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Philip T. Bergmaier and Bart Geerts

, Steenburgh and Campbell (2017) show how large-scale flow, the shoreline geometry of Lake Ontario, and differential surface heating and roughness led to the development of two land-breeze fronts (LBFs) that played a significant role in the upstream origin of the LLAP band, its downstream evolution, and the precipitation maximum over Tug Hill. During the most intense snowfall period, a well-defined, coherent secondary circulation consisting of two counterrotating vortices was observed within the band

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W. James Steenburgh and Leah S. Campbell

boundary layer parameterization with a revised surface layer scheme ( Hong et al. 2006 ; Jiménez et al. 2012 ), Kain–Fritsch-2 cumulus parameterization ( Kain 2004 ; 12-km domain only), and Thompson cloud microphysics parameterization ( Thompson et al. 2008 ). Land use derives from U.S. Geological Survey land-use data and around Lake Ontario consists primarily of deciduous broadleaf forest, dryland cropland and pasture, and cropland/grassland mosaic, with pockets of urban and built-up land, grassland

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Leah S. Campbell and W. James Steenburgh

Dawson (2013) , McMillen and Steenburgh (2015a) , and Conrick et al. (2015) , the simulations presented in this paper use the Thompson cloud microphysics ( Thompson et al. 2008 ), Rapid Radiative Transfer Model longwave radiation ( Iacono et al. 2008 ), Dudhia shortwave radiation ( Dudhia 1989 ), Yonsei University planetary boundary layer ( Hong et al. 2006 ), revised MM5 surface layer ( Jiménez et al. 2012 ), and Noah land surface model ( Chen and Dudhia 2001 ) parameterizations. The Kain

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Philip T. Bergmaier, Bart Geerts, Leah S. Campbell, and W. James Steenburgh

the formation of a shallow “shoreline” band ( Braham 1983 ; Hjelmfelt and Braham 1983 ; Kelly 1986 ). Both bands tend to occur under relatively weak onshore prevailing winds, since stronger onshore winds may inhibit land-breeze development ( Biggs and Graves 1962 ; Walsh 1974 ; Hjelmfelt 1990 ). Recently, Steiger et al. (2013) coined the term long-lake-axis-parallel (LLAP) band, a term that has since seen more widespread use (e.g., Minder et al. 2015 ; Veals and Steenburgh 2015 ; Campbell

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David A. R. Kristovich, Luke Bard, Leslie Stoecker, and Bart Geerts

clouds rapidly (e.g., Agee and Gilbert 1989 ; Ballentine et al. 1998 ), and 2) maintenance of the circulation from a lake-effect snowband from an upwind lake as it crosses over the intervening land surface and provides a “boost” to convective circulations over the downwind lake (e.g., Rose 2000 ; Wright et al. 2013 ; Deacu et al. 2012 ). Such processes have been shown to be important for interactions between the Great Lakes and smaller downwind lakes (e.g., Laird et al. 2010 ). Rose (2000

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Dan Welsh, Bart Geerts, Xiaoqin Jing, Philip T. Bergmaier, Justin R. Minder, W. James Steenburgh, and Leah S. Campbell

Ontario ( Jiusto and Kaplan 1972 ; Niziol et al. 1995 ; Kristovich and Steve 1995 ; Steiger et al. 2013 ; Veals and Steenburgh 2015 ). LLAP bands result, in part, from a lake-scale secondary circulation with low-level convergence ( Peace and Sykes 1966 ) and upper-level divergence ( Kristovich et al. 2016 ; Bergmaier et al. 2015 ). It appears that lake-effect snowfall is heavier downwind of the shoreline (over land) than offshore in most lake-effect systems (LeS), including LLAP events. This

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Peter G. Veals and W. James Steenburgh

the Great Salt Lake of Utah. Synoptic, mesoscale, lake-surface, and land surface conditions influence the areal coverage, intensity, and organization of lake-effect precipitation systems, leading to a rich morphological spectrum that includes the following: Wind-parallel bands generated by land-breeze convergence when the prevailing flow is oriented along the long axis of an elongated body of water (e.g., Peace and Sykes 1966 ; Passarelli and Braham 1981 ; Braham 1983 ; Hjelmfelt 1990

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

the Mellor–Yamada level 2.0 scheme ( Mellor and Yamada 1974 ; 1982 ) to parameterize the surface layer, with a viscous sublayer over water surfaces (e.g., Black 1994 ). NARR surface fluxes are calculated using Monin–Obukov functions in conjunction with the Mellor–Yamada level 2.0 scheme; additional details are provided in Black (1994) . In addition, NARR uses an updated version of the Noah land surface model (e.g., Ek et al. 2003 ; Mesinger et al. 2006 ). Most unstable convective available

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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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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

-band Profiling Radar (XPR) showed many more strong updrafts over land (approaching 8 m s –1 ) in the snowband cells during IOP 5. However, cloud depths were 0.5 km greater in IOP 7 and the lake-induced buoyant instability calculated using upwind radiosonde and mean lake surface temperature data (method described in Minder et al. 2015 ) was near 1300 J kg –1 (more than 4 times larger than in IOP 5). Many of the lightning strikes in both events occurred near a wind farm of nearly 200 turbines on Tug Hill

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