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Shixuan Zhang, Zhaoxia Pu, and Christopher Velden

1. Introduction In contrast to the significant improvements in tropical cyclone (TC) track forecasts, only limited progress has been made in TC intensity forecasting in the last two decades ( Rogers et al. 2006 , 2013 ; Rappaport et al. 2009 ; Gall et al. 2013 ). Part of the difficulty in forecasting the intensity of TCs originates from deficiencies in the representation of the initial vortices in numerical weather prediction (NWP) models due to the general lack of high

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Jie Feng and Xuguang Wang

1. Introduction Over the past few decades, great efforts have been made to improve the accuracy of tropical cyclone (TC) forecasts. The major endeavors include the development of high-resolution cloud-resolving numerical weather prediction (NWP) models, advanced data assimilation (DA) systems, and novel observing systems for TCs. So far, the accuracy of TC analysis and prediction has been steadily and significantly improved. For example, the yearly averaged track forecast at the 5-day lead time

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Jie Feng and Xuguang Wang

. (2013) investigated the impact of assimilating the G-IV dropsonde observations on the track forecast from the perspective of the interaction of the outflow with the large-scale environment. Wu et al. (2015) found that the interior and upper-level (100–350 hPa) AMVs played an important role in improving the forecasts of TC intensity and wind structures. The assimilation of the new AMV data was also found to positively influence the TC track and intensity predictions ( Lim et al. 2019 ). Compared

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Xu Lu and Xuguang Wang

speed (Vmax), and minimum sea level pressure (MSLP)] ( Thu and Krishnamurti 1992 ; Kurihara et al. 1995 , 1998 , Liu et al. 2000 , 2006 ; Pu and Braun 2001 ; Tallapragada et al. 2014 ). In the National Oceanic and Atmospheric Administration (NOAA) operational Hurricane Weather Research and Forecasting system (HWRF), vortex initialization (VI) contains two components: vortex relocation (VR) and vortex modification (VM), where VR corrects the storm location and VM modifies the storm intensity

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David R. Ryglicki, James D. Doyle, Daniel Hodyss, Joshua H. Cossuth, Yi Jin, Kevin C. Viner, and Jerome M. Schmidt

to an operational forecast. For demonstration, we choose a high-impact atypical RI TC that was not part of the original six from Part I but nevertheless underwent RI in moderate vertical wind shear: 2016 northern Atlantic (NATL) Matthew ( Stewart 2017 ). For this analysis, we use SHIPS and CIMSS shear analyses, GOES-13 WV observations, CIMSS AMVs, and 0.5° GFS analyses. We use the GFS analyses here in an attempt to simulate operational conditions more closely. The decomposition of the GFS

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Robert G. Nystrom and Fuqing Zhang

1. Introduction Hurricane Patricia (2015) was an extraordinary storm in the eastern North Pacific basin that underwent an unprecedented rapid intensification (RI) process in which it intensified from a tropical storm, with maximum wind speeds of 30 m s −1 , to a category 5 hurricane, with maximum wind speeds of 95 m s −1 , in less than 36 h. While tropical cyclone (TC) track forecasts have been improving substantially over recent decades, and intensity forecast have also improved some in recent

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

years to construct guidelines for forecasters by relating specific features with current intensity. It has since been refined several times to add objective methods for estimating TC strength ( Dvorak 1984 ; Zehr 1989 ; Guard et al. 1992 ; Velden et al. 1998 ; Olander et al. 2004 ; Olander and Velden 2007 ). A modern version of the Dvorak technique, the advanced Dvorak technique (ADT), has even been used as a reanalysis tool for historical TC studies ( Velden et al. 2017 ). In addition to the

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Quanjia Zhong, Jianping Li, Lifeng Zhang, Ruiqiang Ding, and Baosheng Li

1. Introduction The accuracy of tropical cyclone (TC) track and intensity forecasts is of particular importance for warning the public to protect life and property in the affected area. The accuracy of TC track forecasts has steadily improved in recent decades along with a global reduction in forecast error for operational hurricane forecast models ( Elsberry et al. 2007 ; DeMaria et al. 2014 ). However, although many operational and research centers have made efforts to improve TC intensity

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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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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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