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

; Villarini and Krajewski 2007 ; Sapiano and Arkin 2009 ; Baxter et al. 2014 ; Yong et al. 2016 ). Nevertheless, such seasonal and latitudinal variations could be captured by air temperature ( Peel et al. 2007 ; Behrangi et al. 2015 ; Smalley et al. 2014 ). Seasonal and latitudinal variations of the quality of satellite-based precipitation products have been widely investigated. Maggioni et al. (2016) reviewed previous work that evaluates commonly used satellite-based precipitation products across

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Sarah D. Bang and Daniel J. Cecil

.S. National Weather Service to warn for a severe thunderstorm, and severe hail is often a harbinger of other violent weather to come ( Bluestein and Parker 1993 ; Johns and Hart 1998 ). Hailstorms’ destructive potential and their place at the upper reach of the intensity spectrum of convective precipitation drives the need within the meteorological community to establish global hail climatologies, which can be constructed using either ground-report-based or remotely sensed approaches. While there are

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Liang Liao and Robert Meneghini

( Feingold and Levin 1986 ), and several dual-wavelength radar retrieval techniques have been developed ( Meneghini et al. 1992 ; Mardiana et al. 2004 ; Liao and Meneghini 2005 ; Rose and Chandrasekar 2005 ; Seto et al. 2013 ; Seto and Iguchi 2015 ; Liao et al. 2016 ; Liao and Meneghini 2019 ). Some of them are based on an analytic technique that uses the dual-frequency ratio (DFR), that is, the difference of radar reflectivities between two wavelengths, to estimate a characteristic size parameter

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Xinxuan Zhang and Emmanouil N. Anagnostou

-based PMW sensors ( Joyce et al. 2004 ). This study used the CMORPH V1.0 near-real-time and gauge-adjusted products with 0.073°/30-min resolution. The gauge-adjusted product is corrected by two widely used long-term datasets, the CPC unified gauge analysis over land and the pentad Global Precipitation Climatology Project (GPCP) over the ocean. CMORPH has a newer version named V0.x, which employed more advanced algorithms. However, CMORPH V0.x does not provide a gauge-adjusted product, and it is not

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Ali Tokay, Leo Pio D’Adderio, Federico Porcù, David B. Wolff, and Walter A. Petersen

out that the systematic differences in NS and MS precipitation estimates are larger for convective rain over land and strongly depend on the NUBF parameterization. They also mentioned that simulated Z_Ka was significantly and systematically lower than observed Z_Ka, resulting in erroneous DSD adjustments. A methodology to account for NUBF is therefore necessary to mitigate large errors in the N W and precipitation rate estimates derived from DPR observations. A statistical model used by Grecu

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M. Petracca, L. P. D’Adderio, F. Porcù, G. Vulpiani, S. Sebastianelli, and S. Puca

unprecedented Ka-band (35 GHz) radar. GPM provides several precipitation products at different scales by using different sensors’ combinations and synergies. The DPR plays a key role in the GPM precipitation estimation scheme, being the main calibration instrument, serving as space reference for radiometer-derived global precipitation algorithms ( Neeck et al. 2014 ), and providing basic information on the vertical cloud structure ( Grecu et al. 2016 ). Three algorithms (KuPR algorithm, KaPR algorithm, and

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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

understand orographic modification of frontal precipitation processes but also to satisfy the need for further development and refinement of algorithms used to convert GPM’s satellite measurements to precipitation amounts in midlatitudes. The algorithms applied to TRMM satellite data over a nearly 17-yr period have been very successful for rain measurement and characterizing tropical convection ( Simpson 1988 ; Simpson et al. 1996 ; Kummerow et al. 1998 ; Zipser et al. 2006 ; Huffman et al. 2007

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