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T. Ghosh and T. N. Krishnamurti

. (2007) have studied ocean sonic-layer depth estimation by applying ANN techniques. Surface parameters were taken as input in their study. Forecasts of ceiling and visibility using ANN from surface observations and model output were studied by Marzban et al. (2007) . Sharma and Ali (2013) applied ANN to achieve high-resolution tropospheric temperature profiles using geostationary satellite observations. Sharma et al. (2013) have shown that the use of ANN for the prediction of cyclone intensity

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

during the entire simulation. In this study, we employ a time-varying point-downscaling technique (described in section 2 ) to smoothly add the environmental shear, and then keep this shear nearly constant through the simulations. In this framework we aim to obtain robust insights into the response (and resistance) of the TC to uniformly strong environmental shear via the adjustment of the TC secondary circulation. A key motivation of this study arises from our previous studies on the role of TC

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

) are constructed separately, the effects of the IC perturbations from each of these regions can be isolated and their influence on the track and intensity forecast spread examined. The process of removing the IC differences in a specific region is referred to throughout this manuscript as relaxing. A strength of this technique is that it illustrates the effects of IC differences only within a specific region and can help to more clearly understand how IC differences within a specific region evolve

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

utilize all of the forty 6-h AMV datasets to optimize the analysis technique that spreads the AMV information, and more fully demonstrates the impacts of the AMVs on the regional and global model forecasts. An important goal of these future studies will be to demonstrate that a global model forecast after 6 h can then provide the initial and lateral boundary conditions for the next dynamic initialization, and this cycling can be an end-to-end NWP application that fully utilizes the information content

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

that among the Hendricks et al. (2010) environmental factors that best compared with the Joaquin intensity changes was the VWS from both the SHIPS and the CIMSS technique ( Gallina and Velden 2002 ; Velden and Sears 2014 ). Whereas the SHIPS simply takes the difference between the Global Forecast System (GFS) 200 and 850 hPa horizontal wind analyses, the CIMSS approach utilizes a local three-dimensional analysis of high-density, satellite-derived atmospheric motion vectors (AMVs) to calculate

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