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Thomas R. Parish

critical to the formation of the nocturnal wind maximum such as discussed by Wexler (1961) . In this study, the LLJ environment is viewed through the lens of the North American Mesoscale Forecast System. Composite grids are assembled for a 5-yr period for cases of strong LLJs and non-LLJ episodes. Comparison of the gridded datasets enables key differences to be identified and offers another view into the Blackadar–Holton debate. 2. Composite grids for cases of the LLJ As part of the Plains Elevated

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Elizabeth N. Smith, Joshua G. Gebauer, Petra M. Klein, Evgeni Fedorovich, and Jeremy A. Gibbs

, surface buoyancy forcing, atmospheric turbulence, and slope angle. Nonetheless, past numerical modeling studies have consistently shown that representing the evolving NBL and embedded NLLJs is not easily accomplished in mesoscale models, partly due to the poor performance of turbulence parameterizations applied in boundary layer schemes. NLLJ magnitude and depth are often underestimated in studies with different boundary layer parameterization schemes in the Weather Research and Forecasting (WRF

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Bart Geerts, David Parsons, Conrad L. Ziegler, Tammy M. Weckwerth, Michael I. Biggerstaff, Richard D. Clark, Michael C. Coniglio, Belay B. Demoz, Richard A. Ferrare, William A. Gallus Jr., Kevin Haghi, John M. Hanesiak, Petra M. Klein, Kevin R. Knupp, Karen Kosiba, Greg M. McFarquhar, James A. Moore, Amin R. Nehrir, Matthew D. Parker, James O. Pinto, Robert M. Rauber, Russ S. Schumacher, David D. Turner, Qing Wang, Xuguang Wang, Zhien Wang, and Joshua Wurman

evaluations of operational CPMs, reveal significant errors in CI timing and location ( Kain et al. 2013 ), system duration, and QPF, in particular during the night in the PECAN region, even over short forecast periods ( Pinto et al. 2015 ). Certain field campaigns such as IHOP ( Weckwerth et al. 2004 ), BAMEX ( Davis et al. 2004 ), and MPEX ( Weisman et al. 2015 ) collected tantalizing observations of relevance and motivation to PECAN, within the broader PECAN domain. However, IHOP focused on the daytime

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Hristo G. Chipilski, Xuguang Wang, and David B. Parsons

, which may make them inappropriate for real-time forecasting applications. To understand the interplay between nocturnal outflow boundaries and convective systems in real-time high-resolution numerical weather prediction (NWP) models, this study presents a novel object-based algorithm that is capable of seamlessly identifying density currents and bores. The latter is achieved by employing a multivariate approach similar to the dryline identification algorithm of Clark et al. (2015) . Rather than

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Kevin R. Haghi, Bart Geerts, Hristo G. Chipilski, Aaron Johnson, Samuel Degelia, David Imy, David B. Parsons, Rebecca D. Adams-Selin, David D. Turner, and Xuguang Wang

This article presents a survey of atmospheric bores, their role in the initiation and organization of deep convection, and a vision for improving the forecast of atmospheric bores and nocturnal convection through a multidisciplinary approach. On the afternoon of the 10 July 2015 in Hays, Kansas, during the Plains Elevated Convection at Night (PECAN) field campaign ( Geerts et al. 2017 ), the bore group was selected to lead the evening’s intensive observation period (IOP). The PECAN forecasters

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Tammy M. Weckwerth and Ulrike Romatschke

stability (e.g., Crook 1996 ; Weckwerth et al. 1996 ; Ziegler and Rasmussen 1998 ) and wind shear (e.g., Moncrieff and Miller 1976 ; Rotunno et al. 1988 ; Lee et al. 1991 ; Wilson and Megenhardt 1997 ). Nighttime CI episodes in the U.S. Great Plains account for ~50% of the CI events ( Wilson and Roberts 2006 ). They are more difficult to forecast than daytime CI partly because the most unstable layer is typically elevated and is not as readily observed (e.g., Weckwerth et al. 2019 ). Some of the

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J. W. Wilson, S. B. Trier, D. W. Reif, R. D. Roberts, and T. M. Weckwerth

initiating nocturnal storms during IHOP_2002 ( Weckwerth et al. 2004 ). This current PECAN case was unique in that it was the only case where data were collected on convection initiated more than 100 km from any other storms and without a near-surface convergence line or bore causing the CI. In addition, the forecast for CI provided an opportunity to collect a considerable amount of high-resolution data from a variety of measurement systems near the time and location of the CI. Figure 1 shows the

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Matthew D. Parker, Brett S. Borchardt, Rachel L. Miller, and Conrad L. Ziegler

kt (1 kt ≈ 0.5144 m s −1 ), or ≈26 m s −1 ] in northeastern Kansas and western Missouri, including several estimated gusts exceeding 30 m s −1 ( Fig. 1 ). Horgan et al. (2007) discussed the substantial challenges of severe wind forecasting in this scenario. One testable hypothesis is that the 25–26 June MCS remained elevated and lacked a substantial surface cold pool. In such a case, severe winds might result either from the lifting and subsequent descent of air parcels within the near

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Stacey M. Hitchcock, Russ S. Schumacher, Gregory R. Herman, Michael C. Coniglio, Matthew D. Parker, and Conrad L. Ziegler

1. Introduction Mesoscale convective systems (MCSs) play a critical role in the warm season nocturnal precipitation maximum over the U.S. Great Plains region (e.g., Wallace 1975 ; Maddox 1980 ; Fritsch et al. 1986 ; Carbone et al. 2002 ). These systems provide essential rainfall, but are often associated with severe weather ( Jirak et al. 2003 ; Maddox 1980 ). Despite its frequency and importance, nocturnal convection is not particularly well forecast in numerical models ( Davis et al

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Manda B. Chasteen, Steven E. Koch, and David B. Parsons

simultaneously (e.g., Schumacher 2015 ). Additionally, strong dynamical forcing associated with mature convection may be sufficient to lift conditionally unstable air within the near-surface stable layer to its level of free convection (LFC), enabling nocturnal convection to remain surface based (e.g., Parker 2008 ; Nowotarski et al. 2011 ; Billings and Parker 2012 ). The degree to which nocturnal convection is surface based is often uncertain and thus creates complications for forecasters, who may

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