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Shih-Yu Wang and Adam J. Clark

1. Introduction Seasonal precipitation exhibits a maximum center over the upper Midwest during midsummer (July–August). This precipitation center occurs in close association with the northward extension of the low-level jet (LLJ) and the retreat of the upper-level jet stream (e.g., Higgins et al. 1997 ; Wang and Chen 2009 ). Such a circulation evolution forms a preferred time frame for the “warm-season pattern,” consisting of a slow-moving ridge over the western United States and a synoptic

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Robert R. Gillies, Shih-Yu Wang, Jin-Ho Yoon, and Scott Weaver

predicting persistent inversions for Salt Lake City, Utah. 2. Datasets and the inversion–ISO relationship The CFS is a fully coupled ocean–land–atmosphere dynamical seasonal prediction system and has been operational at NCEP since August 2004. Model specifications of the CFS are detailed in Saha et al. (2006) . The NCEP provides historical CFS hindcast data starting at 1981 and extending through 2008. For each predicted period, the CFS hindcast is initialized from three ensemble means (denoted by μ 1

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William A. Gallus Jr., Nathan A. Snook, and Elise V. Johnson


Radar data during the period 1 April–31 August 2002 were used to classify all convective storms occurring in a 10-state region of the central United States into nine predominant morphologies, and the severe weather reports associated with each morphology were then analyzed. The morphologies included three types of cellular convection (individual cells, clusters of cells, and broken squall lines), five types of linear systems (bow echoes, squall lines with trailing stratiform rain, lines with leading stratiform rain, lines with parallel stratiform rain, and lines with no stratiform rain), and nonlinear systems. Because linear systems with leading and line-parallel stratiform rainfall were relatively rare in the 2002 sample of 925 events, 24 additional cases of these morphologies from 1996 and 1997 identified by Parker and Johnson were included in the sample.

All morphologies were found to pose some risk of severe weather, but substantial differences existed between the number and types of severe weather reports and the different morphologies. Normalizing results per event, nonlinear systems produced the fewest reports of hail, and were relatively inactive for all types of severe weather compared to the other morphologies. Linear systems generated large numbers of reports from all categories of severe weather. Among linear systems, the hail and tornado threat was particularly enhanced in systems having leading and line-parallel stratiform rain. Bow echoes were found to produce far more severe wind reports than any other morphology. The flooding threat was largest in broken lines and linear systems having trailing and line-parallel stratiform rain. Cellular storms, despite much smaller areal coverage, also were abundant producers of severe hail and tornadoes, particularly in broken squall lines.

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Ming Cai, Chul-Su Shin, H. M. van den Dool, Wanqiu Wang, S. Saha, and A. Kumar

long-range weather prediction as it used to be called) is the outgrowth of technology employed originally for numerical weather prediction so the earliest of such climate prediction efforts neglected to address changing GHGs. Currently, few operational weather and climate forecast centers use coupled climate models with time-evolving GHG concentrations for their operational seasonal climate predictions. The assumption behind such a configuration, other than tradition, is that the global warming

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Hannah R. Young and Nicholas P. Klingaman

.1038/43854 Trenberth , K. E. , 1997 : The definition of El Niño . Bull. Amer. Meteor. Soc. , 78 , 2771 – 2777 ,<2771:TDOENO>2.0.CO;2 . 10.1175/1520-0477(1997)078<2771:TDOENO>2.0.CO;2 van den Hurk , B. , F. Doblas-Reyes , G. Balsamo , R. D. Koster , S. I. Seneviratne , and H. Camargo , 2012 : Soil moisture effects on seasonal temperature and precipitation forecast scores in Europe . Climate Dyn. , 38 , 349 – 362 ,

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Julián David Rojo Hernández, Óscar José Mesa, and Upmanu Lall

1. Introduction El Niño–Southern Oscillation (ENSO) is the most important interannual climate mode, with significant effects on the planetary hydrological cycle, agriculture, ecosystems, health, and society. The name “El Niño” was proposed at the end of the nineteenth century by Peruvian geographers to describe the warming of the surface waters of the Pacific Ocean around the coasts of Peru and Equator during Christmas ( Carranza 1891 ). Later Sir Gilbert Walker described the existence of the

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Christophe Lavaysse, Tim Stockdale, Niall McCormick, and Jürgen Vogt

subseasonal and seasonal time scales ( Stockdale et al. 1998 ; Vitart et al. 2014 ). Therefore, ensemble prediction systems (EPS) have been developed in order to forecast also the uncertainties that are associated with NWP models. These “probabilistic” forecasts become particularly important when assessing the risks associated with rare weather events such as droughts and tropical cyclones ( Hamill et al. 2012 ; Dutra et al. 2013 , 2014 ), and for identifying uncertainties in the forecasts ( Buizza et

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Ching-Sen Chen, Yi-Leng Chen, Che-Ling Liu, Pay-Liam Lin, and Wan-Chin Chen

to typhoons and other heavy rainfall events in Taiwan were about 2.8 billion New Taiwan dollars (approximately $86 million U.S.) with more than 100 casualties ( Shieh 1986 ). Most of the previous studies on heavy rainfall events over Taiwan are based on case studies, especially on the roles of synoptic, mesoscale, and local-scale processes as well as the orographic effects on the development of heavy rainfall (e.g., Wang et al. 1990 ; Akaeda et al. 1995 ; Li et al. 1997 ; Teng et al. 2000

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Richard H. Grumm, Robert J. Oravec, and Anthony L. Siebers

and 48 h, respectively. The results show that the skill of the NGM forecasts of surface cyclones displayed both seasonal and annualvariability. The seasonal variability is represented by overall smaller errors in the summer and larger errors inthe winter. The NGM tended to overdeepen surface cyclones in all but the summer months. A large part of the pressureerror was due to the model's inability to fill cyclones properly and a tendency to forecast systems to deepenwhen they were observed to

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Ronald M. Reap

network of direction-findingstations in Alaska were examined to determine the seasonal, diurnal, and spatial distributions of cloud-to-groundlightning, including the effects of the underlying topography on the timing, location, and magnitude of thelightning activity. The interior of Alaska was found to exhibit a continental type climate with a pronouncedafternoon maximum in lightning activity and no significant nocturnal activity. Over 90% of the strikes werefound to occur during June and July, the

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