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Kyle A. Hilburn, Imme Ebert-Uphoff, and Steven D. Miller

1. Introduction Geostationary Operational Environmental Satellite (GOES) imagery is a key element of U.S. operational weather forecasting, supporting the need for high-resolution, rapidly refreshing imagery for situational awareness ( Line et al. 2016 ). While used extensively by human forecasters, its usage in data assimilation (DA) for numerical weather prediction (NWP) models is limited. Instead DA makes greater usage of microwave and infrared sounder data on low-Earth-orbiting satellites

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

1. Introduction Precipitation is an important source of water resources and a major driving factor in the functioning of agriculture, forest, and freshwater ecosystems. Accurate precipitation forecasting is one of the most sensible aspects of weather prediction to the society. It strongly affects daily decisions in different sectors, such as public health, water resources, energy production, agriculture, and environmental protection. Numerical weather prediction (NWP) models are the state

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Eric D. Loken, Adam J. Clark, Amy McGovern, Montgomery Flora, and Kent Knopfmeier

1. Introduction Over the past 20 years, increases in computing resources have reshaped the state of numerical weather prediction (NWP) in several key ways: by enabling skillful high-resolution ensemble forecasts (e.g., Xue et al. 2007 ; Jirak et al. 2012 , 2016 , 2018 ; Roberts et al. 2019 ; Clark et al. 2018 ; Schwartz et al. 2015 , 2019 ); by increasing the capacity to run and store models for research and operations (e.g., Hamill and Whitaker 2006 ; Kain et al. 2010 ; Hamill et al

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Imme Ebert-Uphoff and Kyle Hilburn

. In contrast the image-to-image translation models ( Figs. 1b,c ) generate as output an image, typically of the same dimension (but not necessarily the same number of channels) as the input image. Image-to-image translation models can be used to enhance remote sensing images ( Tsagkatakis et al. 2019 ), to detect changes in satellite imagery ( Peng et al. 2019 ), for precipitation forecasting ( Sønderby et al. 2020 ), for weather forecasting ( Weyn et al. 2020 ), to detect tropical and

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

overfitting can be reduced by properly filtering the time series. Fig . 5. Illustration of Eqs. (1) , (10) , and (11) . Fig . 6. Time series of the residue of Hs (blue) and the filtered signal using a moving average of 120 h (black). Moving from a single spot analysis to a spatial approach in the Gulf of Mexico required a small modification in the ANN configuration. As ANN models converge to optimum weights and biases that cannot be directly interpolated or extrapolated in space, the strategy of

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