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William S. Lamberson, Ryan D. Torn, Lance F. Bosart, and Linus Magnusson

of individual high-impact extratropical cyclones are still occasionally characterized by large errors. Examples from North America include the snowstorm of 26–27 December 2010, which was poorly predicted 3–5 days in advance ( Zheng et al. 2013 ), and the “surprise” snowstorm of 24–25 January 2000, which was poorly forecasted even 1 to 2 days in advance ( Zhang et al. 2002 ). Examples from Europe include Cyclones Martin and Lothar from December 1999, both of which were poorly predicted 1–3 days in

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Shawn M. Milrad, Eyad H. Atallah, and John R. Gyakum

1. Introduction Atlantic Canada ( Fig. 1 ), and more specifically, St. John’s, Newfoundland (CYYT), is a location susceptible to extreme precipitation events, particularly in the cool season ( Stewart et al. 1987 ), defined in Milrad et al. (2009) as October–April. Located at the confluence of several North American storm tracks ( Milrad et al. 2009 ) and near the convergence zone of the cold southward-flowing Labrador Current and the warm northward-flowing Gulf Stream current ( Aguado and

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Amit Bhardwaj, Vasubandhu Misra, Ben Kirtman, Tirusew Asefa, Carolina Maran, Kevin Morris, Ed Carter, Christopher Martinez, and Daniel Roberts

forced with the SST forecast produced from another coupled GCM. This is necessary to supply lateral boundary conditions for all prognostic variables of the full atmosphere based on the global field to RSM at a 6-h interval. The SST forecast was made available at a daily interval from one of the ensemble members of the Community Climate System Model, version 4 (CCSM4), which was also initialized on 1 November. CCSM4 is part of the North American Multimodel Ensemble (NMME) suite ( Kirtman et al. 2014

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Gary A. Wick, Paul J. Neiman, F. Martin Ralph, and Thomas M. Hamill

prediction systems to accurately forecast the IWV signature of ARs in the northeast Pacific Ocean roughly in the region from Hawaii to the west coast of North America. The existence and characteristics of ARs in the model fields are compared against corresponding satellite-derived observations of IWV. Control forecasts from five prominent ensemble prediction systems over the months of October–March for the three cool seasons from 2008–09 to 2010–11 are evaluated as a function of lead time out to 10 days

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Hong Guan and Yuejian Zhu

distribution. The climatological distribution for the 2-m temperature and precipitation are assumed to be a normal distribution C = N ( x , μ , σ 2 ) and a gamma distribution C = Γ( x , k , θ ), respectively. Previous work ( Hou et al. 2014 ) demonstrated that a gamma distribution can well simulate the distribution of precipitation over North America. The x , μ , σ 2 , k , and θ represent the location, mean, variance, shape factor, and scale parameter for the corresponding distributions

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Joseph B. Pollina, Brian A. Colle, and Joseph J. Charney

:// ), and Plymouth State University ( ) were used. The North American Regional Reanalysis (NARR; Mesinger et al. 2006 ) at 32-km horizontal grid spacing was used to composite the large-scale flow evolution and other meteorological variables. Spatial composites were created for regions 1 and 2 separately using the actual fires dates. Since wildfire start times were not available for many fires, daily composites of sea level pressure (SLP) and 500-hPa geopotential

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Brice E. Coffer, Lindsay C. Maudlin, Peter G. Veals, and Adam J. Clark

corresponding dryline forecasts from the 12-km grid-spacing North American Mesoscale Model (NAM; Rogers et al. 2009 )—the operational mesoscale model run by the National Centers for Environmental Prediction (NCEP). Daily 0000 UTC initializations of the NSSL-WRF and NAM are compared over the 5-yr period of 2007–11 for the months April–June. These months were chosen because they cover the approximate period with the highest frequency of dewpoint temperature gradients and drylines over the southern U.S. high

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Garrett B. Wedam, Lynn A. McMurdie, and Clifford F. Mass

. Harper et al. (2007) and Kalnay et al. (1998) documented the increasing skill of the National Centers for Environmental Prediction’s (NCEP) operational models for 500-mb heights and other forecast parameters. But even with recent improvements in numerical weather prediction, major failures of short-to-medium-range forecasts still occur regularly. McMurdie and Mass (2004) showed that NCEP’s North American Mesoscale (NAM) model experienced large 0–48-h forecast errors over the northeast Pacific

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Pierre Bourgouin

vertical temperature profile needed to establish the different criteria. The precipitation had to be reported within 1 h of the time that the sounding was taken and at the same location; hence, the number of cases per season is relatively limited. The data were taken from the 1989–90 and 1990–91 cold seasons over North America. The database consisted of 54 cases used to discriminate between freezing rain and ice pellets, 119 cases for rain and snow, and 3–5 cases of ice pellets and rain. These last

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Ryan Lagerquist, Amy McGovern, and David John Gagne II

people with rare expertise. Our labels already existed, but in general this is a problem for supervised ML (the type where correct answers are needed for training). When human labels are unavailable the best option may be labels from a set of algorithms with different biases (e.g., the thermal and wind-shift methods discussed in Schemm et al. 2015 ). Predictors come from the North American Regional Reanalysis (NARR; Mesinger et al. 2006 ), which outputs data every three hours (synchronously with

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