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Randy J. Chase, Stephen W. Nesbitt, and Greg M. McFarquhar

1. Introduction Despite being confined to high latitudes and altitudes when occurring at the surface, snow can be related to approximately 50% by number ( Field and Heymsfield 2015 ) and approximately 60% by mass accumulation ( Heymsfield et al. 2020 ) of all precipitation across cold and warm climates. Thus, the accurate retrieval of snow properties is required for an accurate quantification of the hydrologic cycle. Furthermore, the quantitative retrieval of snowfall properties is invaluable

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

analyses to classify the probability of snow versus rain using the approach of Sims and Liu (2015) . The model is GANAL for GMI GPROF near-real-time and production products while ECMWF interim reanalysis (ERA-Interim) ( Dee et al. 2011 ) is used for the GMI GPROF CLIM (climate) products. Le et al. (2017) have introduced a different, experimental method of rain/snow classification for DPR using characteristics of the dual-frequency ratio profile, but this still only uses data above the surface

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Veljko Petković, Christian D. Kummerow, David L. Randel, Jeffrey R. Pierce, and John K. Kodros

ice particle size distributions . J. Appl. Meteor. , 40 , 345 – 364 , doi: 10.1175/1520-0450(2001)040<0345:TSOMRS>2.0.CO;2 . 10.1175/1520-0450(2001)040<0345:TSOMRS>2.0.CO;2 Berg , W. , T. L'Ecuyer , and C. Kummerow , 2006 : Rainfall climate regimes: The relationship of regional TRMM rainfall biases to the environment . J. Appl. Meteor. Climatol. , 45 , 434 – 454 , doi: 10.1175/JAM2331.1 . 10.1175/JAM2331.1 Bretherton , C. S. , M. E. Peters , and L. E. Back , 2004 : Relationships

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Sarah D. Bang and Daniel J. Cecil

snow-covered surfaces can exhibit very low microwave T b s ( Skofronick-Jackson and Johnson 2011 ; Ebtehaj and Kummerow 2017 ), occupying the same T b regimes as intense hailstorms. This can be seen in the strong representation of hail in central Greenland in the climatology of Ferraro et al. (2015) , where there is likely not a high concentration of severe hail. All of the aforementioned factors are challenges faced by those building satellite-based hail climatologies, and the application of

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W.-K. Tao, T. Iguchi, and S. Lang

Studies (IFloodS), and the Integrated Precipitation and Hydrology Experiment (IPHEX)] as well as regional climate simulations over the continental United States (CONUS) (e.g., Iguchi et al. 2017 ; Lee et al. 2017 ; Tian et al. 2017 ). It has also been used to simulate a variety of precipitation systems in intensive field measurement campaigns [e.g., the Canadian CloudSat / CALIPSO Validation Programme (C3VP) ( Shi et al. 2010 ; Iguchi et al. 2012a ), the Light Precipitation Validation Experiment

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Jackson Tan, Walter A. Petersen, and Ali Tokay

satellites, including Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Cloud Classification System (PERSIANN-CCS; Hong et al. 2004 ), the Climate Prediction Center (CPC) morphing technique (CMORPH; Joyce et al. 2004 ; Joyce and Xie 2011 ), Global Satellite Mapping of Precipitation (GSMaP; Kubota et al. 2007 ; Kachi et al. 2014 ), the Naval Research Laboratory blended-satellite technique (NRL blended; Turk and Miller 2005 ), and TRMM Multisatellite

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Jiaying Zhang, Liao-Fan Lin, and Rafael L. Bras

world map of the Koppen-Geiger climate classification . Hydrol. Earth Syst. Sci. , 11 , 1633 – 1644 , . 10.5194/hess-11-1633-2007 PRISM Climate Group , 2018 : PRISM climate data. Oregon State University, accessed 26 March 2018, . Sapiano , M. R. P. , and P. A. Arkin , 2009 : An intercomparison and validation of high-resolution satellite precipitation estimates with 3-hourly gauge data . J. Hydrometeor. , 10 , 149

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Stephen E. Lang and Wei-Kuo Tao

fairly consistent range of gradient values that could be adopted as part of a metric for the LUTs and that the model, for the most part, at least spans the range of observed values. However, the reflectivity gradient metric is initially introduced here with just a simple positive/negative classification with zero gradient values grouped as positive. So, in addition to the convective/stratiform and land/ocean separation, whether or not low-level reflectivities increase or decrease toward the surface

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Xinxuan Zhang and Emmanouil N. Anagnostou

precipitation rates by certain retrieval algorithms ( Ebert and Manton 1998 ). These estimates represent an indirect measurement of precipitation, and their accuracy is largely affected by different cloud types, rain systems, and hydroclimatic regimes. The PMW measurements observe the microwave energy emitted by rain droplets or scattered by precipitating ice particles. While the IR/VIS and PMW techniques can only capture horizontal precipitation patterns and intensities, the precipitation radar (PR) can

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Zeinab Takbiri, Ardeshir Ebtehaj, Efi Foufoula-Georgiou, Pierre-Emmanuel Kirstetter, and F. Joseph Turk

) developed a statistical approach that partitions high-frequency brightness temperatures (≥89 GHz) into two distinct warm and cold weather regimes by thresholding the brightness temperature at 53 GHz. Another class of empirical approaches relies on Bayesian techniques. These techniques use a database or a lookup table that relates brightness temperatures of snowing clouds to the radar snowfall observations along with the atmospheric temperature profile. As an example, Liu and Seo (2013) used matched

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