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Ryan Eastman, Matthew Lebsock, and Robert Wood

. While the CloudSat precipitation products provide the best available estimates of precipitation frequency and intensity in shallow marine clouds, the nadir-only sampling of CloudSat is insufficient for work attempting to disentangle cause and effect in drizzle and cloud processes. Recently, new satellite data products utilizing passive microwave observations of brightness temperature T b ( Miller and Yuter 2013 , hereafter MY13 ; Duncan et al. 2018 ) have shown the potential for vastly

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Min-Jeong Kim, Mark S. Kulie, Chris O’Dell, and Ralf Bennartz

1. Introduction With the success of the Tropical Rainfall Measuring Mission (TRMM), satellite-based remote sensing has become a key tool for understanding tropical precipitation. The TRMM’s successor, the Global Precipitation Measurement (GPM) is on the horizon and will extend the unique capabilities of combined radar and passive microwave observations to higher latitudes. Extratropical precipitation is, in general, shallower than tropical precipitation and generally exhibits a lower freezing

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F. Joseph Turk, Ziad S. Haddad, and Yalei You

1. Introduction The joint National Aeronautics and Space Administration (NASA) and Japanese Aerospace Exploration Agency (JAXA) Global Precipitation Measurement (GPM) core satellite will provide considerably more overland observations over complex terrain, high-elevation river basins, and cold surfaces, which are problematic for existing Tropical Rainfall Measuring Mission (TRMM) radar and radiometer precipitation algorithms ( Fu and Liu 2007 ). Current passive microwave (PMW) overland

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L. Cucurull, R. A. Anthes, and L.-L. Tsao

1. Introduction In recent years, the large increase in the number of satellite observations and the improvements in the assimilation of the data in numerical weather prediction (NWP) models have been major factors in improving the skill of numerical weather forecasts, particularly in the Southern Hemisphere, where the number of nonsatellite observations is limited ( Kelly and Pailleux 1988 ). Infrared and microwave nadir sounders are the most commonly used satellite instruments for operational

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Aina Taniguchi, Shoichi Shige, Munehisa K. Yamamoto, Tomoaki Mega, Satoshi Kida, Takuji Kubota, Misako Kachi, Tomoo Ushio, and Kazumasa Aonashi

product ( Iguchi et al. 2009 ) and the TMI 2A12 version 6 product derived from the GPROF algorithm ( Kummerow et al. 2001 ; McCollum and Ferraro 2003 ; Olson et al. 2006 ; Wang et al. 2009 ). Observations derived from other microwave imagers, such as the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Special Sensor Microwave Imager (SSM/I), and Special Sensor Microwave Imager/Sounder (SSMIS) as well as the Advanced Microwave Sounding Unit (AMSU) microwave

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Konstantinos M. Andreadis and Dennis P. Lettenmaier

strongly alter microwave emissivity and thus complicate retrieval algorithms. An alternative approach to using satellite observations alone is to merge them with physically based model predictions to constrain retrieval algorithms and potentially account for the uncertainties (e.g., through data assimilation; see, e.g., Durand and Margulis 2006 ; Pulliainen 2006 ). Such an approach usually requires coupling a large-scale snow hydrology model and a microwave emission model. Results from previous

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T. T. Wilheit, A. T. C. Chang, J. L. King, E. B. Rodgers, R. A. Nieman, B. M. Krupp, A. S. Milman, J. S. Stratigos, and H. Siddalingaiah

AUGUST 1982 WILHEIT ET AL. 1137 Microwave Radiometric Observations Near 19.35, 92 and 183 GHz of Precipitation in Tropical Storm Cora T. T. WILHEIT, A. T. C. CHANG, J. L. KING1 AND E. B. RODGERS NASA/Goddard Space Flight Center, Greenbelt, MD 20771 R. A. NlEMAN Computer Sciences Corporation, Silver

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Christopher W. O’Dell, Peter Bauer, and Ralf Bennartz

several more computationally efficient approaches to serve as fast alternatives to the reference scheme. Section 5 characterizes the accuracy of the fast models as compared to the reference overlap model, whereas section 6 examines the full forward-model errors as compared with actual microwave observations. A brief discussion of the results is given in section 7 . 2. Base profiles and microphysics The profile datasets were drawn from the ECMWF efforts to assimilate cloud- and precipitation

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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 statistics ( Skofronick-Jackson et al. 2019 ). In particular, the Goddard Profiling Algorithm (GPROF; Kummerow et al. 1996 ; Kummerow et al. 2015 ), which retrieves precipitation rates using passive microwave (PMW) observations, generally underestimates both snowfall detection and quantification when compared to active remote sensing sensor snowfall products. Previous studies based on theoretical analyses ( Skofronick-Jackson and Johnson 2011 ) and radiometer observations ( Panegrossi et al

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Harald Czekala, Susanne Crewell, Clemens Simmer, Ariane Thiele, Achim Hornbostel, and Arno Schroth

-dimensional radiative transfer model to such rain events of limited horizontal scale is at least ambiguous. Conclusions We compared ground-based polarized microwave observations of rainfall with simulated brightness temperature results from a one-dimensional vector radiative transfer model. The findings clearly show that using spherical particles to model microwave radiative transfer fails to explain the observations. The choice of oblate raindrop shape with size-dependent deformation and strict horizontal

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