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Robert G. Nystrom, Fuqing Zhang, Erin B. Munsell, Scott A. Braun, Jason A. Sippel, Yonghui Weng, and Kerry Emanuel

forecast errors from multiple operational NWP models and NHC official forecasts. The purpose of this study is to understand the reasons for the large track and intensity spread in the ensemble forecasts of Joaquin and identify potential regions of IC errors that contributed to the track bifurcation and large intensity spread. Section 2 will describe the methods used in this study, including the details of the PSU WRF EnKF system. Section 3 will examine the regions of IC errors contributing to the

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Russell L. Elsberry, Eric A. Hendricks, Christopher S. Velden, Michael M. Bell, Melinda Peng, Eleanor Casas, and Qingyun Zhao

dense level of coverage of AMVs over three Atlantic hurricanes and their near environments. With this special processing strategy, these AMV observations in effect serve as a proxy for the AMV datasets becoming routinely available from the Himawari-8 and GOES-16 satellites (except for the limited coverage of the rapid-scan domains). Velden et al. (2017) utilized the operational version of the Hurricane Weather and Research Forecast (HWRF) Model data assimilation to create “cold start” initial

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Jie Feng and Xuguang Wang

data assimilation for HWRF with continuous cycling and a dual-resolution configuration ( Lu et al. 2017a , b ), extended from the GSI EnVar hybrid DA system for the global prediction system (e.g., Wang et al. 2013 ; Wang and Lei 2014 ). The initial conditions in the outer domain with an 18-km grid are directly interpolated from the global analysis of the operational Global Forecast System (GFS) hybrid DA system at National Centers for Environmental Prediction (NCEP; Wang et al. 2013 ). As for

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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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James D. Doyle, Jonathan R. Moskaitis, Joel W. Feldmeier, Ronald J. Ferek, Mark Beaubien, Michael M. Bell, Daniel L. Cecil, Robert L. Creasey, Patrick Duran, Russell L. Elsberry, William A. Komaromi, John Molinari, David R. Ryglicki, Daniel P. Stern, Christopher S. Velden, Xuguang Wang, Todd Allen, Bradford S. Barrett, Peter G. Black, Jason P. Dunion, Kerry A. Emanuel, Patrick A. Harr, Lee Harrison, Eric A. Hendricks, Derrick Herndon, William Q. Jeffries, Sharanya J. Majumdar, James A. Moore, Zhaoxia Pu, Robert F. Rogers, Elizabeth R. Sanabia, Gregory J. Tripoli, and Da-Lin Zhang

-57 flight track (solid line) and dropsonde launch locations (diamonds) for the two TCI flights over Marty, overlaid on Geostationary Operational Environmental Satellite (GOES) infrared imagery centered on the time the aircraft was over the storm. Potential development of Marty off the Pacific coast of Mexico was noted in the 10-day European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble and deterministic forecasts as early as 16 September. It was not until much later, though, that

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

the Dvorak technique, have also been observed, and this work will focus on this “atypical” class of TCs. Six cases have been observed that all share similar characteristics in both IR and water vapor (WV) satellite observations, SHIPS-RII parameters, and upper-level synoptic situations, but were all poorly forecast by both official forecasters and operational models. They are 1997 EPAC Guillermo, 2008 EPAC Hernan, 2008 EPAC Norbert, 2012 EPAC Fabio, 2015 EPAC Hilda, and 2015 North Atlantic (NATL

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Peter Black, Lee Harrison, Mark Beaubien, Robert Bluth, Roy Woods, Andrew Penny, Robert W. Smith, and James D. Doyle

. J. Trop. Cyclone Res. Rev. , 1 , 75 – 88 , doi: 10.6057/2012TCRR01.09 . Black , P. G. , and Coauthors , 2007 : Air–sea exchange in hurricane winds: Synthesis of observations from the Coupled Boundary Layer Air–Sea Transfer experiment . Bull. Amer. Meteor. Soc. , 88 , 357 – 374 , doi: 10.1175/BAMS-88-3-357 . Burpee , R. W. , S. D. Aberson , J. L. Franklin , S. J. Lord , and R. E. Tuleya , 1996 : The impact of omega dropwindsondes on operational hurricane track forecast

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Daniel J. Cecil and Sayak K. Biswas

.1109/LGRS.2010.2043814 . 10.1109/LGRS.2010.2043814 Franklin , J. L. , M. L. Black , and K. Valde , 2003 : GPS dropwindsonde wind profiles in hurricanes and their operational implications . Wea. Forecasting , 18 , 32 – 44 , doi: 10.1175/1520-0434(2003)018<0032:GDWPIH>2.0.CO;2 . 10.1175/1520-0434(2003)018<0032:GDWPIH>2.0.CO;2 Goodberlet , M. A. , 2000 : Improved image reconstruction techniques for synthetic aperture radiometers . IEEE Trans. Geosci. Remote Sens. , 38 , 1362 – 1366 , doi

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

1. Introduction Accurate forecasts of tropical cyclone (TC) intensity changes remain one of the most difficult weather predictions, even for short lead times. This is in part due to multiscale interactions, which require operational forecast models to precisely capture the evolution of the atmosphere over a vast range of scales in the vicinity of a TC. DeMaria et al. (2014) demonstrated that although intensity forecast errors have not improved as much as track forecast errors over the past

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William A. Komaromi and James D. Doyle

Cyclones (COAMPS-TC; Doyle et al. 2012 , 2014 ). COAMPS-TC is a specialized version of COAMPS, the navy’s operational mesoscale prediction system. The model uses a terrain-following sigma-height coordinate and the nonhydrostatic compressible equations of motion ( Klemp and Wilhelmson 1978 ). A more thorough description of COAMPS is provided by Hodur (1997) and Chen et al. (2003) . In this study, all simulations are run at 5-km horizontal resolution. There are 40 sigma levels in the vertical, with

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