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David R. Novak, David R. Bright, and Michael J. Brennan

1. Introduction Uncertainty is a fundamental characteristic of hydrometeorological (hydrologic, weather, and seasonal climate) prediction, and is a consequence of the inherent chaotic nature of the atmosphere, inadequate observations, and numerical weather prediction (NWP) deficiencies ( NRC 2006 ). Thus, the assessment and communication of uncertainty is an inherent part of any forecast process. The assessment of uncertainty in modern operational forecasting has largely relied on the use of

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Chermelle Engel and Elizabeth Ebert

techniques that try to predict the best “model of the day” ( Hibon and Evgeniou 2005 ; Fritsch et al. 2000 ). Combining multiple individual forecasts to increase accuracy is an approach used in various fields from business to psychology ( Clemen 1989 ). The operational consensus forecast (OCF) scheme developed at the Bureau combines multimodel guidance. Daily OCF has been shown to produce objective guidance for forecast fields such as maximum and minimum daily air temperatures that is competitive with

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Ralph F. Milliff and Peter A. Stamus

1. Introduction The research value of satellite ocean surface vector wind (SVW) data has been well established over more than a decade of published work, across a broad range of studies. What is also emerging is that these data play essential roles in many operational applications as well, including (i) numerical weather prediction (NWP) and (ii) the manual production of forecasts, analyses, and warnings by trained analysts (i.e., forecasters). SVW impacts in NWP have been highlighted recently

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Keqi Zhang, Yuepeng Li, Huiqing Liu, Jamie Rhome, and Cristina Forbes

continuity equation by maintaining nonlinear advective acceleration and diffusion terms. These models and their extensions also include the wetting–drying component and have recently been applied to the simulation of overland flooding ( Bunya et al. 2010 ; Forbes et al. 2009 ; Forbes et al. 2010 ; Huang et al. 2010 ; Shen et al. 2006 ; Sheng et al. 2010 ; Xie et al. 2004 ; Xu et al. 2010 ). However, these models cannot be used directly for operational surge forecasts because most of them are

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Natacha B. Bernier, Jose-Henrique G. M. Alves, Hendrik Tolman, Arun Chawla, Syd Peel, Benoit Pouliot, Jean-Marc Bélanger, Pierre Pellerin, Mario Lépine, and Michel Roch

continues to receive considerable attention from both the research and operational communities (e.g., Tolman et al. 2013 ). Several countries have already developed and implemented global wave forecast systems—for example, the European Center for Medium-Range Weather Forecasts [ Bidlot (2012) and references therein], the Met Office ( Li and Saulter 2014 ), the U.S. Navy ( Rogers et al. 2014 ), and the National Centers for Environmental Prediction ( Chawla et al. 2013 ), and additional centers are

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Joshua H. Cossuth, Richard D. Knabb, Daniel P. Brown, and Robert E. Hart

). Tropical cyclogenesis has therefore become the subject of extensive research. Further, the operational community has begun to enhance their public products, including forecasts of TC formation, due to great user interest in that information. This paper describes historical data and analyses and their use in producing a forecasting tool that can assist operational centers in making present-day genesis forecasts and in assessing the skill of new and future forecast capabilities arising from ongoing

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Adam J. Clark, William A. Gallus Jr., and Morris L. Weisman

of forecasts as perceived by human forecasters. The purpose of this study is to demonstrate the usefulness of a neighborhood-based equitable threat score (ETS; Schaefer 1990 ) to compare precipitation forecasts from experimental convection-allowing Weather Research and Forecasting Model (WRF; Skamarock et al. 2005 ) simulations conducted during April–July 2004–08 by the National Center for Atmospheric Research (NCAR) to operational North American Mesoscale (NAM; Janjić 2003 ) model forecasts

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Amanda Burke, Nathan Snook, David John Gagne II, Sarah McCorkle, and Amy McGovern

NOAA’s Hazardous Weather Testbed (HWT) Spring Forecasting Experiment (SFE). For example, during the 2010 HWT SFE operational forecasters subjectively indicated that the CAM guidance improved convection forecasts, compared to traditional convective-parameterizing schemes ( Clark et al. 2012 ). Also, Gallo et al. (2017) noted that CAMs played an important role in reliable short-term forecasts, especially hourly forecasts, during the 2015 HWT SFE. For day-ahead forecasts (12–36-h lead time), CAM

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Amanda Burke, Nathan Snook, David John Gagne II, Sarah McCorkle, and Amy McGovern

NOAA’s Hazardous Weather Testbed (HWT) Spring Forecasting Experiment (SFE). For example, during the 2010 HWT SFE operational forecasters subjectively indicated that the CAM guidance improved convection forecasts, compared to traditional convective-parameterizing schemes ( Clark et al. 2012 ). Also, Gallo et al. (2017) noted that CAMs played an important role in reliable short-term forecasts, especially hourly forecasts, during the 2015 HWT SFE. For day-ahead forecasts (12–36-h lead time), CAM

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Vijay Tallapragada, Chanh Kieu, Samuel Trahan, Zhan Zhang, Qingfu Liu, Weiguo Wang, Mingjing Tong, Banglin Zhang, and Brian Strahl

mi at 1–5-day forecast lead times, respectively ( Evans and Falvey 2013 ), indicating about 20% larger errors in the WPAC compared to NATL. Given the high degree of uncertainty of TC forecasts in this ocean basin, consensus of multiple models or ensemble forecasts is an optimal choice for improving the operational forecast skill as these ensemble approaches could take into account the strengths and weaknesses of each individual model (e.g., Evans and Falvey 2013 ). In an attempt to support

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