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Yu-Kun Qian, Chang-Xia Liang, Shiqiu Peng, Shumin Chen, and Sihua Wang

for meteorologists, requiring more effort in the future. It has been known that there are multiscale factors (from the convective scale to the synoptic scale) controlling TC intensity (e.g., Wang and Wu 2004 ). One of these factors is the upper-tropospheric (typically 200 hPa) environmental flow. The emphasis on its role may be traced back to Riehl (1950) , who noted that in a hurricane’s development, some forcings were needed to ensure that upper-level outflow did not sink in the immediate

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Huming Luo and Zhenshan Lin

precipitation for five benchmark meteorological stations around Beijing (Laoting, Chengde, Shijiazhuang, Tianjin, and Huailai; see Fig. 1 ). Considering that the monthly average atmospheric pressure, temperature, and precipitation fluctuate periodically with the seasonal variation every year, we add the sine item to Eq. (8) , with the period of the sine item being 12 (12 months per year). The sine item is the outside periodic driving force to the seasonal change of the Beijing local climate. Fig . 1

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Shawn M. Milrad, Eyad H. Atallah, John R. Gyakum, and Giselle Dookhie

), while cool-season extreme events were dominated by strong synoptic-scale forcing. In Canada, research into heavy precipitation events has been largely limited to case studies such as the 1996 Montreal flood ( Durnford 2001 ), consecutive extreme events at St. John’s ( Milrad et al. 2010a ), and the drought-breaking Canadian prairie rainstorm of 2002 ( Szeto et al. 2011 ). In addition, the Canadian Atlantic Storms Program (CASP) I and II field projects examined the formation of heavy mesoscale

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Shou-Jun Chen, Le-sheng Bai, and Stanley L. Barnes

, based on Hosidns' Q.vector analysis and developedby Barnes, was applied to a cold mesoscale vortex with severe convection over not:theast China in summer.The limited area model used at the Bcijing Weather Center did not predict this event because the baroclinieforcing was rather weak, but the Q-vector analysis clearly indicated the forcing 12 h before. In addition toBarnes' diagnostics, we estimate divergence tendency in low levels through computation of the rotational component of the Q

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Matías G. Dinápoli, Claudia G. Simionato, and Diego Moreira

decisions about the processes and interactions to be included, and a model adjustment and validation ( Kalnay 2002 ). Previous works have shown that the proper design of a hindcast/forecast system demands knowledge about the sources of uncertainties, the order of magnitude of the forcing effects (e.g., Bastidas et al. 2016 ), the relative importance of the parameters/forcings (for instance, Mayo et al. 2014 ; Ferreira et al. 2014 ; Höllt et al. 2015 ), the real need of their inclusion ( Gayathri et

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Joan M. Von Ahn, Joseph M. Sienkiewicz, and Paul S. Chang

described by Bowditch (2005) : gale, 34–47 kt (17.2–24.4 m s −1 ); storm, 48–63 kt (24.5–32.6 m s −1 ); and hurricane force, 64 kt or greater (32.7 m s −1 or greater). In Bowditch (2005) , winds speeds are given in whole knots whereas meters per second are continuous and given to the nearest tenth. Since wind speeds are given in knots for all OPC graphical and text products, that convention will be maintained throughout this paper (conversion to m s −1 will follow in parentheses and may not exactly

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Greg L. Dial, Jonathan P. Racy, and Richard L. Thompson

numerically simulated supercells. They demonstrated that shear oriented normal to a line of forcing was associated with upscale linear growth through the interaction of splitting storm pairs at regular intervals along the line of forcing. On the other hand, shear oriented at an oblique angle to the boundary resulted in discrete cyclonic supercells, presumably given the propensity for the precipitation cascade to spread downstream with little interaction between adjacent storms or storm splits. Furthermore

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Charles R. Sampson and John A. Knaff

= 0.514 m s −1 )], damaging (50 kt), and hurricane (64 kt) force winds in compass quadrants surrounding the TC. These are collectively referred to as wind radii. NHC forecasts hurricane force wind radii through 36 h, damaging and gale force wind radii through 72 h, and intensity (1-min mean maximum wind speed near the center) and track through 120 h. These forecasts are used for the official NHC watch and warning decision process and are employed as inputs to other decision aids designed to

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W. Erick Rogers, Paul A. Wittmann, David W. C. Wang, R. Michael Clancy, and Y. Larry Hsu

the periods of January 2001 and January–February 2002) was very likely caused by the inaccuracy of the forcing fields from the operational global atmospheric model NOGAPS, in particular a negative bias in predictions of high wind speed ( U 10 > 15 m s −1 ) events by that model. Bias associated with the wave model itself (internal error) was believed to be only secondary. b. The operational meteorological product For wind forcing, both of the Navy’s global wave models use wind vectors from the

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Jeffry S. Evans and Charles A. Doswell III

, the cases were classified into those associated with 1) weak synoptic-scale forcing and 2) strong synoptic-scale forcing. The “weak” and “strong” forcing categories correspond roughly to Johns's (1993) “warm season” and “dynamic” synoptic patterns associated with bow echo development. This was accomplished by obtaining the 1200 UTC 500-mb and surface charts prior to development, and assessing subjectively the strength of the forcing. Events that occurred ahead of an advancing high

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