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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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T. Ghosh and T. N. Krishnamurti

1. Introduction Consensus forecasts for meteorological events were operationally used in the pioneering studies of Toth and Kalnay (1993 1997 ), Molteni et al. (1996) , Houtekamer et al. (1996) , and Goerss (2000) . Krishnamurti et al. (1999) introduced the notion of a multimodel superensemble (MMSE) to combine multimodel forecast datasets using a linear multiple regression approach that utilized the mean-square error reduction principle. Studies reported on the efficiency of this

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Shixuan Zhang, Zhaoxia Pu, and Christopher Velden

, 2005 ) derived from geostationary satellites, have supplied useful information for improving hurricane forecasting. Previous studies have demonstrated that assimilating these AMVs into NWP models can result in improved analyses and forecasts of TCs and their environment. Langland et al. (2009) and Berger et al. (2011) found that track forecasts in the Navy Operational Global Atmospheric Prediction System (NOGAPS) were improved, owing to the more accurate representation of the environmental flow

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Robert G. Nystrom and Fuqing Zhang

years ( Cangialosi 2018 ), Hurricane Patricia set records for maximum eastern North Pacific NHC official intensity forecast errors at 12, 24, 36, and 48 h lead times ( Kimberlain et al. 2016 ). Additionally, no operationally available dynamical or statistical guidance was able to correctly forecast the peak intensity or rate of intensification. In this study, we demonstrate methods for improved prediction of Hurricane Patricia using a cycling ensemble data assimilation system and also examine

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Nannan Qin and Da-Lin Zhang

operational forecasts of Hurricane Patricia.] Another two experiments deal with the use of different vertical resolutions: a coarser one and a finer one of 41 and 73 vertical levels, which are referred to as V41 and V73, respectively. Figures 9a and 9b show that despite their different resolutions, V41 and V73 share the same Ω vertical distribution as that in CTL, with higher resolutions in both the lower and upper levels, but relatively coarse resolutions in the midtroposphere. For fair comparisons

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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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Shixuan Zhang and Zhaoxia Pu

. (1) , and the other terms are the same as those in Eq. (1) . In the GSI hybrid 4DEnVar, the tangential linear model and adjoint model in the traditional 4DVar are avoided by using the model forecast and preconditioned ensemble perturbations in each observational bin. Detailed explanations of the GSI hybrid 4DEnVar algorithm can be found in Wang and Lei (2014) and Kleist and Ide (2015) . The GSI-4DEnVar system has been applied in the NCEP operational GFS system since 2015, but this scheme has

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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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