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Yi Dai, Sharanya J. Majumdar, and David S. Nolan

understanding the TC resistance to strong environmental shear. By introducing the TCSD, we hope that the outflow can be not only a useful diagnostic to infer the upper-level outflow, but also a nice tool that can be used scientifically and operationally for better understanding and forecasting of TC intensity and structure change. This paper is organized as follows: Section 2 describes the idealized modeling framework and definitions of shear. The main results of the idealized simulations are presented in

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David R. Ryglicki, Daniel Hodyss, and Gregory Rainwater

: Improvements in the probabilistic prediction of tropical cyclone rapid intensification with passive microwave observations . Wea. Forecasting , 30 , 1016 – 1038 , https://doi.org/10.1175/WAF-D-14-00109.1 . 10.1175/WAF-D-14-00109.1 Ryglicki , D. R. , and R. E. Hart , 2015 : An investigation of center-finding techniques for tropical cyclones in mesoscale models . J. Appl. Meteor. Climatol. , 54 , 825 – 846 , https://doi.org/10.1175/JAMC-D-14-0106.1 . 10.1175/JAMC-D-14-0106.1 Ryglicki , D. R

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Jonathan Martinez, Michael M. Bell, Robert F. Rogers, and James D. Doyle

few decades, intensity forecasts at long lead times (e.g., 48–120 h) have improved at a statistically significant rate. However, only marginal improvements have been made at shorter lead times (e.g., 24–48 h), suggesting that additional research is required to better understand the underlying mechanisms associated with TC intensification. In the case of eastern North Pacific Hurricane Patricia (2015), extreme rapid intensification was not well predicted by either global or mesoscale models

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William A. Komaromi and James D. Doyle

to systematically explore the effect of modifying the environmental inertial stability and the resulting effect on the strength, structure, and direction of the storm outflow. Last, predictability issues associated with TC intensity change and the relative positions of the TC and the trough will be investigated. 2. Methodology a. Numerical model configuration The numerical simulations in this study are performed using the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) for Tropical

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Patrick Duran and John Molinari

Transfer Model for GCMs (RRTMG) longwave and shortwave schemes ( Iacono et al. 2008 ). The initial environmental temperature and humidity field was horizontally homogeneous and determined by averaging all Climate Forecast System Reanalysis (CFSR) grid points within 100 km of Patricia’s center of circulation at 1800 UTC 21 October 2015. The balanced vortex described in Rotunno and Emanuel [1987 , their Eq. (37)] was used to initialize the wind field, setting all parameters equal to the values used

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Benjamin C. Trabing, Michael M. Bell, and Bonnie R. Brown

. , 44 , 542 – 561 , https://doi.org/10.1175/1520-0469(1987)044<0542:AAITFT>2.0.CO;2 . 10.1175/1520-0469(1987)044<0542:AAITFT>2.0.CO;2 Saha , S. , and Coauthors , 2010 : The NCEP Climate Forecast System Reanalysis . Bull. Amer. Meteor. Soc. , 91 , 1015 – 1057 , https://doi.org/10.1175/2010BAMS3001.1 . 10.1175/2010BAMS3001.1 Schmetz , J. , and M. Beniston , 1986 : Relative effects of solar and infrared radiative forcing in a mesoscale model . Bound.-Layer Meteor. , 34 , 137 – 155

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Yi Dai, Sharanya J. Majumdar, and David S. Nolan

vapor satellite imagery, are used to study Hurricanes Edouard (2014) and Bill (2009). The AMV images are collected from the Cooperative Institute for Meteorological Satellite Studies (CIMSS) at the University of Wisconsin–Madison. This study also makes use of European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim; Dee et al. 2011 ) data to show upper-level flow features. The horizontal grid spacing of the ERA-Interim data is about 0.7° × 0.7°, which is sufficient

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