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Yalei You, S. Joseph Munchak, Christa Peters-Lidard, and Sarah Ringerud

) has been used by several retrieval algorithms ( You et al. 2015 ; Kummerow et al. 2015 ). To largely avoid the possible surface contamination, instead of using the signatures from window channels (e.g., 85 GHz), Staelin and Chen (2000) developed a rainfall retrieval algorithm solely dependent on the microwave observations near opaque water vapor and oxygen absorption channels (183 and 52 GHz). Brocca et al. (2014) proposed a conceptually different rainfall retrieval algorithm by using the soil

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Sarah D. Bang and Daniel J. Cecil

cloud tops using satellite-based IR imager and CloudSat cloud profiling radar observations . J. Appl. Meteor. Climatol. , 55 , 479 – 491 , . 10.1175/JAMC-D-15-0170.1 Grody , N. C. , 1991 : Classification of snow cover and precipitation using the special sensor microwave imager . J. Geophys. Res. , 96 , 7423 – 7435 , . 10.1029/91JD00045 Hohl , R. , H.-H. Schiesser , and D. Aller , 2002 : Hailfall: The

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Zhaoxia Pu, Chaulam Yu, Vijay Tallapragada, Jianjun Jin, and Will McCarty

assimilating satellite observations to improve hurricane track and intensity predictions ( Pu et al. 2002 , 2008 ; Pu and Zhang 2010 ; Liu et al. 2012 ; Xu et al. 2013 ; Zou et al. 2013 ; Zhang and Pu 2014 ; Yang et al. 2016 ; Xu et al. 2016 ; Wu et al. 2016 ). Specifically, these previous studies found that satellite microwave sounders is particularly useful for understanding moist processes associated with hurricanes owing to its unique capability to depict precipitation structure and moisture

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Dalia B. Kirschbaum, George J. Huffman, Robert F. Adler, Scott Braun, Kevin Garrett, Erin Jones, Amy McNally, Gail Skofronick-Jackson, Erich Stocker, Huan Wu, and Benjamin F. Zaitchik

data assimilation and modeling scenarios and for diverse end-user audiences. These case studies demonstrate how the availability and continuity of satellite-based precipitation data records can influence and enhance scientific research and societal issues in ways that are not otherwise possible. GMI impact study for hurricane track prediction. Numerical weather prediction centers around the world rely on microwave and IR-based observations to improve weather prediction and forecasting of tropical

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Catherine M. Naud, James F. Booth, Matthew Lebsock, and Mircea Grecu

latitudinal coverage, observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E; Kawanishi et al. 2003 ) are also used over the oceans ( Kummerow et al. 2011 ), but this instrument has some sensitivity issues in the midlatitudes ( Stephens et al. 2010 ; Behrangi et al. 2012 ). The availability of gridded combined products such as the Global Precipitation Climatology Project (GPCP; Adler et al. 2003 ) helps to overcome the coverage issue, but these are typically

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Toshio Iguchi, Nozomi Kawamoto, and Riko Oki

, . Liu , G. , 2008 : Deriving snow cloud characteristics from CloudSat observations . J. Geophys. Res. , 113 , D00A09 , . Liu , G. , and E.-K. Seo , 2013 : Detecting snowfall over land by satellite high-frequency microwave observations: The lack of scattering signature and a statistical approach . J. Geophys. Res. Atmos. , 118 , 1376 – 1387 , . 10.1002/jgrd.50172 Marra , A. C

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Jackson Tan, Walter A. Petersen, and Ali Tokay

-top temperatures. Much progress has been made in the last two decades with a contingent of low-Earth-orbiting passive microwave satellites and two NASA/JAXA spaceborne radars in the microwave band, the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM) mission. Unlike infrared radiation, microwave radiation is able to penetrate clouds and interact more directly with precipitation; consequently, microwave retrieval techniques generally provide a superior estimate of

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Xinxuan Zhang and Emmanouil N. Anagnostou

1. Introduction Satellite remote sensing plays an irreplaceable role in precipitation measurement because it is the only mean of gathering data with uninterrupted, quasi-global coverage. Precipitation-related satellite observations are of four main types: longwave infrared (IR), visible spectrum (VIS), passive microwave (PMW), and active microwave retrievals. The satellite IR and VIS sensors measure the cloud-top brightness temperature or reflectivity that researchers use to derive

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Xiang Ni, Chuntao Liu, and Edward Zipser

. With simultaneous observations of two radars at Ku and Ka band, DPR is capable to further infer the microphysical properties of hydrometeors inside the precipitation systems ( Seto et al. 2013 ; Olson et al. 2016 ). Before the launch of GPM, dual-frequency retrieval algorithms have been reviewed and revised with hybrid methods ( Le and Chandrasekar 2014 ). Kuo et al. (2016) have discussed the microwave scattering properties of spherical ice-air particles and nonspherical snow particles based on

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Robert A. Houze Jr., Lynn A. McMurdie, Walter A. Petersen, Mathew R. Schwaller, William Baccus, Jessica D. Lundquist, Clifford F. Mass, Bart Nijssen, Steven A. Rutledge, David R. Hudak, Simone Tanelli, Gerald G. Mace, Michael R. Poellot, Dennis P. Lettenmaier, Joseph P. Zagrodnik, Angela K. Rowe, Jennifer C. DeHart, Luke E. Madaus, Hannah C. Barnes, and V. Chandrasekar

. With its onboard Dual-Frequency Precipitation Radar (DPR) and 13-channel GPM Microwave Imager (GMI), the GPM satellite extends into future decades the global surveillance of precipitation provided until 2014 by the Tropical Rainfall Measuring Mission (TRMM) satellite and broadens coverage to higher latitudes, where many of Earth’s snow-covered mountain ranges are located. GPM also serves as a reference for other satellites carrying a variety of microwave imaging or sounding radiometers [see Hou et

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