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Abebe Sine Gebregiorgis, Pierre-Emmanuel Kirstetter, Yang E. Hong, Nicholas J. Carr, Jonathan J. Gourley, Walt Petersen, and Yaoyao Zheng

the overlapping coverage of the WSR-88D network and the level-2 satellite data feeds to build a seamless rapidly updating, high-resolution 3D cube of radar data. Objectively, it blends volumetric radar data with surface, upper air, lightning, rain gauges, and model analysis fields to produce severe weather products. For the purpose of quality control, the dataset includes a radar quality index (RQI; Zhang et al. 2016 ), which ranges from 0% to 100% (with 100% corresponding to the highest quality

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Chris Kidd, Toshihisa Matsui, Jiundar Chern, Karen Mohr, Chris Kummerow, and Dave Randel

. Crucial to the success of the XT GPROF retrieval scheme is the MMF. The primary purpose of using the MMF-simulated database is to establish a quality-controlled and physically based precipitation retrieval algorithm consistent with the GPM core satellite as well as the GPM constellation satellites. The advantages of using an MMF-simulated database include the following: 1) the simulated microwave Tbs are derived from the identical physical assumptions and calculation methods, 2) it is straightforward

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E. Cattani, A. Merino, and V. Levizzani

discussed in section 3b . GPCC_Clim is computed by GPCC for the global land areas by means of an objective analysis of the climatological normals of about 67 200 ground stations. The method substantially reduces the shortcomings due to space and time coverage inhomogeneities and insufficient quality control of the station data typical of past climatological datasets ( Schneider et al. 2014 ). However, EA has a nonuniform coverage of gauges because of their scarcity, especially in Somalia, eastern

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Hamed Ashouri, Phu Nguyen, Andrea Thorstensen, Kuo-lin Hsu, Soroosh Sorooshian, and Dan Braithwaite

24-hourly scales at 4-km spatial resolution at Hydrologic Rainfall Analysis Project (HRAP) national grid system. Stage IV radar data are manually quality controlled at NWS River Forecast Centers (RFCs). (More information about stage IV data can be obtained from .) Stage IV precipitation data have been used in different studies (e.g., Ebert et al. 2007 ; Zeweldi and Gebremichael 2009 ; Anagnostou et al. 2010 ; Ashouri et al. 2015 ). In this study

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Ali Behrangi, Bin Guan, Paul J. Neiman, Mathias Schreier, and Bjorn Lambrigtsen

-Elevation Regressions on Independent Slopes Model (PRISM) dataset ( Daly et al. 2002 ) developed by the PRISM Climate Group at Oregon State University. PRISM data are generated from high-quality meteorological stations interpolated to a 4-km grid using a human expert and statistical knowledge-based system ( Daly et al. 2002 ; ). In other words, PRISM uses knowledge on the spatial patterns of climate and their relationships with geographic features to help enhance, control, and

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Yiwen Mei, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, and Marco Borga

(km 2 )] over the whole area. Note that gauge density over the 16 selected cascade basins varied between 1/25 (M1) and 1/67 (the entire basin). Table 2 reports the number of contributing gauges for each basin. The rain gauge rainfall record used in this study covers a 9-yr period (2002–10) at hourly temporal resolution. These rain gauge data have gone through a quality-control (QC) process according to the guidelines of the World Meteorological Organization ( Zahumenský 2010 ). Values that did

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F. Joseph Turk, R. Sikhakolli, P. Kirstetter, and S. L. Durden

. Description of datasets The analyses will focus on OSCAT and TRMM PR and TMI for a 2-yr period (2010–11) over the continental United States. To capture the rapid time evolution of precipitation during the 24-h period just prior to each of these satellite overpasses, the high-refresh, time-coincident precipitation derived from NEXRAD data is used. In this section, we provide a brief description of each of these datasets. a. OceanSat-2 over land The Indian Space Research Organisation (ISRO) OceanSat-2

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