Selman, C. (2012).
Understanding the 21st Century Projection of the Wet Season over the Southeastern United States. Master's thesis, Florida State University, Tallahassee, FL.
Holbach, H. (2012).
The Effects of Gap-Wind-Induced Vorticity, the Monsoon Trough, and the ITCZ on Tropical Cyclogenesis. Master's thesis, Florida State University, Tallahassee, FL.
Farmer, B. (2012).
Evaluation of Bulk Heat Fluxes from Atmospheric Datasets. Master's thesis, Florida State University, Tallahassee, FL.
Collier, C. (2012).
Effects of Sea State on Offshore Wind Resourcing in Florida. Master's thesis, Florida State University, Tallahassee, FL.
Ford, K. M. (2008).
Uncertainty in Scatterometer-Derived Vorticity. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: A more versatile and robust technique is developed for determining area averaged surface vorticity based on vector winds from the SeaWinds scatterometer on the QuikSCAT satellite. This improved technique is discussed in detail and compared to two previous studies by Sharp et al. (2002) and Gierach et al. (2007) that focused on early development of tropical systems. The error characteristics of the technique are examined in detail. Specifically, three independent sources of error are explored: random observational error, truncation error and representation error. Observational errors are due to random errors in the wind observations, and determined as a worst-case estimate as a function of averaging spatial scale. The observational uncertainty in vorticity averaged for a roughly circular shape with a 100 km diameter, expressed as one standard deviation, is approximately 0.5 x 10 -5 s-1 for the methodology described herein. Truncation error is associated with the assumption of linear changes between wind vectors. For accurate results, it must be estimated on a case-by-case basis. An attempt is made to determine a lower bound of truncation errors through the use of composites of tropical disturbances. This lower bound is calculated as 10-7 s-1 for the composites, which is relatively small compared to the tropical disturbance detection threshold set at 5 x 10-5 s-1, used in an earlier study. However, in more realistic conditions, uncertainty related to truncation errors is much larger than observational uncertainty. The third type of error discussed is due to the size of the area being averaged. If the wind vectors associated with a vorticity maximum are inside the perimeter of this area (away from the edges), it will be missed. This type of error is analogous to over-smoothing. Tropical and sub-tropical low pressure systems from three months of QuikSCAT observations are used to examine this error. This error results in a bias of approximately 1.5 x 10-5 s-1 for area averaged vorticity calculated on a 100 km scale compared to vorticity calculated on a 25 km scale. The discussion of these errors will benefit future projects of this nature as well as future satellite missions.
Frumkin, A. (2011).
Predictability of Dry Season Reforecasts over the Tropical South American Region. Master's thesis, Florida State University, Tallahassee, FL.
Goto, Y. (2008).
Improved Vegetation Characterization and Freeze Statistics in a Regional Spectral Model for the Florida Citrus Farming Region. Ph.D. thesis, Florida State University, Tallahassee, FL.
Abstract: This study focused on the effective use of a numerical climate model for agriculture in Florida, especially in the citrus farming region of the Florida peninsula, because of the impact of agriculture to Florida's economy. For the analyses of the ensemble, the climate models used in this study were the FSU/COAPS Global Spectral Model and FSU/COAPS Regional Spectral Model (FSU/COAPS RSM) coupled with a land-surface model. The multi-convective scheme method and variable initial conditions were used for the ensembles. Severe freezes impacting agriculture in Florida were associated with some major climate patterns, such as El Niño and Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO). In the first part of this study, seasonal ensemble integrations of the regional model were examined for the tendencies of freezes in the Florida peninsula during each ENSO or NAO phase is examined. Mean excess values of minimum temperatures from thresholds on the basis of the Generalized Pareto Distribution (GPD), which represents the extreme data in a dataset, were used to analyze the freezes in the regional model. According to some previous studies, El Niño winters obtain fewer freezes than the other ENSO phases. Although the ensemble comprised only 19 winters, the ensemble found variability patterns in minimum temperatures in each climate phase similar to the findings in the previous studies which were based on the observed data. The FSU/COAPS RSM was coupled with Community Land Model 2.0 (CLM2), to represent the land-surface conditions. Although the coupling improved the temperature forecast of the RSM, it still has a cold bias and simulates smaller diurnal temperature changes than actually occur in southern Florida. Among the prescribed surface data, Leaf Area Index (LAI) for southern Florida in the CLM2 is lower than those observed by MODIS (Moderate Resolution Imaging Spectroradiometer). In the first experiment of this part, the sensitivity of the temperature forecast to the LAI in the climate models was investigated, by modifying the LAI data in the CLM2 based on the monthly MODIS observations. In the second experiment, newly created prescribed datasets of LAI and plant functional types for the CLM2 based on the MODIS observations were applied to the RSM. The substitution increased the diurnal temperature change in southern Florida slightly but almost consistently.
Gouillon, F. (2010).
Internal Wave Propagation and Numerically Induced Diapycnal Mixing in Oceanic General Circulation Models. Ph.D. thesis, Florida State University, Tallahassee, FL.
Abstract: Numerical ocean models have become powerful tools for providing a realistic view of the ocean state and for describing ocean processes that are difficult to observe. Recent improvements in model performance focus on simulating realistic ocean interior mixing rates, as ocean mixing is the main physical process that creates water masses and maintains their properties. Below the mixed layer, diapycnal mixing primarily arises from the breaking of internal waves, whose energy is largely supplied by winds and tides. This is particularly true in abyssal regions, where the barotropic tide interacts with rough topography and where high levels of diapycnal mixing have been recorded (e.g., the Hawaiian Archipelago). Many studies have discussed the representation of internal wave generation, propagation, and evolution in ocean numerical models. Expanding on these studies, this work seeks to better understand the representation of internal wave dynamics, energetics, and their associated mixing in several different classes of widely used ocean models (e.g., the HYbrid Coordinate Ocean Model, HYCOM; the Regional Ocean Modeling System, ROMS; and the MIT general circulation model, MITgcm). First, a multi-model study investigates the representation of internal waves for a wide spectrum of numerical choices, such as the horizontal and vertical resolution, the vertical coordinate, and the choice of the numerical advection scheme. Idealized configurations are compared to their corresponding analytical solutions. Some preliminary results of realistic baroclinic tidal simulations are shown for the Gulf of Mexico. Second, the spurious diapycnal mixing that exists in models with fixed vertical coordinates (i.e., geopotential and terrain following) is documented and quantified. This purely numerical error arises because, in fixed-coordinate models, the numerical framework cannot properly maintain the adiabatic properties of an advected water parcel. This unrealistic mixing of water masses can be a source of major error in both regional and global ocean models. We use the tracer flux method to compute the spurious diapycnal diffusivities for both a lockexchange scenario and a propagating internal wave field using all three models. Results for the lock exchange experiments are compared to the results of a recent study. Our results, obtained by using three different model classes, provide a comprehensive analysis of the impact of model resolution choice and numerical framework on the magnitude of the spurious diapycnal mixing and the representation of internal waves.
Hite, M. M. (2006).
Vorticity-Based Detection of Tropical Cyclogenesis. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Ocean wind vectors from the SeaWinds scatterometer on QuikSCAT and GOES imagery are used to develop an objective technique that can detect and monitor tropical disturbances associated with the early stages of tropical cyclogenesis in the Atlantic basin. The technique is based on identification of surface vorticity and wind speed signatures that exceed certain threshold magnitudes, with vorticity averaged over an appropriate spatial scale. The threshold values applied herein are determined from the precursors of 15 tropical cyclones during the 1999-2004 Atlantic hurricane seasons using research-quality QuikSCAT data. Tropical disturbances are found for these cases within a range of 19 hours to 101 hours before classification as tropical cyclones by the National Hurricane Center (NHC). The 15 cases are further subdivided based upon their origination source (i.e., easterly wave, upper-level cut-off low, stagnant frontal zone, etc). Primary focus centers on the cases associated with tropical waves, since these waves account for approximately 63% of all Atlantic tropical cyclones. The detection technique illustrates the ability to track these tropical disturbances from near the coast of Africa. Analysis of the pre-tropical cyclone (TC) tracks for these cases depict stages, related to wind speed and precipitation, in the evolution of an easterly wave to tropical cyclone.
Griffin, J. (2009).
Characterization of Errors in Various Moisture Roughness Length Parameterizations. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Often the parameterization of the moisture roughness length is not seen as being important, as long as the parameterization seems reasonable; that is, it is within the rather considerable bounds of error for the data sets used to determine the parameterization. However, the choice of parameterization does influence height adjustments of humidity and calculations of turbulent heat fluxes. This paper focuses on the calculation of the turbulent heat fluxes using different parameterizations of roughness length. Five roughness length parameterizations are examined herein. These parameterizations include wall theory; the Clayson, Fairall, Curry parameterization; the Liu, Katsaros, Businger parameterization; Zilitinkevich et al. parameterization; and the COARE3.0 parameterization. Turbulent heat fluxes are calculated from each parameterization of the roughness length and are compared to observed turbulent heat flux values. The bulk latent heat flux estimates have a much better signal to noise ratio than the sensible heat fluxes, and are therefore the focus of the comparison to observations. This comparison indicates how to improve the proportionality in the above roughness length parameterizations, which are causing modeled turbulent heat flux magnitudes to be too large in four of the five parameterizations. The modeled turbulent heat fluxes are evaluated again after the modification of the parameterizations. Significant improvements in both the bias and the root mean square error (RMSE) are seen. Three parameterizations see roughly the same improvements of around 17Wm^-2 in the bias and roughly 10Wm^-2 in the RMSE. The largest improvements are in the Liu, Katsaros, Businger parameterization with bias improvements of over 45Wm^-2 and a RMSE reduction of nearly 32Wm^-2.