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Jonathan E. Thielen and William A. Gallus Jr.

1. Introduction Mesoscale convective systems (MCSs) play a crucial role climatologically in precipitation across the central United States. These systems account for roughly 30%–70% of the precipitation that occurs during the April–September period (warm season) in this region ( Ashley et al. 2003 ) and are therefore key phenomena of interest when seeking to improve the quantitative precipitation forecast (QPF) skill of models ( Fritsch et al. 1986 ). While this rainfall is essential to

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Aaron Johnson, Xuguang Wang, and Samuel Degelia

designed to better understand optimal convection-permitting ensemble forecasts and storm-scale DA configurations for the prediction of nocturnal convection and related features using retrospective forecasts from 2014. The GSI-based multiscale ensemble DA and forecast system described in Part I and Johnson et al. (2015) was also implemented as an operational real-time nocturnal-convection prediction system during the PECAN field experiment. This system is described and evaluated in the present paper

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John M. Peters, Erik R. Nielsen, Matthew D. Parker, Stacey M. Hitchcock, and Russ S. Schumacher

nocturnal MCSs and their EILs are essential to identifying potential sources of errors in numerical forecasts of elevated MCSs, and the analysis of such observations are currently lacking in the scientific literature. This literary gap exists because the necessary observations required for analyzing elevated MCS environments are difficult to obtain. For instance, regular upper-level observations of temperature, moisture, and wind are taken via radiosondes with a spatial density of 100–1000 km, and at a

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Aaron Johnson and Xuguang Wang

layer ( Parker 2008 ; Trier et al.2011 ; Marsham et al. 2011 ; Coleman and Knupp 2011 ; Erlingis and Barros 2014 ) and low-level jets (LLJs; Carbone et al. 1990 ; Trier and Parsons 1993 ; Trier et al. 2006 ; Tuttle and Davis 2006 ; Coniglio et al. 2010 ; Trier et al. 2010 ; French and Parker 2010 ). The notoriously low skill of warm-season quantitative precipitation forecasting is due in large part to the low predictability of nocturnal convective initiation (CI) and subsequent evolution

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

problematic for NWP forecasts (e.g., Johnson and Wang 2017 ; Johnson et al. 2017 ; Stelten and Gallus 2017 ; Johnson et al. 2018 ). Reif and Bluestein (2017) note that NWP models are often tuned specifically for features that initiate surface-based convection, whereas nocturnal CI tends to be initiated by features above the boundary layer ( Corfidi et al. 2008 ). For example, the nocturnal low-level jet (LLJ), defined as a wind maximum occurring within the lowest kilometer of the atmosphere after

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Sean Stelten and William A. Gallus Jr.

can threaten public safety and property with high winds, hail, flooding, and occasionally tornadoes, despite their helpful role as the primary producer of warm season precipitation in the central United States ( Maddox et al. 1979 ; Maddox 1980 ; Fritsch et al. 1986 ; Rochette and Moore 1996 ). Thus, correctly predicting the initiation of MCSs and other less organized convection is an integral part of forecasting for the Great Plains. Prediction of the CI that leads to nighttime convection is

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

1. Introduction Warm season precipitation forecasting remains a difficult problem, as forecast accuracy is consistently higher in the cool season than in the summer ( Fritsch and Carbone 2004 ). Forecasting warm season precipitation at night provides additional challenges, as forecasts of nocturnal convective storms in the United States are less accurate than forecasts of daytime storms ( Davis et al. 2003 ). Additionally, nocturnal convection produces many flash flooding events ( Maddox et al

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Aaron Johnson, Xuguang Wang, Kevin R. Haghi, and David B. Parsons

NWP forecasts of bores and their impacts on nocturnal convection. An accurate bore simulation is dependent on an accurate representation of both the evolution of the nocturnal boundary layer and low-level jet and a correct forecast of the formation, location, temperature, and depth of the density current. These features can be separated into three key ingredients that are necessary for successful NWP forecasts of bores. First, the mesoscale environment in which the bore occurs must be accurately

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Matthew D. Flournoy and Michael C. Coniglio

of kilometers and minutes, and can develop very quickly within QLCSs ( Mahale et al. 2012 ; Newman and Heinselman 2012 ). Because of this, forecasting severe wind associated with mesovortices is a difficult problem, and the study of both (i) synoptic conditions conducive for the development of mesovortices and (ii) mechanisms forcing mesovortex genesis in QLCSs remain active areas of research. Given favorable thermodynamic conditions, 15–20 m s −1 of line-normal vertical wind shear in the

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

Plains, nocturnal CI (NCI) remains challenging to forecast, especially in the absence of surface boundaries ( Wilson and Roberts 2006 ; Reif and Bluestein 2018 ; Weckwerth et al. 2019 ). This is due in part to the paucity of routine thermodynamic profiling in the PBL and the limited resolution of satellite observations within the lowest few kilometers of the atmosphere ( Kahn et al. 2011 ; Steinke et al. 2015 ; Weckwerth et al. 2019 ). Previous studies based on radiosonde and surface data or

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