Dukhovskoy, D., & Bourassa, M. (2011). Comparison of ocean surface wind products in the perspective of ocean modeling of the Nordic Seas. In OCEANS 2011.
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Duncan, J. B. (2013). Atmospheric Power-Law Behavior: A Look into Southeastern US Daily Temperature Extremes. Master's thesis, , .
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Elsner, J. B., Strazzo, S. E., Jagger, T. H., LaRow, T., & Zhao, M. (2013). Sensitivity of Limiting Hurricane Intensity to SST in the Atlantic from Observations and GCMs. J. Climate, 26(16), 5949–5957.
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Engelman, M. B. (2008). A Validation of the FSU/COAPS Climate Model. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: This study examines the predictability of the Florida State University/Center for Oceanic and Atmospheric Prediction Studies (FSU/COAPS) climate model, and is motivated by the model's potential use in crop modeling. The study also compares real-time ensemble runs (created using persisted SST anomalies) to hindcast ensemble runs (created using weekly updated SST) to asses the effect of SST anomalies on forecast error. Wintertime (DJF, 2 month lead time) surface temperature and precipitation forecasts over the southeastern United States (Georgia, Alabama, and Florida) are evaluated because of the documented links between tropical Pacific SST anomalies and climate in the southeastern United States during the winter season. The global spectral model (GSM) runs at a T63 resolution and then is dynamically downscaled to a 20 x 20 km grid over the southeastern United States using the FSU regional spectral model (RSM). Seasonal, monthly, and daily events from the October 2004 and 2005 model runs are assessed. Seasonal (DJF) plots of real-time forecasts indicate the model is capable of predicting wintertime maximum and minimum temperatures over the southeastern United States. The October 2004 and 2005 real-time model runs both produce temperature forecasts with anomaly errors below 3°C, correlations close to one, and standard deviations similar to observations. Real-time precipitation forecasts are inconsistent. Error in the percent of normal precipitation vary from greater than 100% in the 2004/2005 forecasts to less than 35% error in the 2005/2006 forecasts. Comparing hindcast runs to real-time runs reveals some skill is lost in precipitation forecasts when using a method of SST anomaly persistence if the SST anomalies in the equatorial Pacific change early in the forecast period, as they did for the October 2004 model runs. Further analysis involving monthly and daily model data as well as Brier scores (BS), relative operating characteristics (ROC), and equitable threat scores (ETS), are also examined to confirm these results.
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Enloe, J. (2002). ENSO impacts on peak wind gusts in the United States. Master's thesis, , .
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Enloe, J., O'Brien, J. J., & Smith, S. R. (2002). ENSO impacts on peak wind gusts in the United States. COAPS Technical Report Series. Tallahassee, FL: Center for Ocean-Atmospheric Prediction Studies, Florida State University.
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Enloe, J., O'Brien, J. J., & Smith, S. R. (2004). ENSO Impacts on Peak Wind Gusts in the United States. J. Climate, 17(8), 1728–1737.
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Enloe, J., Smith, S. R., & O'Brien, J. J. (2003). El Nino/Southern Oscillation impacts on peak wind gusts in the United States. In 14th Symposium on Global Change and Climate Variations, American Meteorological Society, Long Beach, CA, USA (cdrom).
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Fairall, C. W., Barnier, B., Berry, D.I, Bourassa, M.A., Bradley, E.F., Clayson, C.A., de Leeuw, G., Drennan, W.M., Gille, S.T., Gulev, S.K., Kent, E.C., McGillis, W.R., Quartly, G.D., Ryabinin, V., Smith, S.R., Weller, R.A., Yelland, M.J. and Zhang, H-M. (2010). Observations to Quantify Air-Sea Fluxes and Their Role in Climate Variability and Predictability. In D.(eds.) D.E. and Stammer Harrison J. Hall (Ed.), Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society, Vol. 2 (pp. 299–313). European Space Agency.
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Farmer, B. (2012). Evaluation of Bulk Heat Fluxes from Atmospheric Datasets. Master's thesis, Florida State University, Tallahassee, FL.
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