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Brian J. Carroll, Belay B. Demoz, David D. Turner, and Ruben Delgado

focused study of LLJ moisture transport is only preceded in the literature by Tollerud et al. (2008) , which was relatively limited in that they only measured meridional moisture flux along two flight legs a few hours after sunrise. Recent work by Lin et al. (2019) bordered this topic, as they presented airborne Raman lidar observations near an MCS, targeting interactions between inflow (an LLJ), outflow, and the stable boundary layer. This manuscript shifts focus away from the MCS’s immediate

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Yun Lin, Jiwen Fan, Jong-Hoon Jeong, Yuwei Zhang, Cameron R. Homeyer, and Jingyu Wang

al. 2002 ; Shepherd 2005 ; Hubbart et al. 2014 ). Convective storms may be initiated at the UHI convergence zone that is created through a combination of increased temperature and mechanical turbulence resulting from complex urban surface geometry and roughness ( Bornstein and Lin 2000 ; Shepherd 2005 ; Hubbart et al. 2014 ; Liu and Niyogi 2019 ). Urban landscapes can impact sensible and latent heat flux, soil moisture, etc., affecting thunderstorm initiation with a higher frequency in urban

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Stacey M. Hitchcock and Russ S. Schumacher

top. The domain was set to translate east at 9 m s −1 and north at 8 m s −1 . Fifth-order positive definite advection, the Klemp–Wilhelmson time-splitting, vertically implicit pressure solver ( Klemp and Wilhelmson 1978 ), and a 2-s time step were used. Open radiative lateral boundary conditions were used to allow fast moving gravity waves created during initiation to escape the domain. Rayleigh damping was applied near the model top, and a free slip condition was applied at the surface. This

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Evgeni Fedorovich, Jeremy A. Gibbs, and Alan Shapiro

–Väisälä frequency, free-atmosphere geostrophic wind, radiative damping parameter, day and night diffusivities (assumed equal for momentum and buoyancy), maximum and minimum surface buoyancies, and times of maximum surface buoyancy and sunset. The unified theory predicted that jets strengthen with increasing geostrophic wind, maximum surface buoyancy, and day-to-night ratio of the eddy diffusivities, and weaken with increasing Brunt–Väisälä frequency and magnitude of minimum slope buoyancy. Peak winds were found

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Tammy M. Weckwerth, Kristy J. Weber, David D. Turner, and Scott M. Spuler

removed from analyses due to dissimilar profiles. See text for explanation of how and why dissimilar profiles were removed from DIAL comparisons with AERI and MWRP. During FRAPPÉ the radiosondes were Vaisala RS92s and were corrected for dry bias caused by solar radiative heating of the relative humidity sensor arm following Wang et al. (2013) . The sounding launch site was collocated with the DIAL and AERI. During PECAN the radiosondes were Vaisala RS41s, which do not require dry bias correction due

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Samuel K. Degelia, Xuguang Wang, David J. Stensrud, and Aaron Johnson

environments in which storms form. Childs et al. (2006) showed improved CI forecasts by assimilating surface observations that induced convergent boundaries through enhanced surface heat fluxes. More recently, Sobash and Stensrud (2015) found positive results by using an ensemble Kalman filter (EnKF) to assimilate mesonet and conventional surface observations. Forecast improvements were found to have resulted from a better analysis of moisture within the PBL. Additionally, the assimilation of radar

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Rachel L. Miller, Conrad L. Ziegler, and Michael I. Biggerstaff

and Rutledge 1995 ; Rasmussen and Rutledge 1993 ; Schuur and Rutledge 2000 ; McAnelly et al. 1997 ; Grady and Verlinde 1997 ; Watson et al. 1988 ; Bernstein and Johnson 1994 ). Smull and Houze (1985) utilized single Doppler analysis to infer that a squall line’s FTR flow was driven by the organized deep convection forming the CL, while Smull and Houze (1987) observed with a dual-Doppler analysis that the FTR flow which extended to the rear of the system facilitated horizontal flux of ice

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Stanley B. Trier, James W. Wilson, David A. Ahijevych, and Ryan A. Sobash

, 2002 ) PBL scheme, the Rapid Radiative Transfer Model for global climate models (RRTMG; Mlawer et al. 1997 ; Iacono et al. 2008 ) longwave and shortwave radiation schemes, and the Noah land surface model ( Chen and Dudhia 2001 ). Figure 8 compares vertical profiles of adjusted diagnosed from observations with corresponding area-averaged from the model ensemble. Since an important criterion used for triangle selection is the absence of significant precipitation within the triangle at the time

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W. G. Blumberg, T. J. Wagner, D. D. Turner, and J. Correia Jr.

the mid-1990s using a retrieval algorithm called AERIprof ( Smith et al. 1999 ; Feltz et al. 1998 ). AERIprof has several limitations: 1) the carbon dioxide concentration was fixed and not easily changed, 2) the fast radiative transfer model used within AERIprof was tuned for Southern Great Plains (SGP) conditions and hence had significant errors when used in the tropics or Arctic, 3) uncertainty estimates are not provided by this algorithm, and 4) the algorithm was very sensitive to its first

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Aaron Johnson and Xuguang Wang

parameterization determines the mean turbulent flux, , as follows: In Eq. (1) , is the gridbox mean vertical gradient of some variable , and is the eddy diffusivity coefficient for that variable. In the MYJ parameterization used for the CPM experiments, the eddy diffusivity is parameterized as a function of turbulent kinetic energy (TKE), which is predicted with a 1.5-order closure model ( Janjić 1994 ). The implied assumption that all turbulence is subgrid scale contrasts to the LES framework where it

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