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David O. Blanchard

1. Introduction Occurrences of supercell thunderstorms producing widespread severe weather in northern Arizona are most likely to arise during the transition between the moist, subtropical environment of the warm-season North American monsoon regime (NAM; Adams and Comrie 1997 ) and the first, early season incursions of midlatitude baroclinic systems. The presence of copious tropical moisture, combined with steeper lapse rates, increased buoyant instability, and, more importantly, deep

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Andy Taylor and Gary B. Brassington

forecast narratives in those regions also underplay remotely forced coastal sea level is beyond our scope, but a waveguide perspective may offer some insight into explaining the Di Liberto et al. (2011) finding that a 5-day bias correction improved forecasts skill for particular depth-integrated surge models in a North American context. The way that numerical forecast guidance is framed informs the forecast narratives that can ultimately influence decisions made at the coast. Given the apparently

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Nicholas A. Bond and Clifford F. Mass

three cities are unchanged. The resources available to the students for making these forecasts include all available observations (station, satellite, radar, etc.) as well as analyses and numerical weather prediction (NWP) model data from the National Centers for Environmental Prediction’s Global Forecast System (GFS) and North American Mesoscale (NAM) models. For the type 3 forecasts for SEA, they are allowed to consider the output from the high-resolution Weather Research and Forecasting Model

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David R. Novak, Keith F. Brill, and Wallace A. Hogsett

( Manikin 2005 ). Precipitation type for non-NCEP models is determined by applying a simple decision tree algorithm using near-surface (2 m) temperature; and temperatures at the 925-, 850-, and 700-hPa mandatory isobaric levels. At each grid point where the precipitation type is diagnosed as snow, an SLR is applied. The SLR is an average of the value obtained using the Roebber et al. (2007) neural network algorithm (Rnna) applied to North American Mesoscale Model (NAM), the value from Rnna applied to

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Michael J. Brennan, Gary M. Lackmann, and Kelly M. Mahoney

at 1200 UTC 16 Feb 2004 of 900–700-hPa layer potential vorticity (shaded as in legend, PVU), sea level pressure (dashed contours, hPa), and 3-h model forecast of convective precipitation (solid contours, mm). (b) As in (a) but for a 36-h forecast valid 0000 UTC 18 Feb. (c), (d) As in (a), (b) but for a Workstation Eta KF run. Fig . 6. North American Regional Reanalysis (NARR) 900–700-hPa potential vorticity (contours every 0.25 PVU starting at 0.5 PVU) and 2-km radar mosaic reflectivity imagery

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Clark Evans, Donald F. Van Dyke, and Todd Lericos

precipitation forecast issued at 0000 UTC 22 August 2008 by the Hydrometeorological Prediction Center (HPC) and kinematic and thermodynamic forecast fields from the 0000 UTC 22 August 2008 cycles of the Global Forecast System (GFS), North American Mesoscale (NAM), and European Centre for Medium-Range Weather Forecasts (ECMWF) deterministic models. Utilizing these data and their subjective interpretation of the forecast event, they were asked to make a 72-h deterministic quantitative precipitation forecast

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