COAPS Virtual Library (Publications)

Bourassa, M. A., Legler, D. M., & O'Brien, J. J. (1997). The use of significant wave height to improve the accuracy of wind derived stress and wave characteristics. 12th Symposium on Boundary Layers and Turbulence, , 291–292. https://www.coaps.fsu.edu/bibliography/show.php?record=544
Bourassa, M. A., Legler, D. M., O'Brien, J. J., Stricherz, J. N., & Whalley, J. (1998). High temporal and spatial resolution animations of winds observed with the NSCAT scatterometer. In 14th International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology at 78th AMS Annual Meeting (pp. 556–559). https://www.coaps.fsu.edu/bibliography/show.php?record=538
Bourassa, M. A., Smith, S. R., & O'Brien, J. J. (2002). Assimilation of scatterometer and in situ winds for regularly gridded products. In 6th Symposium on Integrated Observing Systems (pp. 161–165). https://www.coaps.fsu.edu/bibliography/show.php?record=500
Bove, M. C., O'Brien, J. J., Eisner, J. B., Landsea, C. W., & Niu, X. (1998). Effect of El Niño on U.S. Landfalling Hurricanes, Revisited. Bull. Amer. Meteor. Soc., 79(11), 2477–2482. https://www.coaps.fsu.edu/bibliography/show.php?record=535
Bove, M. C., Zierden, D. F., & O'Brien, J. J. (1998). Are Gulf Landfalling Hurricanes Getting Stronger? Bull. Amer. Meteor. Soc., 79(7), 1327–1328. https://www.coaps.fsu.edu/bibliography/show.php?record=537
Buchanan, S., Misra, V., & Bhardwaj, A. (2018). https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.5450. International Journal of Climatology, 38(6), 2651–2661. Abstract: The integrated kinetic energy (IKE) of a tropical cyclone (TC), a volume integration of the surface winds around the centre of the TC, is computed from a comprehensive surface wind (National Aeronautics and Space Administration’s (NASA) cross‐calibrated multi‐platform [CCMP]) analysis available over the global oceans to verify against IKE from wind radii estimates of extended best‐track data maintained by NOAA for the North Atlantic TCs. It is shown that CCMP surface wind analysis severely underestimates IKE largely from not resolving hurricane force winds for majority of the Atlantic TCs, under sampling short‐lived and small‐sized TCs. The seasonal cycle of the North Atlantic TC IKE also verifies poorly in the CCMP analysis. In this article we introduce proxy IKE (PIKE) based on the kinetic energy of the winds at the radius of the last closed isobar (ROCI), which shows promise for a wide range of TC sizes including the smaller‐sized TCs unresolved in the CCMP data set. https://www.coaps.fsu.edu/bibliography/show.php?record=551
Caron, J. M., & O'Brien, J. J. (1998). The Generation of Synthetic Sea Surface Temperature Data for the Equatorial Pacific Ocean. Mon. Wea. Rev., 126(11), 2809–2821. https://www.coaps.fsu.edu/bibliography/show.php?record=536
Cocke, S., & LaRow, T. E. (2000). Seasonal Predictions Using a Regional Spectral Model Embedded within a Coupled Ocean-Atmosphere Model. Mon. Wea. Rev., 128(3), 689–708. https://www.coaps.fsu.edu/bibliography/show.php?record=520
Coles, V. J., Stukel, M. R., Brooks, M. T., Burd, A., Crump, B. C., Moran, M. A., et al. (2017). Ocean biogeochemistry modeled with emergent trait-based genomics. Science, 358(6367), 1149–1154. https://www.coaps.fsu.edu/bibliography/show.php?record=552
Devanas, A., & Stefanova, L. (2018). Statistical Prediction Of Waterspout Probability For The Florida Keys. Wea. Forecasting, 33, 389–410. Abstract: A statistical model of waterspout probability was developed for wet-season (June–September) days over the Florida Keys. An analysis was performed on over 200 separate variables derived from Key West 1200 UTC daily wet-season soundings during the period 2006–14. These variables were separated into two subsets: days on which a waterspout was reported anywhere in the Florida Keys coastal waters and days on which no waterspouts were reported. Days on which waterspouts were reported were determined from the National Weather Service (NWS) Key West local storm reports. The sounding at Key West was used for this analysis since it was assumed to be representative of the atmospheric environment over the area evaluated in this study. The probability of a waterspout report day was modeled using multiple logistic regression with selected predictors obtained from the sounding variables. The final model containing eight separate variables was validated using repeated fivefold cross validation, and its performance was compared to that of an existing waterspout index used as a benchmark. The performance of the model was further validated in forecast mode using an independent verification wet-season dataset from 2015–16 that was not used to define or train the model. The eight-predictor model was found to produce a probability forecast with robust skill relative to climatology and superior to the benchmark waterspout index in both the cross validation and in the independent verification. Keywords: Regression analysis; Forecast verification/skill; Forecasting techniques; Probability forecasts/models/distribution; Statistical forecasting https://www.coaps.fsu.edu/bibliography/show.php?record=553

Bourassa, M. A., Legler, D. M., & O'Brien, J. J. (1997). The use of significant wave height to improve the accuracy of wind derived stress and wave characteristics. 12th Symposium on Boundary Layers and Turbulence, , 291–292.

Bourassa, M. A., Legler, D. M., O'Brien, J. J., Stricherz, J. N., & Whalley, J. (1998). High temporal and spatial resolution animations of winds observed with the NSCAT scatterometer. In 14th International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology at 78th AMS Annual Meeting (pp. 556–559).

Bourassa, M. A., Smith, S. R., & O'Brien, J. J. (2002). Assimilation of scatterometer and in situ winds for regularly gridded products. In 6th Symposium on Integrated Observing Systems (pp. 161–165).

Bove, M. C., O'Brien, J. J., Eisner, J. B., Landsea, C. W., & Niu, X. (1998). Effect of El Niño on U.S. Landfalling Hurricanes, Revisited. Bull. Amer. Meteor. Soc., 79(11), 2477–2482.

Bove, M. C., Zierden, D. F., & O'Brien, J. J. (1998). Are Gulf Landfalling Hurricanes Getting Stronger? Bull. Amer. Meteor. Soc., 79(7), 1327–1328.

Buchanan, S., Misra, V., & Bhardwaj, A. (2018). https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.5450. International Journal of Climatology, 38(6), 2651–2661.

Caron, J. M., & O'Brien, J. J. (1998). The Generation of Synthetic Sea Surface Temperature Data for the Equatorial Pacific Ocean. Mon. Wea. Rev., 126(11), 2809–2821.

Cocke, S., & LaRow, T. E. (2000). Seasonal Predictions Using a Regional Spectral Model Embedded within a Coupled Ocean-Atmosphere Model. Mon. Wea. Rev., 128(3), 689–708.

Coles, V. J., Stukel, M. R., Brooks, M. T., Burd, A., Crump, B. C., Moran, M. A., et al. (2017). Ocean biogeochemistry modeled with emergent trait-based genomics. Science, 358(6367), 1149–1154.

Devanas, A., & Stefanova, L. (2018). Statistical Prediction Of Waterspout Probability For The Florida Keys. Wea. Forecasting, 33, 389–410.

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