Phelps, M., Kumar, A., & O'Brien, J. J. (2002). Potential predictability in the NCEP/CPC dynamical seasonal forecast system . COAPS Technical Report 02-04a. Tallahassee, FL: Center for Ocean-Atmospheric Prediction Studies, Florida State University.
Salapata, D., Higgins, W., Schemn, J., & O'Brien, J. J. (2002). Winter Temperature and Precipitation Verification of the NCEP Operational Climate Model . COAPS Technical Report 02-04b. Tallahassee, FL: Center for Ocean-Atmospheric Prediction Studies, Florida State University.
Arguez, A., Smith, S. R., & O'Brien, J. J. (2002). The relationship between low-frequency North Atlantic sea surface temperatures and Eastern North American climate . COAPS Technical Report 02-6. Tallahassee, FL: Center for Ocean-Atmospheric Prediction Studies, Florida State University.
Tartaglione, C. S., Hanley, D. E., O'Brien, J. J., & Smith, S. R. (2002). Regional Effects of ENSO on U.S Hurricane Landfalls . COAPS Technical Report 02-5. Tallahassee, FL: Center for Ocean-Atmospheric Prediction Studies, Florida State University.
Morey, S., Koch, M., Liu, Y., & Lee, S. - K. (2017). Florida's oceans and marine habitats in a changing climate. In E. P. Chassignet, J. W. Jones, V. Misra, & J. Obeysekera (Eds.), Florida's climate: Changes, variations, & impacts (pp. 391–425). Gainesville, FL: Florida Climate Institute.
Stauffer, C. L. (2018). Air-sea coupling dependency on sea surface temperature fronts as observed by research vessel data . Bachelor's thesis, Florida State University, Tallahassee, FL.
Stewart, M. L. (2007). Cyclogenesis and Tropical Transition in Frontal Zones . Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Tropical cyclones can form from many different precursors, including baroclinic systems. The process of an extratropical system evolving into a warm core tropical cyclone is defined by Davis and Bosart (2004) as a Tropical Transition (TT) with further classification of systems into Weak Extratropical Cylclones (WEC) and Strong Extratropical Cyclones (SEC). It is difficult to predict which systems will make the transition and which will not, but the description of a common type of TT occurring along a front will aid forecasters in identifying systems that might undergo TT. A wind speed and SST relationship thought to be necessary for this type of transition is discussed. QuikSCAT and other satellite data are used to locate TT cases forming along fronts and track their transformation into tropical systems. Frontal TT is identified as a subset of SEC TT and the evolution from a frontal wave to a tropical system is described in five stages. A frontal wave with stronger northerly wind and weaker southerly wind is the first stage in the frontal cyclogenesis. As the extratropical cyclogenesis continues in the next two stages, bent back warm front stage and instant occlusion stage, the warmer air of the bent back front becomes surrounded by cooler air . Next, in the subtropical stage the latent heat release energy from the ocean surface begins ascent and forms a shallow warm core. As the energy from surface heat fluxes translates to convection within the system, the warm core extends further into the upper levels of the atmosphere in the final, tropical stage of TT. Model data from MM5 simulations of three storms, Noel (2001), Peter (2003) and Gaston (2004) are analyzed to illustrate the five stages of frontal TT. Noel is found to have the most baroclinic origin of the three and Gaston the least.
Yu, P. (2006). Development of New Techniques for Assimilating Satellite Altimetry Data into Ocean Models . Ph.D. thesis, Florida State University, Tallahassee, FL.
Abstract: State of the art fully three-dimensional ocean models are very computationally expensive and their adjoints are even more resource intensive. However, many features of interest are approximated by the first baroclinic mode over much of the ocean, especially in the lower and mid latitude regions. Based on this dynamical feature, a new type of data assimilation scheme to assimilate sea surface height (SSH) data, a reduced-space adjoint technique, is developed and implemented with a three-dimensional model using vertical normal mode decomposition. The technique is tested with the Navy Coastal Ocean Model (NCOM) configured to simulate the Gulf of Mexico. The assimilation procedure works by minimizing the cost function, which generalizes the misfit between the observations and their counterpart model variables. The “forward” model is integrated for the period during which the data are assimilated. Vertical normal mode decomposition retrieves the first baroclinic mode, and the data misfit between the model outputs and observations is calculated. Adjoint equations based on a one-active-layer reduced gravity model, which approximates the first baroclinic mode, are integrated backward in time to get the gradient of the cost function with respect to the control variables (velocity and SSH of the first baroclinic mode). The gradient is input to an optimization algorithm (the limited memory Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is used for the cases presented here) to determine the new first baroclinic mode velocity and SSH fields, which are used to update the forward model variables at the initial time. Two main issues in the area of ocean data assimilation are addressed: 1. How can information provided only at the sea surface be transferred dynamically into deep layers? 2. How can information provided only locally, in limited oceanic regions, be horizontally transferred to ocean areas far away from the data-dense regions, but dynamically connected to it? The first problem is solved by the use of vertical normal mode decomposition, through which the vertical dependence of model variables is obtained. Analyses show that the first baroclinic mode SSH represents the full SSH field very closely in the model test domain, with a correlation of 93% in one of the experiments. One common way to solve the second issue is to lengthen the assimilation window in order to allow the dynamic model to propagate information to the data-sparse regions. However, this dramatically increases the computational cost, since many oceanic features move very slowly. An alternative solution to this is developed using a mapping method based on complex empirical orthogonal functions (EOF), which utilizes data from a much longer period than the assimilation cycle and deals with the information in space and time simultaneously. This method is applied to map satellite altimeter data from the ground track observation locations and times onto a regular spatial and temporal grid. Three different experiments are designed for testing the assimilation technique: two experiments assimilate SSH data produced from a model run to evaluate the method, and in the last experiment the technique is applied to TOPEX/Poseidon and Jason-1 altimeter data. The assimilation procedure converges in all experiments and reduces the error in the model fields. Since the adjoint, or “backward”, model is two-dimensional, the method is much more computationally efficient than if it were to use a fully three-dimensional backward model.
Banks, R. (2006). Variability of Indian Ocean Surface Fluxes Using a New Objective Method . Master's thesis, Florida State University, Tallahassee, FL.
Abstract: A new objective technique is used to analyze monthly mean gridded fields of air and sea temperature, scalar and vector wind, specific humidity, sensible and latent heat flux, and wind stress over the Indian Ocean. A variational method produces a 1°x1° gridded product of surface turbulent fluxes and the variables needed to calculate these fluxes. The surface turbulent fluxes are forced to be physically consistent with the other variables. The variational method incorporates a state of the art flux model, which should reduce regional biases in heat and moisture fluxes. The time period is January 1982 to December 2003. The wind vectors are validated through comparison to monthly scatterometer winds. Empirical orthogonal function (EOF) analyses of the annual cycle emphasize significant modes of variability in the Indian Ocean. The dominant monsoon reversal and its connection with the southeast trades are linked in eigenmodes one and two of the surface fluxes. The third eigenmode of latent and sensible heat flux reveal a structure similar to the Indian Ocean Dipole (IOD) mode. The variability in surface fluxes associated with the monsoons and IOD are discussed. September-October-November composites of the surface fluxes during the 1997 positive IOD event and the 1983 negative IOD event are examined. The composites illustrate characteristics of fluxes during different IOD phases.
Lombardi, K. C. (2004). Resolving the Diurnal and Synoptic Variance of Scatterometer Vector Wind Observations . Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Scatterometer observations of vector winds are used to examine the amplitudes of synoptic and diurnal cycles. Scatterometers have the advantage of providing global coverage over water; however, irregular temporal sampling complicates the analyses. A least squares technique is used in determination of the amplitudes and phases of the diurnal and synoptic cycles on spatial scales of 5°, 15°, and 30°. In open ocean areas and regions with sufficient open water, the magnitudes of the diurnal and synoptic cycles are 1.0 ms-1 and 3.5ms-1, respectively. Diurnal amplitudes are highest in the polar regions and close to land surfaces due to sea breeze effects. The fraction of variance explained by the diurnal cycle is greatest near the equator. Synoptic amplitudes are consistently larger downwind of land from storm tracks and in the southern polar region as the time analyzed is during the southern winter season.
