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Yoo-Jeong Noh, Curtis J. Seaman, Thomas H. Vonder Haar, and Guosheng Liu

, concentration, and refractive index ( Sun and Shine 1994 ). The generalized properties of mixed-phase clouds in which liquid and ice coexist are relatively unknown and remain an active area of research. Recent studies indicate that 40%–60% of clouds in the temperature range between 0° and −30°C are mixed phase and 30%–60% are supercooled liquid water clouds ( Korolev et al. 2003 ; Mazin 2006 ; Shupe et al. 2006 ; Zhang et al. 2010 ). The longevity and areal extent of these supercooled-liquid and mixed-phase

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Tatsuya Seiki and Woosub Roh

shortwave cloud radiative forcing (SWCRF) over the Southern Ocean ( Bodas-Salcedo et al. 2012 ; Williams et al. 2013 ). Bodas-Salcedo confirmed that the SWCRF bias mainly originated from underestimation of supercooled liquid water in low-level mixed-phase clouds. Large intermodal spread in supercooled liquid water over the mid- to high-latitude regions results in large uncertainties in cloud feedbacks (e.g., McCoy et al. 2015 ). The SWCRF bias mainly originates from poor representation of cloud

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Hongchun Jin and Shaima L. Nasiri

1. Introduction Cloud thermodynamic phase is a highly uncertain observable from satellite observations that indicates whether a cloud is composed of liquid water droplets, ice crystals, or a mixture of the two phases of hydrometeors (i.e., mixed phase). The determination of cloud phase is an important step in the satellite-based retrieval of several cloud properties, such as cloud particle size, optical thickness, and water path. Cloud phase can significantly impact the planetary radiation

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Yongxiang Hu, David Winker, Mark Vaughan, Bing Lin, Ali Omar, Charles Trepte, David Flittner, Ping Yang, Shaima L. Nasiri, Bryan Baum, Robert Holz, Wenbo Sun, Zhaoyan Liu, Zhien Wang, Stuart Young, Knut Stamnes, Jianping Huang, and Ralph Kuehn

1. Introduction In passive remote sensing, cloud thermodynamic phase (water or ice) information typically comes from the spectral absorption difference between visible (VIS; 0.65 μ m) and shortwave infrared (SWIR; 1.5–1.6 and 3–4 μ m) wavelengths. Neither ice clouds nor water clouds absorb much visible light. However, absorption by both ice and water increases at near-infrared wavelengths, and multiple scattering enhances the absorption. At SWIR wavelengths, ice clouds absorb significantly

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Maki Hirakata, Hajime Okamoto, Yuichiro Hagihara, Tadahiro Hayasaka, and Riko Oki

1. Introduction Cloud phase and ice crystal orientation are among the major factors that determine the radiative effect of clouds. Even at the same wavelength, the complex refraction index differs between water and ice. The phase function of a cloud particle, which determines its scattering characteristics, varies depending on the shape of the particle ( Sassen and Liou 1979 ). Phases and shapes of clouds are also important in retrieving the microphysical properties, such as particle size

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Vincent E. Larson and Adam J. Smith

1. Introduction There are several reasons that one may wish to know the fraction of liquid water in thin, mixed-phase layer clouds. One is aircraft icing. Between 1975 and 1988, there were 803 aviation accidents in the continental United States in which icing was a cause or a factor ( Bragg et al. 1998 ). Cober et al. (2001) discuss several well-documented cases of severe icing suffered by research aircraft and also mention the crash of an ATR-72 commuter aircraft near Roselawn, Indiana, in

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Matthew D. Shupe, David D. Turner, Alexander Zwink, Mandana M. Thieman, Eli J. Mlawer, and Timothy Shippert

algorithm combines measurements from radiosondes, lidar, radar, microwave radiometer, and infrared radiometer within a framework that consists of multiple ground-based remote-sensor retrieval methods to produce estimates of cloud water content and hydrometeor size for both liquid and ice phases. The strength of the algorithm lies in the instrument and retrieval synergy. For example, while infrared measurements are accurate at determining cloud properties for optically thin clouds, they provide little

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

, seawater, and bacterial samples were also studied, often motivated by collections of fog water and precipitation (e.g., Schnell and Vali 1976 ; Vali et al. 1976 ; Schnell 1977 ). 3) IRs in mixed-phase clouds There exist two ground-based CVI inlet systems for sampling IRs of ice crystals contained in MPCs. These are the Ice-CVI ( Mertes et al. 2007 ) and Ice Selective Inlet (ISI; Kupiszewski et al. 2015 ), both of which have been deployed at the high-altitude research station Jungfraujoch in the

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Christopher J. Cox, David D. Turner, Penny M. Rowe, Matthew D. Shupe, and Von P. Walden

1. Introduction Clouds play an important and complex role in the climate system by modulating the surface-energy budget. The net radiative forcing of clouds is caused by the interplay of albedo (negative forcing) and thermal emission (positive forcing) effects ( Ramanathan et al. 1989 ), with the magnitude and sign being dependent on cloud properties. Properties including liquid and ice water paths, optical depth, temperature, particle size, and phase are important components of the radiative

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Hyoun-Myoung Cho, Shaima L. Nasiri, and Ping Yang

1. Introduction Cloud thermodynamic phase is a physical quantity that indicates whether a cloud is composed of liquid water droplets, ice crystals, or a mixture of liquid water and ice particles. When cloud phase is determined from satellite observations, spatial averaging over a field of view on the order of kilometers is inevitable and the upper portion of a cloud is weighed more heavily than the lower portions. The retrieval of cloud thermodynamic phase is a prerequisite for satellite

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