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Stefan F. Cecelski, Da-Lin Zhang, and Takemasa Miyoshi

Research and Forecasting Model (WRF) ( Skamarock et al. 2005 ) and the ensemble simulations using the coupled WRF and local ensemble transform Kalman filter (LETKF) system ( Hunt et al. 2007 ; Miyoshi and Kunii 2012 , hereafter MK12 ); and (ii) identify the fundamental synoptic-scale and mesoscale differences between developing and nondeveloping ensemble members, or developers and nondevelopers for short, with an emphasis on upper-level warming ( Zhang and Zhu 2012 ; Cecelski and Zhang 2013 ), the

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Yamei Xu, Tim Li, and Melinda Peng

) demonstrated that the ISO can influence TC formation through both a dynamic effect (primarily via low-level convergence and cyclonic vorticity) and a thermodynamic (moisture) effect. Besides the strong intraseasonal and synoptic variability, the WNP is also the active region of high-frequency (at a period of shorter than 3 days) eddies (HFEs). These eddies have a typical spatial scale of 200 km or less, often including mesoscale convective systems and small-scale convective vortices. Small-scale convective

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Reuben Demirdjian, Richard Rotunno, Bruce D. Cornuelle, Carolyn A. Reynolds, and James D. Doyle

lead time, finding that fewer than 75% of the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble members predicted AR landfall within 250 km of the actual location. This error provides motivation to work toward improving not only the magnitude of the water-vapor content in the AR, but also its position. Improvements in AR prediction can be subdivided into two broad categories, improving (i) numerical-prediction systems, and (ii) the data used to initialize the prediction systems

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Ralph F. Milliff and Jan Morzel

observations from spaceborne scatterometers. However, true mesoscale resolution [ O (10 0 –10 2 km)] for the globe has yet to be achieved. This paper examines in some detail the sampling effects of the National Aeronautics and Space Administration (NASA) Scatterometer (NSCAT) system on an estimate of the average wind stress curl field for the global ocean. NSCAT represents a prototype for spaceborne, broad-swath, active scatterometer systems, which are being coordinated internationally to provide for more

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Simon Alexander and Damian Murphy

) to investigate the tropopause structure at Davis (69°S, 78°E); here, we use the lower-tropospheric winds obtained simultaneously. We will quantify the seasonal cycle of gravity wave activity in the lower troposphere, calculated from wind observations made with the Davis VHF radar. We will use case-study output from the Antarctic Mesoscale Prediction System (AMPS) forecast ( Powers et al. 2003 ) along with the radar results to investigate the interaction of synoptic winds from an offshore low

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Jonathan D. Hall, Ming Xue, Lingkun Ran, and Lance M. Leslie

with synoptic-scale features in its environment, such as baroclinic midlatitude or monsoon troughs, can produce rainfall asymmetries that affect accumulations (e.g., Atallah and Bosart 2003 ). In summary, accurate QPF for a landfalling TC requires accurate track forecasts, and realistic treatment of mesoscale processes in the eyewall and inner core of the cyclone, accurate depictions of topographic forcing, interactions of the TC with its environment, and nonlinear interactions between these

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Chung-Chieh Wang, Hung-Chi Kuo, Yu-Han Chen, Hsiao-Ling Huang, Chao-Hsuan Chung, and Kazuhisa Tsuboki

along the ridge of the southern CMR at 22.3°–22.8°N. Other mesoscale models, including the Weather Research and Forecasting Model (WRF), also have this tendency for the Morakot case (e.g., Nguyen and Chen 2011 , their Figs. 12 and 18; Fang et al. 2011 , their Figs. 1 and 4). It is noted that few rain gauges exist in this remote region of the southern CMR ( Fig. 12a ), so the model tendency to overforecast rainfall here remains uncertain and requires further study. Fig . 12. (a) Terrain heights (m

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Masayuki Kawashima

~35 km behind the first ( Fig. 1b ). The process was repeated with the formation of a third WCFR ~30 km behind the second ( Fig. 1c ). These WCFRs moved at a speed a few meters per second faster than the SCF. However, the WCFRs did not move ahead of the SCF but instead dissipated over the SCF. 3. Mesoscale model and experimental design a. Numerical model Version 3.2 of the Advanced Research version of the Weather Research and Forecasting Model (ARW) ( Skamarock et al. 2008 ) was employed to

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Michael D. Toy and Richard H. Johnson

: Implementation and initial results . Mon. Wea. Rev. , 132 , 897 – 914 , doi: 10.1175/1520-0493(2004)132<0897:ATVDAS>2.0.CO;2 . Barker , D. , and Coauthors , 2012 : The Weather Research and Forecasting model’s Community Variational/Ensemble Data Assimilation System: WRFDA . Bull. Amer. Meteor. Soc. , 93 , 831 – 843 , doi: 10.1175/BAMS-D-11-00167.1 . Bourras , D. , G. Reverdin , H. Giordani , and G. Caniaux , 2004 : Response of the atmospheric boundary layer to a mesoscale oceanic eddy in

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Roland B. Stull and Takehiko Hasegawa

: Himeji LNG Terminal, Osaka Gas Company,Mega-Chisaki, Shimhama, Himeji-City, Hyogo, Japan T672.fall within the range of atmospheric eddy sizes. Thiscould be large mechanical eddies in a pollutantdispersion model, thermals in a boundary layer model,or perhaps meso-scale circulations in a synopticweather forecast model. After a rev/ew of turbulent adjustment in Section2, it is compared to transilient theory in Sections 3,5 and 7. A multiple-pass turbulence adjustmentscheme is shown in Section 4 to

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