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P. L. Heinselman, B. L. Cheong, R. D. Palmer, D. Bodine, and K. Hondl

Surveillance Radar-1988 Doppler (WSR-88D) at Norman (KOUN), 2) hydrometeor classification products, and 3) quantitative precipitation estimates showed the potential for polarimetric radar to significantly benefit the decision making and forecasts of operational meteorologists. The JPOLE also contributed to the decision to upgrade the WSR-88D network with dual-polarization technology, which is anticipated during 2010–12. Given the successful attainment of refractivity retrievals during IHOP 2002 ( Weckwerth

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Lance M. Leslie, Bruce W. Buckley, and Mark Leplastrier

1. Introduction Recent studies have underlined the operational utility of the near-surface wind data from the SeaWinds scatterometer on board the National Aeronautics and Space Administration (NASA) Quick Scatterometer (QuikSCAT) satellite. For example, Atlas et al. (2001) provide a detailed review of the impact of scatterometer data on numerical weather prediction and a discussion of the first successful use of QuikSCAT data by operational marine forecasters. Chelton and Freilich (2005

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Xiaqiong Zhou, Yuejian Zhu, Dingchen Hou, and Daryl Kleist

sample the error probability density functions (PDFs) of the analyzed atmospheric state and represent the analysis uncertainty. Several schemes have been developed and implemented at operational forecast centers, including the singular vector method at ECMWF ( Buizza and Palmer 1995 ; Molteni et al. 1996 ), the bred vector method at NCEP ( Toth and Kalnay 1993 ), and the ensemble data assimilation method at the Canadian Meteorological Centre (CMC; Houtekamer et al. 1996 ; Houtekamer and Mitchell

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Michael E. Charles and Brian A. Colle

1. Introduction a. Background Extratropical cyclones are responsible for a wide range of hazardous weather, including flooding, severe convection, strong winds, snow, and ice. The skill of numerical weather prediction models in forecasting these major storm events has varied. Some storms, such as the Superstorm of 1993 along the U.S. east coast, have been relatively well forecast several days in advance ( Uccellini et al. 1995 ). In contrast, operational models have poorly predicted other

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Eric Metzger and Wendell A. Nuss

utilized operationally by the NWS Forecast Office (NWSFO) in Huntsville since 2003 ( Darden et al. 2010 ), where forecasters note a sudden increase in total lightning activity prior to the onset of severe weather. These lightning jumps occurred as much as 30 min prior to the occurrence of severe weather ( Darden et al. 2010 ), confirming earlier studies by Williams et al. (1999) and Goodman et al. (2005) . The observations from these prior studies and the Huntsville site led to the development of

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Julie L. Demuth, Rebecca E. Morss, Isidora Jankov, Trevor I. Alcott, Curtis R. Alexander, Daniel Nietfeld, Tara L. Jensen, David R. Novak, and Stanley G. Benjamin

, not the only factor, in managing risk. Risk information that considers this multifaceted decision context can then be developed accordingly. This risk communication approach underpins the goal of the social science research presented here, which is to understand NWS forecasters’ IDSS-focused decision contexts in order to identify their needs for new and improved CAM ensemble information. Our research builds on a foundation of past work that has investigated public- and private-sector operational

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Xiaqiong Zhou, Yuejian Zhu, Dingchen Hou, Yan Luo, Jiayi Peng, and Richard Wobus

1. Introduction The Global Ensemble Forecast System (GEFS) has been one of the most important components of NOAA’s environmental prediction operational systems since its implementation in 1993 ( Toth and Kalnay 1993 , 1997 ). The forecast skill of the GEFS has been improved significantly since then, benefiting from upgrades in ensemble initial perturbation generation ( Wei et al. 2006 , 2008 ), the inclusion of stochastic model perturbations ( Hou et al. 2006 ), higher model resolution, and

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Charles R. Sampson, Paul A. Wittmann, Efren A. Serra, Hendrik L. Tolman, Jessica Schauer, and Timothy Marchok

.S. naval vessel could run into the billions of dollars ( U.S. Navy 2008 ). Sortie decisions are frequently made at least 72 h ahead of a TC passage in order to provide enough lead time for ships to get under way and out of the path of the approaching TC, so long-range (3–5 day) forecasts are of great interest to U.S. Navy operational forecasters. Similar arguments can be made concerning the costs of disaster preparedness for non–U.S. Navy vessels, coastal communities, and offshore oil platforms

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Thomas M. Hamill, Jeffrey S. Whitaker, Daryl T. Kleist, Michael Fiorino, and Stanley G. Benjamin

1. Introduction Recently, Hamill et al. (2011 , hereafter H11 ) verified global ensemble predictions of 2009’s Northern Hemisphere summer tropical cyclone forecasts initialized with a global ensemble Kalman filter (EnKF) system. The assimilation and forecasts were performed at a relatively high resolution, T384L64, or approximately 31 km at 25°N. 1 The significant improvement of these experimental forecasts relative to the operational global ensemble guidance provided by the National Centers

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Sung-Hun Kim, Il-Ju Moon, and Pao-Shin Chu

predictions from CSTIPS-DAT for Typhoons (a) Pewa (2013), (b) Fitow (2013), (c) Pabuk (2013), (d) Faxai (2014), (e) Kalmaegi (2014), and (f) Phanfone (2014). The thick line denotes observations (RSMC best-track data), and the colored lines are individual CSTIPS-DAT predictions. The numbers above the x axis denote the assigned cluster number. It is also interesting to compare the CSTIPS-DAT model with the latest operational dynamical models such as the Hurricane Weather Research and Forecasting Model

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