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Eric A. Hendricks, Russell L. Elsberry, Christopher S. Velden, Adam C. Jorgensen, Mary S. Jordan, and Robert L. Creasey

Scheme (SHIPS; DeMaria et al. 2005 ) intensity forecasts from 0000 UTC 4 October to 0000 UTC 5 October ( Fig. 1 ) underestimate the rapid weakening during the early forecast intervals. While these SHIPS intensity forecasts then somewhat coincidently had smaller errors during the subsequent constant intensity period, these SHIPS forecasts then indicate rapid weakening to 20 kt when the verifying intensities continued to be greater than 60 kt due to the 30-h period of constant intensity of Joaquin

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William A. Komaromi and James D. Doyle

between the northward- versus southward-directed outflow between the trough and the no-trough simulations but only at a single forecast time. Radius–time Hovmöller diagrams demonstrate that 200–100-hPa υ r is consistently stronger in the southern semicircle ( Fig. 8c ) than in the northern semicircle ( Fig. 8a ) throughout the forecast. The opposite relationship is observed in the trough simulation ( Figs. 8b,d ). Note the strong burst of υ r in the northern semicircle from 50- to 200-km radius

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David R. Ryglicki, James D. Doyle, Yi Jin, Daniel Hodyss, and Joshua H. Cossuth

model, a “verification” in a strict sense—such as a direct comparison of a model forecast with observational data (e.g., Smith et al. 2017 )—cannot be readily performed. With that in mind, this section describes basic features of the simulations including the intensity, the general similarities between synthetic satellite imagery of the CM1 and satellite observations, and perhaps most importantly, the tilt of the vortex. Understanding the behavior of the tilt of the vortex is critical to the entire

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Daniel J. Cecil and Sayak K. Biswas

1. Introduction Mapping the surface wind speed in a hurricane is a great challenge that affects the ability to issue accurate forecasts and warnings for the maximum wind speed, wind field structure, and related impacts ( Powell et al. 2009 ; Uhlhorn and Nolan 2012 ; Nolan et al. 2014 ). Buoys can provide useful measurements, but only for the precise parts of a hurricane that happen to track across the buoy. As with any surface stations, buoys are subject to failures in extreme conditions (i

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T. Connor Nelson, Lee Harrison, and Kristen L. Corbosiero

). The dropsonde horizontal winds were put into a storm-relative framework by subtracting the u and υ components of TC motion from the horizontal wind components. The TC motion was calculated by taking 6-h centered differences about the closest (in time) Automated Tropical Cyclone Forecast (AFTC) best track center from NHC. A single ZWC was found by constructing orthogonal lines to the storm-motion-relative horizontal wind vectors at all altitudes. Weighted means of the intersecting independent

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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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Robert L. Creasey and Russell L. Elsberry

vortex tilt and the radial and tangential wind structure. It will be productive to compare the vortex tilt (if any) in the initial conditions and forecasts of numerical models of the TCI-15 tropical cyclones. It may be challenging to incorporate these high temporal and spatial resolution HDSS observations in the numerical models. Perhaps our technique of creating layer-average wind direction and speed from overlapping 1-km layers may be useful for initializing those computer models that also

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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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William A. Komaromi and James D. Doyle

13 km out to a radius of 100 km from high-resolution Weather Research and Forecasting (WRF) Model simulations, and demonstrate a reduction of I in the TC core and moat region along with an increase in I outside of the primary eyewall during secondary eyewall formation. However, they do not include the outflow region in their analyses. As is the case with outflow, the TC warm core has traditionally been infrequently documented by in situ observations because of its combination of high altitude

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