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Sarah Ringerud, Christa Peters-Lidard, Joe Munchak, and Yalei You

field of view has been collocated to the same center point ( NASA PPS and X-Cal Working Group 2017 ). b. The OE emissivity retrieval Munchak et al. (2020) describe an optimal estimation-based emissivity retrieval for the GPM Combined algorithm, anticipated to be included in version 7 of the operational product. The retrieval uses GMI Tb as input and retrieves surface emissivity at the GMI frequencies along with the water vapor profile. It should be noted that the emissivity retrieval uses the

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Lisa Milani, Mark S. Kulie, Daniele Casella, Pierre E. Kirstetter, Giulia Panegrossi, Veljko Petkovic, Sarah E. Ringerud, Jean-François Rysman, Paolo Sanò, Nai-Yu Wang, Yalei You, and Gail Skofronick-Jackson

detection performance can also be influenced by snowfall regimes, with intense, deeper events accompanied by higher columnar water vapor amounts typically easier to detect than light and/or shallow snowfall events that occur in drier ambient conditions (e.g., Skofronick-Jackson et al. 2013 ). Several recent studies highlight different snowfall modes both from satellite ( Kulie and Milani 2018 ; Kulie et al. 2016 ; West et al. 2019 ; Kulie et al. 2020 ) and ground-based radar perspectives ( Pettersen

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Nobuyuki Utsumi, F. Joseph Turk, Ziad S. Haddad, Pierre-Emmanuel Kirstetter, and Hyungjun Kim

the precipitation-free scenes inferred from the DPR profiles, together with the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) ( Gelaro et al. 2017 ) temperature and water vapor profile, the surface emissivity for GMI’s first nine (89 GHz and below) channels is estimated by the emissivity retrieval method of Mathew et al. (2008) with the successive order of interaction (SOI) radiative transfer model ( Heidinger et al. 2006 ), regardless of the surface. For

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Shruti A. Upadhyaya, Pierre-Emmanuel Kirstetter, Jonathan J. Gourley, and Robert J. Kuligowski

) by both the products, with SCaMPR detecting 100% of the raining pixels classified as Hail. However, the Tropical/Stratiform Mix type is better detected by MWCOMB (94.0%) than by SCaMPR (85.9%). In MRMS, this precipitation type tends to be associated collision–coalescence processes with limited vertical extent and ice content, which makes it more challenging to detect with IR and water vapor (WV) channels than with microwave channels ( Cecil and Zipser 2002 ). Clouds producing moderate

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Clément Guilloteau and Efi Foufoula-Georgiou

of orbiting imagers providing frequent observations of clouds and precipitation all over the globe ( Skofronick-Jackson et al. 2018 ). The passive microwave retrieval of precipitation relies on the measurement of radiances at the top of the atmosphere, which are the product of the surface emission, emission and absorption by liquid rain drops and water vapor and scattering by ice particles. Vertically and horizontally polarized radiances are measured at various frequencies between 5 and 200 GHz

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Stephen E. Lang and Wei-Kuo Tao

1. Introduction Latent heat release within the atmosphere arises from heat exchanges as water changes phase between vapor, liquid, and solid and is an important component or principal driver for many atmospheric circulations. Even at midlatitudes, latent heating (LH) can be an important part of midlatitude cyclone dynamics and the larger-scale storm track ( Willison et al. 2013 ) and can be especially important for the rapid deepening of such storms ( Whitaker and Davis 1994 ; Pirret et al

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Zhe Li, Daniel B. Wright, Sara Q. Zhang, Dalia B. Kirschbaum, and Samantha H. Hartke

spatial resolution over the inner simulation domain. Control variables in the data assimilation module EDAS include wind, temperature, surface pressure, water vapor, and five hydrometeors (the mixing ratios of cloud water, rain, ice, snow, and graupel). In summary, the observations for EDAS analysis cycles include in situ conventional data (radiosonde, pilot, wind profiler, and GPS integrated precipitable water data), clear-sky satellite radiances from the Advanced Microwave Sounding Unit A (AMSU

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