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Citations
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Cintra, R., Velho, H. D., & Cocke, S. (2016). Tracking the model: data assimilation by artificial neural network. In IEEE International Joint Conference on Neural Networks (IJCNN) (pp. 403–410).
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Cintra, R., de Campos Velho, H., Anochi, J., & Cocke, S. (2015). Data assimilation by artificial neural networks for the global FSU atmospheric model: Surface pressure. In Computational Intelligence (LA-CCI), 2015 Latin America Congress on.
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LaRow, T. E., Stefanova, L., Shin, D. - W., & Cocke, S. (2010). Seasonal Atlantic tropical cyclone hindcasting/forecasting using two sea surface temperature datasets. Geophys. Res. Lett., 37(2).
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Lim, Y. - K., Shin, D. W., Cocke, S., LaRow, T. E., Schoof, J. T., O'Brien, J. J., et al. (2007). Dynamically and statistically downscaled seasonal simulations of maximum surface air temperature over the southeastern United States. J. Geophys. Res., 112(D24).
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Shin, D. W., Cocke, S., & LaRow, T. E. (2007). Diurnal cycle of precipitation in a climate model. J. Geophys. Res., 112(D13).
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Cocke, S., LaRow, T. E., & Shin, D. W. (2007). Seasonal rainfall predictions over the southeast United States using the Florida State University nested regional spectral model. J. Geophys. Res., 112(D4).
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Boisserie, M., Shin, D. W., LaRow, T. E., & Cocke, S. (2006). Evaluation of soil moisture in the Florida State University climate model-National Center for Atmospheric Research community land model (FSU-CLM) using two reanalyses (R2 and ERA40) and in situ observations. J. Geophys. Res., 111(D8).
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Shin, D. W., LaRow, T. E., & Cocke, S. (2003). Convective scheme and resolution impacts on seasonal precipitation forecasts. Geophys. Res. Lett., 30(20).
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Schoof, J. T., Shin, D. W., Cocke, S., LaRow, T. E., Lim, Y. - K., & O'Brien, J. J. (2009). Dynamically and statistically downscaled seasonal temperature and precipitation hindcast ensembles for the southeastern USA. Int. J. Climatol., 29(2), 243–257.
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Shin, D. W., Baigorria, G. A., Romero, C. C., Cocke, S., Oh, J. - H., & Kim, B. - M. (2017). Assessing crop yield simulations driven by the NARCCAP regional climate models in the southeast United States. J. Geophys. Res. Atmos., 122(5), 2549–2558.
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