepe, A. J. Heymsfield, P. R. Field, and D. Axisa

Abstract

Ice-phase precipitation occurs at Earth’s surface and may include various types of pristine crystals, rimed crystals, freezing droplets, secondary crystals, aggregates, graupel, hail, or combinations of any of these. Formation of ice-phase precipitation is directly related to environmental and cloud meteorological parameters that include available moisture, temperature, and three-dimensional wind speed and turbulence, as well as processes related to nucleation, cooling rate, and microphysics. Cloud microphysical parameters in the numerical models are resolved based on various processes such as nucleation, mixing, collision and coalescence, accretion, riming, secondary ice particle generation, turbulence, and cooling processes. These processes are usually parameterized based on assumed particle size distributions and ice crystal microphysical parameters such as mass, size, and number and mass density. Microphysical algorithms in the numerical models are developed based on their need for applications. Observations of ice-phase precipitation are performed using in situ and remote sensing platforms, including radars and satellite-based systems. Because of the low density of snow particles with small ice water content, their measurements and predictions at the surface can include large uncertainties. Wind and turbulence affecting collection efficiency of the sensors, calibration issues, and sensitivity of ground-based in situ observations of snow are important challenges to assessing the snow precipitation. This chapter’s goals are to provide an overview for accurately measuring and predicting ice-phase precipitation. The processes within and below cloud that affect falling snow, as well as the known sources of error that affect understanding and prediction of these processes, are discussed.

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Daniel J. Cziczo, Luis Ladino, Yvonne Boose, Zamin A. Kanji, Piotr Kupiszewski, Sara Lance, Stephan Mertes, and Heike Wex

Abstract

It has been known that aerosol particles act as nuclei for ice formation for over a century and a half (see Dufour). Initial attempts to understand the nature of these ice nucleating particles were optical and electron microscope inspection of inclusions at the center of a crystal (see Isono; Kumai). Only within the last few decades has instrumentation to extract ice crystals from clouds and analyze the residual material after sublimation of condensed-phase water been available (see Cziczo and Froyd). Techniques to ascertain the ice nucleating potential of atmospheric aerosols have only been in place for a similar amount of time (see DeMott et al.). In this chapter the history of measurements of ice nucleating particles, both in the field and complementary studies in the laboratory, are reviewed. Remaining uncertainties and artifacts associated with measurements are described and suggestions for future areas of improvement are made.

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A. Korolev, G. McFarquhar, P. R. Field, C. Franklin, P. Lawson, Z. Wang, E. Williams, S. J. Abel, D. Axisa, S. Borrmann, J. Crosier, J. Fugal, M. Krämer, U. Lohmann, O. Schlenczek, M. Schnaiter, and M. Wendisch

Abstract

Mixed-phase clouds represent a three-phase colloidal system consisting of water vapor, ice particles, and coexisting supercooled liquid droplets. Mixed-phase clouds are ubiquitous in the troposphere, occurring at all latitudes from the polar regions to the tropics. Because of their widespread nature, mixed-phase processes play critical roles in the life cycle of clouds, precipitation formation, cloud electrification, and the radiative energy balance on both regional and global scales. Yet, in spite of many decades of observations and theoretical studies, our knowledge and understanding of mixed-phase cloud processes remains incomplete. Mixed-phase clouds are notoriously difficult to represent in numerical weather prediction and climate models, and their description in theoretical cloud physics still presents complicated challenges. In this chapter, the current status of our knowledge on mixed-phase clouds, obtained from theoretical studies and observations, is reviewed. Recent progress, along with a discussion of problems and gaps in understanding the mixed-phase environment is summarized. Specific steps to improve our knowledge of mixed-phase clouds and their role in the climate and weather system are proposed.

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Ulrich Schumann and Andrew J. Heymsfield

Abstract

The life cycle of individual (initially line shaped) contrails behind aircraft and of contrail cirrus (aged contrails mixed with other ice clouds) is described. The full contrail life cycle is covered, from ice formation for given water, heat, and particulate emissions; to changes in the jet, wake, and dispersion phases; through final sublimation or sedimentation. Contrail properties are deduced from various in situ, remote sensing, and model studies. Aerodynamically induced contrails and distrails are explained briefly. Contrails form both in clear air and inside cirrus. Young contrails consume most of the ambient ice supersaturation. Optical properties of contrails are age and humidity dependent. Contrail occurrence and radiative forcing depends on the ambient Earth–atmosphere conditions. Contrail cirrus seems to be optically thicker than assessed previously and may not only increase cirrus coverage but also thicken existing cirrus. Some observational constraints for contrail cirrus occurrence and radiative forcing are derived. Key parameters controlling contrail properties—besides aircraft and fuel properties, ambient pressure, temperature, and humidity—are the number of ice particles per flight distance surviving the wake vortex phase, the contrail depth, and particle sedimentation, wind shear, turbulence, and vertical motions controlling contrail dispersion. The climate impact of contrails depends among other things on the ratio of shortwave to longwave radiative forcing (RF) and on the efficacy with which contrail RF contributes to surface warming. Several open issues are identified, including renucleation from residuals of sublimated contrail ice particles.

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Zamin A. Kanji, Luis A. Ladino, Heike Wex, Yvonne Boose, Monika Burkert-Kohn, Daniel J. Cziczo, and Martina Krämer

Abstract

Ice particle formation in tropospheric clouds significantly changes cloud radiative and microphysical properties. Ice nucleation in the troposphere via homogeneous freezing occurs at temperatures lower than −38°C and relative humidity with respect to ice above 140%. In the absence of these conditions, ice formation can proceed via heterogeneous nucleation aided by aerosol particles known as ice nucleating particles (INPs). In this chapter, new developments in identifying the heterogeneous freezing mechanisms, atmospheric relevance, uncertainties, and unknowns about INPs are described. The change in conventional wisdom regarding the requirements of INPs as new studies discover physical and chemical properties of these particles is explained. INP sources and known reasons for their ice nucleating properties are presented. The need for more studies to systematically identify particle properties that facilitate ice nucleation is highlighted. The atmospheric relevance of long-range transport, aerosol aging, and coating studies (in the laboratory) of INPs are also presented. Possible mechanisms for processes that change the ice nucleating potential of INPs and the corresponding challenges in understanding and applying these in models are discussed. How primary ice nucleation affects total ice crystal number concentrations in clouds and the discrepancy between INP concentrations and ice crystal number concentrations are presented. Finally, limitations of parameterizing INPs and of models in representing known and unknown processes related to heterogeneous ice nucleation processes are discussed.

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Greg M. McFarquhar, Darrel Baumgardner, Aaron Bansemer, Steven J. Abel, Jonathan Crosier, Jeff French, Phil Rosenberg, Alexei Korolev, Alfons Schwarzoenboeck, Delphine Leroy, Junshik Um, Wei Wu, Andrew J. Heymsfield, Cynthia Twohy, Andrew Detwiler, Paul Field, Andrea Neumann, Richard Cotton, Duncan Axisa, and Jiayin Dong

Abstract

In situ observations of cloud properties made by airborne probes play a critical role in ice cloud research through their role in process studies, parameterization development, and evaluation of simulations and remote sensing retrievals. To determine how cloud properties vary with environmental conditions, in situ data collected during different field projects processed by different groups must be used. However, because of the diverse algorithms and codes that are used to process measurements, it can be challenging to compare the results. Therefore it is vital to understand both the limitations of specific probes and uncertainties introduced by processing algorithms. Since there is currently no universally accepted framework regarding how in situ measurements should be processed, there is a need for a general reference that describes the most commonly applied algorithms along with their strengths and weaknesses. Methods used to process data from bulk water probes, single-particle light-scattering spectrometers and cloud-imaging probes are reviewed herein, with emphasis on measurements of the ice phase. Particular attention is paid to how uncertainties, caveats, and assumptions in processing algorithms affect derived products since there is currently no consensus on the optimal way of analyzing data. Recommendations for improving the analysis and interpretation of in situ data include the following: establishment of a common reference library of individual processing algorithms, better documentation of assumptions used in these algorithms, development and maintenance of sustainable community software for processing in situ observations, and more studies that compare different algorithms with the same benchmark datasets.

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