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Seth Saslo and Steven J. Greybush

1998 ; Markowski and Richardson 2010 ), which can result in shallow convection. This convection takes many forms, but very often it develops into banded features characterized by the wind direction, lake orientation, and large-scale environment ( Niziol et al. 1995 ). These bands result in sharp gradients of precipitation that prove challenging to forecast accurately at short- to medium-range lead times. The synoptic environment is a significant influence on LES events; in the eastern Great Lakes

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Daniel T. Eipper, George S. Young, Steven J. Greybush, Seth Saslo, Todd D. Sikora, and Richard D. Clark

. 2017 ), underscoring the need for accurate understanding and forecasting of LLAP-band inland penetration. In this study we pursue this quest by investigating physical mechanisms and environmental predictors supportive of the inland penetration of LLAP-band radar echoes (hereafter InPen). Previous lake-effect studies have established the fundamental requirement for lake-effect convection to be the flow of a sufficiently cold air mass over a relatively warm lake surface (e.g., Phillips 1972

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Philip T. Bergmaier and Bart Geerts

eta ( η ) levels, the first 14 of which are in the lowest 1 km AGL. Initial and lateral boundary conditions were generated at 6-h intervals with analyses from the 12-km North American Mesoscale Forecast System (NAM). The simulation was run for 96 h, from 0000 UTC 6 January to 0000 UTC 10 January. The model physics configuration includes the Yonsei University planetary boundary layer scheme ( Hong et al. 2006 ), the revised MM5 surface layer scheme ( Jiménez et al. 2012 ), and the Noah land surface

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Daniel T. Eipper, Steven J. Greybush, George S. Young, Seth Saslo, Todd D. Sikora, and Richard D. Clark

cover all periods with dominant bands in OWLeS with the exception of the 15–16 December 2013 storm. Following the identification of these time periods, reanalysis simulations were generated for each period with the Weather Research and Forecasting (WRF) Model ( Skamarock et al. 2008 ). These reanalyses were generated by assimilating hourly in situ observations (e.g., operational surface, aircraft, and radiosonde data were assimilated; radar reflectivities and OWLeS field observations were not

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Leah S. Campbell, W. James Steenburgh, Peter G. Veals, Theodore W. Letcher, and Justin R. Minder

secondary role, although the intense precipitation rates associated with these bands remains a critical forecast concern in both lowland and upland areas. Future work should utilize numerical modeling to investigate the processes controlling the distribution and intensity of precipitation east of Lake Ontario and variations in enhancement over Tug Hill. Improved knowledge and modeling of such storm characteristics is fundamental to advancing lake-effect prediction and can provide a valuable framework

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David A. R. Kristovich, Richard D. Clark, Jeffrey Frame, Bart Geerts, Kevin R. Knupp, Karen A. Kosiba, Neil F. Laird, Nicholas D. Metz, Justin R. Minder, Todd D. Sikora, W. James Steenburgh, Scott M. Steiger, Joshua Wurman, and George S. Young

region of New York include 30.5 cm in 1 h at Copenhagen, 44.5 cm in 2 h at Oswego, and 129.5 cm in 16 h at Bennetts Bridge ( Burt 2007 ). Fig . 1. (a) Map showing all deployment locations discussed in this manuscript. Examples of facility deployment during (b) IOP 2b (intense LLAP snowband), (c) IOP 7 (intense LLAP snowband), and (d) IOP 17 (Finger Lakes snowbands). WCR data from the middle flight leg shown in (b) are plotted in Fig. 3 . To better understand and improve forecasts of intense lake

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Leah S. Campbell and W. James Steenburgh

1. Introduction Lake-effect snowstorms generated over the Great Lakes of North America and other bodies of water can produce intense, extremely localized snowfall (e.g., Andersson and Nilsson 1990 ; Steenburgh et al. 2000 ; Eito et al. 2005 ; Laird et al. 2009 ; Kindap 2010 ). Forecasters still struggle, however, to accurately predict the timing and location of the heaviest snowfall during lake-effect events, which disrupt local and regional transportation, education, utilities, and

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Peter G. Veals, W. James Steenburgh, and Leah S. Campbell

and Kristovich 2002 ). The strength of the fluxes and height of the cap in turn affect the behavior and intensity of the lake-effect convection. Larger fluxes and a higher cap enable deeper, stronger convection and greater LPE downwind of the lake (e.g., Braham 1983 ; Niziol 1987 ; Hjelmfelt 1990 ; Byrd et al. 1991 ; Smith and Boris 2017 ). For operational forecasting, the potential for boundary layer growth and lake-effect convection is often assessed using estimates of the lake

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W. James Steenburgh and Leah S. Campbell

1. Introduction Accurate prediction of the timing, location, and intensity of lake-effect snowfall is paramount for forecasters in lake-, sea-, and ocean-effect (hereafter simply lake effect) regions. Intense, often highly localized lake-effect snowfall can produce rapid and extreme accumulations, adversely impacting transportation, commerce, and property ( Norton and Bolsenga 1993 ; Schmidlin 1993 ; Kunkel et al. 2002 ). Especially strong lake-effect systems (i.e., complexes of lake

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Peter G. Veals and W. James Steenburgh

to provide new insights into lake-effect precipitation east of Lake Ontario and over Tug Hill, with relevance for operational forecasting, regional climate applications, and improved knowledge of lake-effect and orographic precipitation processes. The methods used for the radar-based climatology are described in section 2 , with detailed analysis of the regional lake-effect characteristics and influence of Tug Hill presented in section 3 . Conclusions and future work are summarized in section

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