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Ricardo Martins Campos, Vladimir Krasnopolsky, Jose-Henrique G. M. Alves, and Stephen G. Penny

spatial approach for wave simulations in the Gulf of Mexico, a region with intense maritime activity, offshore industry, and coastal vulnerabilities. The prognostic variables selected for analysis are wind speed (U10), significant wave height (Hs), and peak period (Tp). The use of artificial neural networks (ANNs) for environmental analyses and forecasts has rapidly increased over recent years. Sánchez et al. (2018) presented a mathematical model that uses ANNs for the assessment of wave energy

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Hanoi Medina, Di Tian, Fabio R. Marin, and Giovanni B. Chirico

forecasting. It is therefore necessary to conduct comprehensive assessments of the NWP’s ability to forecast heavy and highly variable rainfall regimes in tropical and near-tropical regions dominated by large mesoscale convective systems ( Mohr and Zipser 1996 ). The National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System (GEFS) and the European Centre for Medium-Range Weather Forecasts (ECMWF) are two leading NWPs for medium-range weather forecasting at the global scale. In

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Anthony Wimmers, Christopher Velden, and Joshua H. Cossuth

imagery for TC applications have been well documented in earlier studies (e.g., Velden et al. 1989 ; Cecil and Zipser 1999 ; Hawkins et al. 2001 ; Kieper and Jiang 2012 ; Jiang 2012 ; Edson 2014 ). The majority of these were based on qualitative image assessment or empirical analysis. More analytical approaches to examining microwave imagery have revealed ways to nowcast/forecast intensity variations from eyewall replacement cycles ( Sitkowski et al. 2011 ) and rapid intensification ( Rozoff et

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