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Lawrence Coy, Stephen Eckermann, and Karl Hoppel

analyses were available every 6 h on a 1.25° × 1° longitude–latitude grid at 36 pressure levels, from 1000 to 0.2 hPa. The time period examined covered January–February 2006. To explore the dependence of the major stratospheric warming on tropospheric forcing, we also use analyses and forecasts based on a high-altitude version of the Navy’s operational global forecast and data assimilation system, the Navy Operational Global Atmospheric Prediction System (NOGAPS; Hogan and Rosmond 1991 ; Goerss and

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Robert E. Tuleya, Morris Bender, Thomas R. Knutson, Joseph J. Sirutis, Biju Thomas, and Isaac Ginis

more realistic initial and boundary conditions and land processes and the development of the moveable, nested grid system ( Kurihara et al. 1979 ), still unique and in use today in research and operations. Because of its capabilities, it was transitioned into NCEP (1995) and U.S. Navy (1996) operational suites. Besides real-data forecasts and process studies, it also became a valuable tool for climate studies (e.g., Knutson et al. 1998 ; Bender et al. 2010 ). An idealized framework will be used

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J. B. Klemp and D. R. Lilly

estimation of maximum surface winds from upstream sounding data. Comparisonsof the model predictions with observations are sufficiently encouraging to suggest the future utilization ofsuch a model for operational forecasting. The differences between the predictions of this theory and thoseof hydraulic jump models are explored.Introduction Strong downslope winds, often gusting to well abovenominal hurricane force (34 m s-~) are observed inmany mountainous regions of the world. The generationof such

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Hailiang Du and Leonard A. Smith

to a model trajectory. This means the cost of obtaining useful pseudo orbits is reduced substantially, which in turn makes the approach more attractive for use in operational prediction models (e.g., Judd et al. 2008 ). The PDA c approach can also play a role in forming ensembles of initial conditions. To capture the uncertainty in the nowcast and forecast in numerical weather prediction, some approaches ( Leutbecher and Palmer 2008 ) sample the model’s more rapidly growing directions at the

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Falko Judt and Shuyi S. Chen

) . During the RAINEX field program, high-resolution MM5 forecasts were made with various large-scale operational model forecasts as initial and lateral boundary conditions, including Geophysical Fluid Dynamics Laboratory (GFDL), Global Forecast System, Canadian Meteorological Centre, and Navy Operational Global Atmospheric Prediction System (NOGAPS) models. To understand the physical and dynamical processes in the evolution of storm structures, two MM5 forecasts with the model forecast tracks closest to

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Ulrike Wissmeier and Robert Goler

operational storm forecasting tools developed for midlatitude storms overforecast supercells within the tropics. Thus, there is a need to develop new forecasting tools for severe storms valid in the tropics. This work is seen as a first step in such a development. Diagrams such as Fig. 6c may be helpful because they indicate both for midlatitude and tropical environments when split cells are to be expected for a particular wind shear and for the modeled updraft strength w max . The combination of Figs

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Yizhe Peggy Bu, Robert G. Fovell, and Kristen L. Corbosiero

( Fig. 1 ), and model time steps of 45, 15, and 5 s, respectively. We also adopted some of the model physics used operationally, such as the simplified Arakawa–Schubert (SAS) cumulus parameterization (only in the 27- and 9-km domains after 24 h) 1 and the Global Forecast System (GFS) planetary boundary layer (PBL) scheme. Fig . 1. Domain configuration for the HWRF simulations. The outer (27 km) domain is approximately an 80° × 80° square, while the inner nests are about 11° × 10° and 6° × 5° for

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Robert G. Fovell, Kristen L. Corbosiero, and Hung-Chi Kuo

). When the clouds, their constituent particles, and/or their effects are unresolvable by a numerical model, parameterizations become necessary. Weather forecasting models at operational resolutions (horizontal grid spacing >10 km at this writing) are required to compensate for unresolvable convective activity with convective and cloud microphysics parameterizations (cf. Stensrud 2007 ). Convective schemes, such as Kain–Fritsch ( Kain and Fritsch 1993 ) and Betts–Miller ( Betts and Miller 1986

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Chris Snyder and Gregory J. Hakim

. Here we consider three surrogates for the errors of operational analyses: (i) analysis errors in experiments with simplified models and simulated observations, where the true state is known and analysis errors may be calculated directly; (ii) differences between operational analyses; and (iii) differences between observations and short-range background forecasts used in assimilation schemes. As will be discussed in what follows, each of these are imperfect substitutes for analysis errors. Data

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John A. Knox, Donald W. McCann, and Paul D. Williams

occurrence of CAT during a 144-day period using the 20-km output from the 13-km RUC2 operational numerical weather prediction model. Layer TKE dissipation rates calculated from the 1-h forecasts from the 1500 UTC model run (valid at 1600 UTC) for each day from 3 November 2005 to 26 March 2006 are validated with 5546 text pilot reports of turbulence from 1500 to 1700 UTC at or above FL200. PIREPs of turbulence in convection (as determined subjectively from satellite imagery) or in mountain waves (as

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