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Robert Conrick and Clifford F. Mass

centered within the larger GMI overpass swath at 250-m vertical resolution. The DPR provides measurements over land as well as water, and thus western Washington and its nearshore Pacific waters can be analyzed simultaneously. As described in the GPM Science Implementation Plan, 3 the random instrument errors of the GMI and DPR sensors were similar or better than microwave instruments aboard TRMM. The GMI bias met GPM mission requirements and was dependent on rain rate, decreasing from a bias of 0

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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

al. (2014) for details]. It is therefore important to determine how accurately GPM instruments can determine rain and snowfall in storms passing over mountain ranges. To assess and improve the ability of the GPM satellite, the Olympic Mountains Experiment (OLYMPEX) was planned. OLYMPEX was an international, multiorganization field campaign 1 designed to collect detailed measurements by aircraft and ground sites to correspond with GPM satellite measurements over an area including a midlatitude

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Minda Le and V. Chandrasekar

radar hydrometeor identification. a. Validation with NEXRAD KDVN—Flatland case Figure 3 illustrates a snowstorm observed by both GPM DPR and NEXRAD KDVN on 21 November 2015 near Davenport, Iowa. DPR flew over the KDVN location at 0830:59 UTC with the orbit number of 9828. Figure 3a shows KDVN radar S-band reflectivity at plan position indicator (PPI) scan of 0.46°. The time of the scan starts at 0832:59 UTC. The time difference within 10 min is considered coincidence in this study, while the time

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Yagmur Derin, Emmanouil Anagnostou, Marios Anagnostou, and John Kalogiros

observables Z H , Z DR , and K DP in rain, which were found from T-matrix scattering simulations at X band (9.37 GHz), carried out for a very wide range of values of rain DSD and drop shape parameters, air temperature, and an elevation of the radar antenna close to zero ( Kalogiros et al. 2014 ). c. VPR correction Reflectivity measurements and rainfall estimates in plan position indicator (PPI) scans of polarimetric weather radars in the melting layer (bright band) and the snow layer above it are

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Mircea Grecu, Lin Tian, Gerald M. Heymsfield, Ali Tokay, William S. Olson, Andrew J. Heymsfield, and Aaron Bansemer

, 1887 – 1898 , https://doi.org/10.1175/JTECH-D-16-0016.1 . 10.1175/JTECH-D-16-0016.1 Barros , A. , and Coauthors , 2014 : NASA GPM-ground validation: Integrated Precipitation and Hydrology Experiment 2014 science plan. NASA Doc., 64 pp., https://doi.org/10.7924/G8CC0XMR . 10.7924/G8CC0XMR Battaglia , A. , K. Mroz , T. Lang , F. Tridon , S. Tanelli , L. Tian , and G. M. Heymsfield , 2016 : Using a multiwavelength suite of microwave instruments to investigate the

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Qian Cao, Thomas H. Painter, William Ryan Currier, Jessica D. Lundquist, and Dennis P. Lettenmaier

. Sci. , https://doi.org/10.1175/JAS-D-17-0168.1 , in press . 10.1175/JAS-D-17-0168.1 Zhang , J. , 2011 : National Mosaic and Multi-Sensor QPE (NMQ) system: Description, results, and future plans . Bull. Amer. Meteor. Soc. , 92 , 1321 – 1338 , https://doi.org/10.1175/2011BAMS-D-11-00047.1 . 10.1175/2011BAMS-D-11-00047.1 Zhang , J. , and Coauthors , 2016 : Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimation: Initial operating capabilities . Bull. Amer. Meteor. Soc

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

channels over land . J. Hydrometeor. , 18 , 729 – 751 , https://doi.org/10.1175/JHM-D-16-0190.1 . 10.1175/JHM-D-16-0190.1 Zhang , J. , and Coauthors , 2011 : National Mosaic and Multi-Sensor QPE (NMQ) system: Description, results, and future Plans . Bull. Amer. Meteor. Soc. , 92 , 1321 – 1338 , https://doi.org/10.1175/2011BAMS-D-11-00047.1 . 10.1175/2011BAMS-D-11-00047.1 Zhang , J. , and Coauthors , 2016 : Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimation: Initial

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Stephanie M. Wingo, Walter A. Petersen, Patrick N. Gatlin, Charanjit S. Pabla, David A. Marks, and David B. Wolff

set within respective modules (following the lists in Table 1 ); a future version may permit a user-specified subset of fields to be gridded and included in the output column file. The subset of data within the user-defined column grid is then extracted from the full grid Radx output. SIMBA currently does not adjust multiple input radar frequencies to a common reference, though this is planned for future inclusion, and other than the quality control processing mentioned above, SIMBA does not

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Hannah C. Barnes, Joseph P. Zagrodnik, Lynn A. McMurdie, Angela K. Rowe, and Robert A. Houze Jr.

repeating a sequence of horizontal scans at increasing elevation angles ( Petersen and Krajewski 2018 ), referred to as plan position indicators (PPIs). During OLYMPEX, NPOL was located near Moclips, Washington ( Fig. 2b ; 47.3°N, 124.2°W) ( Petersen and Krajewski 2018 ). Unlike IFloodS, the NPOL operated primarily in range–height indicator (RHI) mode, with scans changing in elevation at constant azimuth. In this scanning mode, radar data are obtained with the finest possible vertical resolution, which

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Aaron R. Naeger, Brian A. Colle, Na Zhou, and Andrew Molthan

forecasting community, as the 2.5-km High-Resolution Deterministic Prediction System (HRDPS) in Canada ( Milbrandt et al. 2016 ) and the 3-km High-Resolution Rapid Refresh (HRRR) model managed at the NOAA/National Centers for Environmental Prediction (NCEP; Pinto et al. 2015 ) utilize the P3 and THOM BMPs, respectively. 2. Data and methods a. OLYMPEX field instrumentation Figure 1a presents an elevation map and instrumentation for the OLYMPEX field campaign ( Houze et al. 2017 ). We analyze plan

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