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Nicholas J. Weber, Matthew A. Lazzara, Linda M. Keller, and John J. Cassano

wind. The top 12 EWE events chosen for the additional dynamical analysis are listed in Table 3 . Table 3. The start date, maximum speed, average speed, resultant direction (vector average), and duration of the top 12 McMurdo Station EWEs. Note that the May 2004 EWE data were obtained from the SPAWAR Arrival Heights AWS data. The winds are considerably stronger because Arrival Heights is at a higher, more exposed location inland above McMurdo Station. Forecast back trajectories are computed for

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Andrew M. Chiodi, Nicholas A. Bond, Narasimhan K. Larkin, and R. James Barbour

summertime rainfall events is needed. The regional geography is characterized by the largely north–south-running coastal Cascade Mountain range, east of which lie the lower elevations of eastern Oregon and Washington’s Columbia River basin. Moving farther east, these lower elevations rise to meet the foothills of the greater Rocky Mountains ( Fig. 1 ). The climatological summertime-average midtropospheric (500 hPa) circulation is westerly with a magnitude of about 10 m s −1 over this region (which is

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Brian Tang, Matthew Vaughan, Ross Lazear, Kristen Corbosiero, Lance Bosart, Thomas Wasula, Ian Lee, and Kevin Lipton

toward the west in the center of the figure. The Adirondack Mountains lie to the north of the Mohawk valley, and the Catskill Mountains lie to the south of the Mohawk valley. Fig . 1. Topography of the region of interest. Elevation (m) is shaded. The A is the location of Amsterdam, and the D is the location of Duanesburg. The interaction of terrain with convection is important for assessing local areas that have a heightened risk for impacts when the synoptic-scale conditions favor severe weather

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Omar V. Müller, Miguel A. Lovino, and Ernesto H. Berbery

, where it rains just a few days per year. Fig . 3. (a) Geographical distribution of the observed precipitation frequency, followed by the forecast precipitation skill scores averaged over the seven lead times: (b) ACC, (c) POD, (d) FAR, (e) BIAS, and (f) HSS. Figures 3b–f summarize the skill scores averaged over the 7-day lead time. In other words, , where is the skill score for lead time i and is the average of those seven scores. The accuracy ( Fig. 3b ) is almost homogeneous over the LPB

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Johannes M. L. Dahl and Jannick Fischer

western periphery of the EML plume, were added manually. Interestingly, the Q-vector convergence is displaced slightly to the northeast relative to the location of the convergence line for several output times. This offset is quite well pronounced at 0900 UTC 2 August, shown in Fig. 7a . A vertical cross section from southwest to northeast through the thermal ridge is presented in Fig. 7b , revealing a quadrupole-like horizontal velocity divergence pattern below the 650-hPa level consistent with a

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Kimberly M. Wood, Oscar G. Rodríguez-Herrera, Elizabeth A. Ritchie, Miguel F. Piñeros, Ivan Arias Hernández, and J. Scott Tyo

also exhibits a wider longitudinal extent of activity, albeit with fewer clusters than in 2012. Fig . 7. Density plots of automated tracked clusters that developed in the western North Pacific during (a) 2009, (b) 2010, (c) 2011, and (d) 2012. Black dots indicate the location at which a developing cloud cluster reached 30 kt in the JTWC best-track archive. Fig . 8. As in Fig. 7 , but for the eastern North Pacific. Black dots indicate the location at which a developing cloud cluster reached 30 kt

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

-day lead time from 27 to 16 kt. The intensity bias ( Fig. 1c ) also shows that the H213 intensity biases (red columns) between the 24- and 96-h lead times were reduced relative to the H212 biases (blue columns), except at the 5-day lead time for which H213 possesses a positive intensity bias. Such a positive bias at the 5-day lead time could be related to several factors such as landfalling storms where a slight difference in the landfall time or location could have a significant influence on the

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Julian T. Heming

central pressure biases (i.e., low centers too deep). This can happen as a result of assimilating central pressure observations that have observation minus background values larger (in absolute terms) than the difference between the observed and background central pressure because of a positional error in the location of the TC in the background field. Fig . 13. Control (solid red lines) and trial (dashed green lines) central pressure forecasts plotted against the best-track observed data (solid blue

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Si Gao, Wei Zhang, Jia Liu, I.-I. Lin, Long S. Chiu, and Kai Cao

improve the classification accuracy of TC intensity change and provide valuable references for the prediction, analysis, and mitigation of TC-related hazards in coastal regions. The data and methodology are described in section 2 . Section 3 presents an improved decision tree with OC_PI for TC intensity change classification, followed by a summary and discussion given in section 4 . 2. Data and methodology a. Data The 6-hourly location and 10-min maximum sustained wind speed (MWS) of WNP TCs are

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D. Hudson, A. G. Marshall, O. Alves, G. Young, D. Jones, and A. Watkins

shown in Figs. 3c–e are for the fortnight from 26 August to 8 September (initialized at the start of the week prior, i.e., weeks 2 and 3 of the forecast). POAMA provided good warning (except perhaps over the far north) a week in advance of the warmer than normal temperatures experienced in this fortnight. Although the ensemble mean anomaly underestimated the observed anomaly, the location of the above normal temperatures is reasonable ( r = 0.84; Table 1 ). The probabilistic forecasts show

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