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Joseph P. Zagrodnik, Lynn McMurdie, and Robert Conrick

with synoptic observations, although the model is prone to underpredicting cloud water and overpredicting snow mixing ratios ( Conrick and Mass 2019a ; Conrick and Mass 2019b ). Figure 1 shows the 36–12–4–1.33-km model domain configuration with 51 vertical levels. The innermost 1.33-km domain is centered over the Olympic Peninsula. Model initialization and boundary conditions were driven by the 0.25° Global Forecast System (GFS) gridded dataset. The 36-km grid boundaries were nudged every 3 h

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Minda Le and V. Chandrasekar

profiles. In other words, 97% of snow profiles have SI > 17, while 97% of rain profiles have SI ≤ 17. A snow flag is generated using the thresholds of the snow index as well as other auxiliary information such as 0°C isotherm and clutter-free height but only as constraints. This surface snowfall flag is a “0” or “1” product, where “0” represents no snow and “1” represents snow. In the GPM DPR level-2 algorithm, this flag is named as “flagSurfaceSnowfall” and is currently available in the experimental

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Robert Conrick, Clifford F. Mass, and Qi Zhong

idealized or dry models. Large-eddy simulation (LES) experiments have investigated KH instability in a variety of real-world cases, including in a mesoscale convective system (MCS) over southern England ( Browning et al. 2012 ), within a hurricane boundary layer ( Nakanishi and Niino 2012 ; Na et al. 2014 ), during frontogenesis ( Samelson and Skyllingstad 2016 ), and for stratified flow over terrain ( Sauer et al. 2016 ). Recent studies have used full-physics NWP models to simulate KH waves. Mahalov

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

gradient and a 180° wind shift at 925 hPa ( Fig. 3b ). Data presented in Figs. 4a and 5a suggest that a strong low-level stable frontal inversion of over 8°C and strong directional shear below 1 km resulted in conditions that could support the development and maintenance of KH waves because the Ri was less than 0.25 in multiple layers below 1 km near Davenport. The radar-observed KH waves were located near Waterloo, which is approximately 180 km to the northwest. Given that the frontal boundary

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Robert Conrick and Clifford F. Mass

issues are explored in this paper. The aim of this study is to evaluate precipitation biases and low-level microphysics in the Weather Research and Forecasting (WRF) Model, comparing observed and simulated rain drop size distributions and precipitation during the OLYMPEX winter experiment and two heavy precipitation events. Our goal is to explore the following questions: What biases exist in simulated precipitation over the Pacific Northwest in current microphysical parameterization schemes? How do

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

observations, and IWC, D m , and the attenuation at all frequencies are iteratively derived. The attenuation from the upper boundary of the current gate to its center is initially assumed to be zero, and IWC, D m , and the attenuation are derived. In the next iteration, potentially different IWC, D m , and attenuation estimates are derived because new estimates of the attenuation within the radar gate are available. The process is repeated until convergence is achieved. This type of attenuation

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

Resolution Imaging Spectroradiometer (MODIS) sensor to account for effects of the background snow-cover emission. We demonstrate that the algorithm shows improved skill in detection of snowfall over snow cover and can predict the likelihood of precipitation phase changes in the atmospheric boundary layer, which is not well observed by the GPM radar. In summary, the presented algorithm isolates a few physically relevant candidate vectors of brightness temperatures in the database via a weighted Euclidean

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William Ryan Currier, Theodore Thorson, and Jessica D. Lundquist

parameterizes processes that control the formation, growth, and fallout of precipitation from clouds. WRF does not require surface gauge observations and represents varying synoptic conditions but is sensitive to various model decisions, such as model resolution ( Colle et al. 1999 ; Colle and Mass 2000 ), boundary conditions ( Yang et al. 2012 ), and the chosen microphysical scheme ( Jankov et al. 2009 ; Liu et al. 2011 ; Minder and Kingsmill 2013 ). In contrast, PRISM is a gridded climatology map

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Joseph P. Zagrodnik, Lynn A. McMurdie, Robert A. Houze Jr., and Simone Tanelli

all of the ground clutter while retaining as much near-surface data as possible. In the current version of the Ku reflectivity product, isolated spikes of 10–15-dB Z reflectivity within broader regions of weak reflectivity frequently affect low signal-to-noise (SNR) regions. A 2D Gaussian filter with a standard deviation of 1.5 bins (R. Chase 2018, personal communication) effectively removed the speckling without degrading the reflectivity information, as seen in the example transects provided in

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

underestimation is not the subject of the current paper, and we will not be going into detail about the reasons underlying it. It is noted that the variability exhibited in the scatterplot of DOW to disdrometer ( Fig. 2 ) is slightly lower than that of the MRR to disdrometer ( Fig. 3 ), which indicates that the DOW can capture reflectivity from a distance similarly to a collocated MRR instrument. This, once more, qualifies the short-range DOW reflectivity measurements over complex terrain providing high

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