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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., Cocke, S., Shin, D. W., Schoof, J. T., LaRow, T. E., & O'Brien, J. J. (2010). Downscaling large-scale NCEP CFS to resolve fine-scale seasonal precipitation and extremes for the crop growing seasons over the southeastern United States. Clim Dyn, 35(2-3), 449–471.
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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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Nunes, A. M. B., & Cocke, S. (2004). Implementing a physical initialization procedure in a regional spectral model: impact on the short-range rainfall forecasting over South America. Tellus A, 56(2), 125–140.
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Oh, J. - H., Shin, D. W., Cocke, S. D., & Baigorria, G. A. (2014). ENSO Teleconnection Pattern Changes over the Southeastern United States under a Climate Change Scenario in CMIP5 Models. Advances in Meteorology, , 1–16.
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Powell, M. D., & Cocke, S. (2012). Hurricane wind fields needed to assess risk to offshore wind farms. Proc Natl Acad Sci U S A, 109(33), E2192; author reply E2193–4.
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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., & Cocke, S. (2013). Alternative ways to evaluate a seasonal dynamical downscaling system. J. Geophys. Res. Atmos., 118(24), 13,443–13,448.
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Shin, D. W., Bellow, J. G., Cocke, S., LaRow, T. E., & O'Brien, J. J. (2006). Seasonal dynamical downscaling for crop yield estimation. Research Activities in Atmospheric and Ocean Modeling, CAS/JSC Working Group on Numerical Experimentation.
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Shin, D. W., Cocke, S., & LaRow, T. E. (2002). Superensemble precipitation forecasts using TRMM and DMSP satellite microwave imager products.
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