Bourassa, M. A. (2004). An improved sea state dependency for surface stress derived from in situ and remotely sensed winds. Advances in Space Research, 33(7), 1136–1142.
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Bourassa, M. A., and P.J. Hughes. (2018). Surface Heat Fluxes and Wind Remote Sensing. In and J. Verron J. Tintoré A. Pascual E. P. Chassignet (Ed.), (pp. 245–270). Tallahassee, FL: GODAE OceanView.
Abstract: The exchange of heat and momentum through the air-sea surface are critical aspects of ocean forcing and ocean modeling. Over most of the global oceans, there are few in situ observations that can be used to estimate these fluxes. This chapter provides background on the calculation and application of air-sea fluxes, as well as the use of remote sensing to calculate these fluxes. Wind variability makes a large contribution to variability in surface fluxes, and the remote sensing of winds is relatively mature compared to the air sea differences in temperature and humidity, which are the other key variables. Therefore, the remote sensing of wind is presented in greater detail. These details enable the reader to understand how the improper use of satellite winds can result in regional and seasonal biases in fluxes, and how to calculate fluxes in a manner that removes these biases. Examples are given of high-resolution applications of fluxes, which are used to indicate the strengths and weakness of satellite-based calculations of ocean surface fluxes.
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Bourassa, M. A., Legler, D. M., O'Brien, J. J., & Smith, S. R. (2003). SeaWinds validation with research vessels. J. Geophys. Res., 108(C2).
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Bourassa, M. A., Romero, R., Smith, S. R., & O'Brien, J. J. (2005). A New FSU Winds Climatology. J. Climate, 18(17), 3686–3698.
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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).
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Brolley, J. M., O'Brien, J. J., Schoof, J., & Zierden, D. (2007). Experimental drought threat forecast for Florida. Agricultural and Forest Meteorology, 145(1-2), 84–96.
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Bruno-Piverger, R. E. (2019). Applying Neural Networks to Simulate Visual Inspection of Observational Weather Data. Florida State University College of Arts and Sciences, Master's Thesis, .
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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.
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Carstens, J. (2019). Tropical Cyclogenesis from Self-aggregated Convection in Numerical Simulations of Rotating Radiative-convective Equilibrium. Florida State University - FCLA; ProQuest Dissertations & Theses Global.
Abstract: Organized convection is of critical importance in the tropical atmosphere. Recent advances in numerical modeling have revealed that moist convection can interact with its environment to transition from a quasi-random to organized state. This phenomenon, known as convective self-aggregation,is aided by feedbacks involving clouds, water vapor, and radiation that increase the spatial variance of column-integrated frozen moist static energy. Prior studies have shown self-aggregation to takeseveral different forms, including that of spontaneous tropical cyclogenesis in an environment of rotating radiative-convective equilibrium (RCE). This study expands upon previous work to address the processes leading to tropical cyclogenesis in this rotating RCE framework. More specifically,a three-dimensional, cloud-resolving numerical model is used to examine the self-aggregation of convection and potential cyclogenesis, and the background planetary vorticity is varied on an f-plane across simulations to represent a range of deep tropical and near-equatorial environments.Convection is initialized randomly in an otherwise homogeneous environment, with no background wind, precursor disturbance, or other synoptic-scale forcing.All simulations with planetary vorticity corresponding to latitudes from 10°to 20°generate intense tropical cyclones, with maximum wind speeds of 80 m s−1or above. Time to genesis varies widely, even within a five-member ensemble of 20°simulations, reflecting a potential degree of stochastic variability based in part on the initial random distribution of convection. Shared across this so-called “high-f” group is the emergence of a midlevel vortex in the days leading to genesis,which has dynamic and thermodynamic implications on its environment that facilitate the spinup of a low-level vortex. Tropical cyclogenesis is possible in this model even at values of Coriolis parameter as low as that representative of 1°. In these experiments, convection self-aggregates into a quasi-circular cluster, which then begins to rotate and gradually strengthen into a tropical storm, aided by near-surface inflow and shallow overturning radial circulations aloft within the aggregated cluster. Other experiments at these lower Coriolis parameters instead self-aggregate into an elongated band and fail to undergo cyclogenesis over the 100-day simulation. A large portion of this study is devoted to examining in greater detail the dynamic and thermodynamic evolution of cyclogenesis in these experiments and comparing the physical mechanisms to current theories.
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Chassignet, E. P., Jones, J. W., Misra, V., & Obeysekera, J. (2017). Florida's Climate: Changes, Variations, & Impacts.
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