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William A. Komaromi, Sharanya J. Majumdar, and Eric D. Rappin

modified field. The primary goal of the study is to diagnose the primary initial condition sensitivities when full-physics, nonlinear models are used. The methodology may be used retrospectively by the research and operational communities to offer suggestions on the weather features in which the initial analysis required improvement, via a combination of improved modeling, observational coverage, or data assimilation. The diagnostic technique may also be used to improve our understanding of the

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Munehiko Yamaguchi and Sharanya J. Majumdar

1. Introduction The skill of tropical cyclone (TC) track prediction has improved significantly over the last few decades, due in large part to improvement in numerical weather prediction (NWP) models, data assimilation schemes, and enhanced observations as obtained through satellites and aircraft. However, significant errors can still exist and are often subject to initial condition errors. For example, errors in 3-day predictions vary between less than 50 km and more than

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Sharanya J. Majumdar, Kathryn J. Sellwood, Daniel Hodyss, Zoltan Toth, and Yucheng Song

1. Introduction The global atmospheric observational network has traditionally comprised land-based rawinsonde balloons and satellite-borne sensors. Yet, as stated by Lorenz and Emanuel (1998) , “ … despite this wealth of data—more, in fact, than we know how to use to full advantage—large gaps remain in our picture of the global weather pattern, particularly over the less frequently visited areas of the oceans.” In an effort to fill these gaps, several field campaigns have taken place over the

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E. A. Irvine, S. L. Gray, J. Methven, and I. A. Renfrew

targeted observation coverage and number using a two-dimensional sampling pattern. Targeted observations were spaced according to the horizontal correlation length scales assumed by the European Centre for Medium-Range Weather Forecasts (ECMWF) four-dimensional variational data assimilation (4D-Var) scheme, and the number of observations and size of target region were varied. Taking targeted observations over a larger area was found to be more effective. The proximity of the targeted observations to

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Thomas M. Hamill, Jeffrey S. Whitaker, Michael Fiorino, and Stanley G. Benjamin

1. Introduction The accuracy of official National Hurricane Center tropical cyclone (TC) track forecasts has improved over the past several decades ( Rappaport et al. 2009 ). In part, this can be attributed to the general improvements in numerical weather prediction (NWP) models, such as increased resolution, improved methods of initialization, more realistic physical parameterizations, and the availability of a greater number of skillful models for generating consensus forecasts

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