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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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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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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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