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

mechanisms for InPen. In particular, we investigate the role of vertically differential temperature advection on InPen, which is not addressed by Villani et al. (2017) . Additional insight into the large-scale predictors of InPen will further equip forecasters to accurately leverage observations and numerical weather prediction (NWP) model guidance. In the remainder of the paper, we first describe the datasets and data processing techniques used in this study. We then investigate physical mechanisms and

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Philip T. Bergmaier and Bart Geerts

about the fall speed estimates and their uncertainties are discussed in appendix A . Fig . 1. (a) WRF Model domains, and (b) regional map of Lake Ontario showing relevant locations and geographic features discussed throughout the text. b. Dual-Doppler synthesis Radial velocity measurements from the two downward-pointing WCR beams were used to retrieve the 2D wind field in the vertical plane below the UWKA via an airborne dual-Doppler (DD) synthesis technique described by Leon et al. (2006) and

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Seth Saslo and Steven J. Greybush

reducing initial condition error and involves statistically combining model forecasts and observations ( Kalnay 2003 ). In particular, the ensemble Kalman filter (EnKF; Evensen 1994 ) is a DA technique that uses a flow-dependent background error covariance from a forecast model ensemble, which often improves the final analysis compared to other methods, such as three-dimensional variational data assimilation (3DVAR; e.g., M. Zhang et al. 2011 ; Miyoshi et al. 2010 ; Buehner et al. 2010 ), and has

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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

-allowing models run by universities and local NWS offices. As a part of this forecasting experience, students considered various model solutions for the timing, placement, and type of LeS and were exposed to model discrepancies that were significant at times. The student teams typically presented their forecasts at the daily briefings and led the discussions during off-time briefings or when NWS personnel were not available. Furthermore, the students benefitted from viewing scientific tools and techniques

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

://doi.org/10.1175/MWR-D-15-0412.1 . 10.1175/MWR-D-15-0412.1 Eipper , D. T. , G. S. Young , S. J. Greybush , S. Saslo , T. D. Sikora , and R. D. Clark , 2018 : Predicting the inland penetration of long-lake-axis-parallel snowbands . Wea. Forecasting , 33 , 1435 – 1451 , https://doi.org/10.1175/WAF-D-18-0033.1 . 10.1175/WAF-D-18-0033.1 Grell , G. A. , and D. Dévényi , 2002 : A generalized approach to parameterizing convection combining ensemble and data assimilation techniques . Geophys. Res

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Philip T. Bergmaier and Bart Geerts

of the Great Salt Lake: Overview and forecast problems . Wea. Forecasting , 8 , 181 – 193 , doi: 10.1175/1520-0434(1993)008<0181:TLEOTG>2.0.CO;2 . Chang , S. , and R. R. Braham Jr. , 1991 : Observational study of the development of a snow producing convective internal boundary layer over Lake Michigan . J. Atmos. Sci. , 48 , 2265 – 2279 , doi: 10.1175/1520-0469(1991)048<2265:OSOACI>2.0.CO;2 . Damiani , R. , and S. Haimov , 2006 : A high-resolution dual-Doppler technique for

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

and automated precipitation gauge measurements of 6-h accumulated LPE at SC and NR ( Fig. 2 ). Although the manual measurements provide greater accuracy, they lack temporal resolution. As an alternative, we implement a technique described by Wüest et al. (2010) to disaggregate the 6-h manual LPE measurements into shorter intervals using high-frequency LPE estimates derived from ~5- to 6-min 0.5° KTYX radar scans. Fig . 2. Observed total snow depth (cm, blue line), automated 6-h interval snow

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

within the LLAP band (see section 4 ). b. Dual-Doppler synthesis Radial velocities from the two downward-pointing WCR beams, oriented ~30° apart, can be utilized to obtain the 2D wind field in a quasi-vertical plane below the aircraft via DD synthesis ( Leon et al. 2006 ). The Leon et al. (2006) DD synthesis technique was further refined by Damiani and Haimov (2006) , whose software has been used in this study and in many others (e.g., Geerts et al. 2006 , 2011 , 2015 ; Yang and Geerts 2006

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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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