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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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Gail Skofronick-Jackson, Walter A. Petersen, Wesley Berg, Chris Kidd, Erich F. Stocker, Dalia B. Kirschbaum, Ramesh Kakar, Scott A. Braun, George J. Huffman, Toshio Iguchi, Pierre E. Kirstetter, Christian Kummerow, Robert Meneghini, Riko Oki, William S. Olson, Yukari N. Takayabu, Kinji Furukawa, and Thomas Wilheit

The GPM mission collects essential rain and snow data for scientific studies and societal benefit. Water is essential to our planet. It literally moves mountains through erosion, transports heat in Earth’s oceans and atmosphere, keeps our planet from freezing as a result of radiative impacts of atmospheric water vapor, and causes catastrophes through droughts, floods, landslides, blizzards, and severe storms, but most importantly water is vital for nourishing all life on Earth. Precipitation as

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Liang Liao and Robert Meneghini

then be used as input to the retrieval algorithms. The degree to which the radar estimates agree with the true values, which are derived directly from the assumed DSD profiles, constitutes a measure of the retrieval accuracy. The basic approach can also be used to evaluate the impact of different model assumptions and various constraints adopted in the retrieval algorithms. In this paper we start with describing the principles of the DPR version-5 algorithms in section 2 , and then evaluate its

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Sarah D. Bang and Daniel J. Cecil

systems in place in some countries to report hail observed at the ground, the coverage of consistent surface reporting is far from global. Allen and Tippett (2015) note that biases in reporting due to population density and other societal or otherwise nonmeteorological factors present difficulties in using surface reports to build a hail climatology. Within the United States, the minimum required hail size to trigger a severe thunderstorm warning changed from 0.75 to 1.0 in. in 2010 (1 in. = 2.54 cm

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Gail Skofronick-Jackson, Mark Kulie, Lisa Milani, Stephen J. Munchak, Norman B. Wood, and Vincenzo Levizzani

1. Introduction and background Observations of the global distributions of falling snow are needed for a wide variety of scientific and societal applications. For example, falling snow observations can be used to evaluate global change precipitation science predictions ( Karl et al. 2009 ; Gergel et al. 2017 ; Harpold and Kohler 2017 ) and are needed for assessing inputs to snowpack water reserves ( Lettenmaier et al. 2015 ). While most of the societal needs for falling snow measurements are

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Daniel Watters, Alessandro Battaglia, Kamil Mroz, and Frédéric Tridon

to exclude profiles from the comparison where the ground-based radars are overshooting rain and looking into the bright band or the snow above it. The results of this paper could be used as a benchmark for assessing the real impact of the dual-polarization upgrade in future studies. Acknowledgments The work done by Daniel Watters was funded by the Central England NERC Training Alliance. The work done by Alessandro Battaglia and Frédéric Tridon was funded by the project “Calibration and validation

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