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Leonard A. Smith, Hailiang Du, and Sarah Higgins

1. Introduction Forecasters are often faced with an ensemble of model simulations that are to be incorporated into quantitative forecast system and presented as a probabilistic forecast. Indeed, ensembles of initial conditions have been operational in weather centers in both the United States ( Kirtman et al. 2014 ) and Europe ( Palmer et al. 2004 ; Weisheimer et al. 2009 ) since the early 1990s, and there is a significant literature on their interpretation ( Raftery et al. 2005 ; Hoeting et

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Thomas M. Hamill and Jeffrey S. Whitaker

is, of course, well established, being the essence of model output statistics (MOS) techniques ( Glahn and Lowry 1972 ; Carter et al. 1989 ). If today’s numerical forecast indicates relatively ordinary conditions, then perhaps the past few months or year will have exhibited enough other similar scenarios that the current forecast can be properly adjusted. But what if the weather is relatively unusual? Suppose high rain amounts are forecast for a desert location; it is likely that there will have

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Jiaxin Black, Nathaniel C. Johnson, Stephen Baxter, Steven B. Feldstein, Daniel S. Harnos, and Michelle L. L’Heureux

1. Introduction Subseasonal forecasting for lead times between 10 and 30 days is in general a difficult task but one that has been receiving increasing focus. At longer lead times, the importance of the initial conditions progressively diminishes, and the impact of slowly varying boundary conditions increases, though they have a more modest impact on the weather and climate. From the end-user perspective, however, skillful subseasonal forecasting is of great importance because it would provide

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John C. Derber

exactly in the VCA technique, some of the effects of systematic model errors can beremoved from the assimilation. Thus, the VCA technique was able to consistently fit the data better than theadjoint technique. Predictions from the results from the assimilation techniques showed that the forecast fromthe adjoint technique's solution was consistently inferior to those from the VCA technique and those from theGeophysical Fluid Dynamics Laboratory's (GFDL's) First GARP (Global Atmospheric Research Program

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UDC 651.609.57:661.616.23(281)Performance Analysis of the HURRANTropical Cyclone Forecast SystemCHARLES J. NEUMANN '"Spaceflight Meteorology Group, National Weather Sewice,NOAA, Miami. Fla.JOHN R. HOPE-National Hurricane Center, National Weather Sewice,NOAA. Miami, Fla.IABSTRACT-The HURRAN (hurricane analog) technique, 1,000 forecast situations. Results arc stratified accordinga fully computerized objective forecast aid making use of to initial direction and speed of movement, of the samplepast

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Fukang Yin, Guoli Wu, Jianping Wu, Jun Zhao, and Junqiang Song

in YHGSM. Table 5. The wall-clock time of 50 time steps in YHGSM (unit: s). 3) Test cases In this section, three test cases including the zonal wavenumber-4 Rossby–Haurwitz wave ( Williamson et al. 1992 ), the baroclinic instability wave ( Jablonowski and Williamson 2006 ), and the true forecast on YHGSM are employed to validate the correctness and reliability of YHGSM using FLT. The accuracy of SHT is estimated by the following error functions: The u wind in the initial fields of the Rossby

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June 1966Jack D. Tracy407ACCURACY OF ATLANTIC TROPICAL CYCLONE FORECASTS JACK D. TRACYNational Hurricane Research Laboratory, Environmental Science Services Administration, Miami, Fla. ABSTRACT During the past several years a number of techniques have been developed for forecasting the motion of tropicalcyclones over areas of the Atlantic, Caribbean, and Gulf of Mexico. Many of these have been tested on an opera-tional basis. These forecasts have been

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André Tremblay, Anna Glazer, Wanda Szyrmer, George Isaac, and Isztar Zawadzki

~Z_Ya Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada (Manuscript received 29 March 1994, in final form 29 November 1994) ABSTRACT Using parametetizatious of cloud microphysics, a technique to forecast supe~eocled cloud events is suggested. Thistechnique can be coupled on the mesoscale with a prognostic equation for cloud water to improve aircra~ icingforecasts. The procedure is validated using comparisons with airborne measurements from the

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Markus Dabernig, Georg J. Mayr, Jakob W. Messner, and Achim Zeileis

1. Introduction Weather forecasts are important for many aspects of life whether professional or private. These weather forecasts rely mainly on numerical weather prediction (NWP) models, which solve partial differential equations. However, it is impossible to solve these equations exactly and errors occur, which grow with forecasting horizon. Additionally, because of limited computational power, the numerical grid of these forecast models has to be coarse and subgrid processes have to be

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Samson Brand, James M. Long, Jack W. Blelloch, and Glenn D. Hamilton

for the North Indian Ocean area is described. The program is a statistical computer technique to provide forecasts for Bay of Bengal and Arabian Sea tropical cyclones from12 to 72 h.1. Introduction Since 1970 a number of tropical cyclone analog forecast techniques have been developed and have beenshown to be very useful to the operational forecaster.The success of the hurricane analog approach in thewestern North Atlantic (Hope and Neumann, 1970;Simpson, 1971; and Neumann and Hope, 1972) and

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