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Joseph P. Zagrodnik, Lynn McMurdie, and Robert Conrick

. 1981 ). Atmospheric conditions favoring enhanced precipitation over terrain included warm sectors with low-level jets of at least 20 m s −1 (i.e., atmospheric rivers) and upwind “seeder” precipitation of at least 0.5 mm h −1 ( Nash and Browning 1977 ; Hill et al. 1981 ; Richard et al. 1987 ). A commonly held assumption of the seeder–feeder framework is that the lower-level warm processes are inefficient because of slow autoconversion rates between cloud and rainwater. Several studies over the

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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

clouds of extratropical cyclones passing over the windward slopes, high terrain, and lee side of the Olympic Mountains. Observations on the western side of the Olympic Peninsula were concentrated within and near the Quinault River valley, a very wet drainage on the windward side of the Olympic Mountains ( Fig. 1 ). A secondary focus of observations was the Chehalis River valley lying to the south of the Olympic Mountains. On two occasions, when the primary precipitation occurrence was in the Chehalis

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

south of the warm-frontal region sometimes contains an extensive narrow zone of water vapor flux commonly called an “atmospheric river” ( Newell et al. 1992 ; Zhu and Newell 1994 , 1998 ; Ralph et al. 2004 ; Warner et al. 2012 ). Behind the cold front, the postfrontal sector consists mainly of small-scale convective showers, which sometimes form into bands or other mesoscale features. This study focuses on the sectors with predominantly stratiform precipitation. Postfrontal convection is left to

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

flood forecasts have been shown to be dependent on the choice of BMP within a model (e.g., Colle and Mass 2000 ; Liu and Moncrieff 2007 ; Halder et al. 2015 ; Naeger et al. 2017 ), For these extreme flooding events from atmospheric rivers (ARs; Ralph et al. 2006 ; Dettinger 2011 ), it was found that total precipitation from operational models can be underestimated by as much as 50% ( Ralph et al. 2010 ). Flood-producing ARs typically feature orographically enhanced precipitation ( Neiman et al

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

-mean precipitation showed up to 30% differences as compared with precipitation derived from PRISM for these relatively small basins. In some of the basins, they found that the PRISM-derived precipitation was too low given the regional climate. Another consideration is that most extreme precipitation events in the western United States are orographically enhanced, and many precipitation events are associated with atmospheric rivers (ARs) accompanied by strong low-level winds (e.g., Zhu and Newell 1994 ; Ralph

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Annareli Morales, Hugh Morrison, and Derek J. Posselt

1. Introduction Orographic precipitation during nonconvective events commonly occurs in environments characterized by moist, nearly neutral conditions. This type of flow allows for little resistance to orographic lifting, resulting in enhancement of precipitation over windward mountain slopes ( Miglietta and Rotunno 2005 , 2006 , hereafter MR05 and MR06 , respectively). Atmospheric rivers (ARs) have been observed to have moist, nearly neutral static stability in the lower levels of the

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

veering than the prefrontal sector and the moist static stability profiles ( Fig. 5 ) were fairly close to moist neutral at low levels, especially from 1 to 4 km. The combination of high melting level (2–3 km), strong IVT (>500 kg m −1 s −1 ; Table 3 ), and moist-neutral stability suggest that all these of these warm sectors contained corridors of strong horizontal vapor transport commonly referred to as atmospheric rivers (e.g., Ralph et al. 2004 ). c. Postfrontal The postfrontal IR satellite

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Robert Conrick and Clifford F. Mass

; Keil et al. 2003 ; Sun and Rikus 2004 ; Otkin and Greenwald 2008 ; Jankov et al. 2011 ). In one assessment using simulated cloud-top brightness temperatures, Jankov et al. (2011) found that several moist physics parameterizations underestimated midlevel clouds during atmospheric river events. Bikos et al. (2012) used brightness temperatures to show that simulations underestimated low-level cloud in a preconvective environment. Other satellite datasets used to evaluate simulated cloud

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

neutral stability from the surface to 550 hPa ( Fig. 4b ). These conditions are consistent with the frontal system being of the “atmospheric river” type ( Newell et al. 1992 ; Zhu and Newell 1994 , 1998 ; Ralph et al. 2004 ; Warner et al. 2012 ). The KH waves occurred between 4 and 6 km, which is the upper boundary of this moist layer. The drier layers above 6 km were associated with considerably stronger winds from an upper-level jet. The analysis presented in Fig. 5b indicates that multiple

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