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Joseph P. Zagrodnik, Lynn McMurdie, and Robert Conrick

precipitation enhancement associated with ridge-induced mountain waves. A model simulation of a particularly intense storm showed that collection of cloud water by rain was the dominant conversion term, but there was “no clear separation between synoptically forced clouds and orographically forced clouds, both of which seed and feed the collection process.” ( Minder et al. 2008 ). Importantly, collection terms from a bulk microphysical scheme cannot be used to directly diagnose the seeder–feeder mechanism

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

partly attributed to initial conditions, in addition to choice of BMP and model resolution. Martin et al. (2018) attributed precipitation deficiencies for AR simulations from the WRF Model to low biases in the low-level water vapor flux. Thus, there remains a strong need to improve forecasts of extreme precipitation events such as ARs in an effort to mitigate flood risk and damage from these storms. The suite of intensive instrumentation deployed during the recent Olympic Mountains Experiment

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Robert Conrick and Clifford F. Mass

: How well does WRF simulate GPM-observed water vapor, cloud water, and rain rate during OLYMPEX? Can the underprediction of precipitation over coastal regions, described in Conrick and Mass (2018, manuscript submitted to J. Hydrometeor. ), be explained by upstream (offshore) GPM measurements? Can cloud water or water vapor fields explain precipitation biases? How realistic are simulated vertical profiles of rainwater, cloud water, and snow mixing ratios compared to GPM observations? Are vertical

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Annareli Morales, Hugh Morrison, and Derek J. Posselt

, ARs are responsible for 20%–50% of the annual precipitation ( Dettinger et al. 2011 ), often from only a few storms producing large amounts of snow, resulting in snowpack reaching “near-record levels of snow water equivalent” ( Guan et al. 2010 , 2013 ). Guan et al. (2013) found that lower-than-normal surface air temperatures during AR events favor increased snow accumulation over the Sierra Nevada. Colder AR events have lower amounts of integrated water vapor, yet they result in a higher snow

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

-free MODIS temperature data. As the liquid water content of global snowpack is not available, we define dry (wet) snow when the skin and air temperature are both below (above) 0°C ( Baggi and Schweizer 2009 ). To account for atmospheric radiometric signals, we also added the integrated liquid and ice water content of the clouds, as well as the integrated water vapor content of the atmospheric column from the second version of the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2-M2

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

the inclusion of a multiple-scattering model in the framework is necessary ( Grecu et al. 2016 ). Note that because the simulated reflectivities in the database are not affected by attenuation, reflectivity observations y obs are corrected for attenuation before being used in Eq. (3) . In our implementation, this is achieved through a gate-by-gate attenuation correction procedure. The attenuation correction accounts for attenuation due to ice particles, water vapor, and cloud water. The

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Andrew Heymsfield, Aaron Bansemer, Norman B. Wood, Guosheng Liu, Simone Tanelli, Ousmane O. Sy, Michael Poellot, and Chuntao Liu

the base of the ML. In the present study, the approach is further justified, with potential errors estimated, using additional CloudSat data as well as data from other spaceborne radars, thereby covering a wide range of radar reflectivities. If the relative humidity (RH) in the ML is 100% with respect to water, there might be a small amount of condensational growth on the ice particles as they are melting because of the vapor pressure difference between water saturation at the ambient

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Robert Conrick and Clifford F. Mass

fidelity of the coastal winds and incoming moisture, since they play a controlling role on moist physics. For example, vertically integrated moisture flux [integrated water vapor transport (IVT)] is strongly correlated with U.S. West Coast orographic precipitation ( Neiman et al. 2008 ; Lin et al. 2013 ) and is a key parameter in defining and forecasting atmospheric rivers (e.g., Newell et al. 1992 ; Zhu and Newell 1998 ). Furthermore, IVT forecast errors have been shown to correlate with

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

the melting level in midlatitude precipitating systems. In the case where the waves are located below the melting level, enhanced Z H and Z DR observed below the upward portions of the waves indicate the fallout of large water drops that likely resulted from increased vapor deposition or coalescence in the upward branch. A significant question is whether KH waves impact surface precipitation accumulations. This study is uniquely able to explore this question because the KH waves observed

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Robert Conrick, Clifford F. Mass, and Qi Zhong

level, which is consistent with generation of supercooled water necessary for riming. Thus, it appears that wave activity enhanced riming and aggregation, which grew particles that melted as they fell below the melting level, resulting in larger raindrop sizes below the waves. During the 17 December event, KH waves occurred below the melting level. In this regime, the Barnes et al. (2018) conceptual model indicates coalescence and vapor deposition as the primary microphysical processes occurring

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