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.
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.
Lowry, M. R. (2009). Developing a Unified Superset in Quantifying Ambiguities Among Tropical Cyclone Best Track Data for the Western North Pacific . Master's thesis, Florida State University, Tallahassee, FL.
Abstract: In the western North Pacific basin, several agencies archive “best track” data of tropical cyclones. The Joint Typhoon Warning Center (JTWC) in Hawaii is responsible for the issuance of tropical cyclone warnings for United States Department of Defense interests and has a record of tropical cyclones extending back to 1945. The Japanese Meteorological Agency (JMA) is the World Meteorological Organization (WMO) official Regional Specialized Meteorological Center (RSMC) for the western North Pacific basin and has best track tropical cyclone data extending back to 1951. The Shanghai Typhoon Institute (STI) of the Chinese Meteorological Administration and the Hong Kong Observatory (HKO) of the Government of the Hong Kong Special Administrative Region also have 6-hourly tropical cyclone data records from 1949 and 1961, respectively. Western North Pacific (WNP) data sets are investigated in order to quantify ambiguities in position and intensity estimates among the forecast institutions through the development of a unified Superset. Ambiguities among the two primary warning centers (JMA and JTWC) are presented in the context of a changing observation network, observational tools, and analysis techniques since the beginning of tropical cyclone records. Mean differences in position estimates are found between the two centers on the order of 60 km prior to the introduction of meteorological satellites in 1961 and near 50 km following the deactivation of aircraft reconnaissance in 1987. Results show a step function change among intensity in JTWC and JMA best track data from 1989 to 1990 due to varying applications of the Dvorak intensity estimation technique. Parsing best track data into landfall subsets does not ameliorate interagency differences in position or intensity estimates. Additionally, analyses from Superset data call into question the veracity of JTWC best track data during the period from 1995-1999. The applicability of adopting an individual data set in discerning long term climate trends is examined in light of these differences. Past efforts to analyze, assemble, and maintain a complete, reliable best track tropical cyclone data set for the WNP are discussed among topical methods of incorporating the Superset within a basin-wide re-analysis.
Williams, M. (2010). Characterizing Multi-Decadal Temperature Variability in the Southeastern United States . Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Prior studies of the long-term temperature record in the Southeastern United States (SE US) mostly discuss the long-term cooling trend, and the inter-annual variability produced by the region's strong ties to El Niño Southern Oscillation (ENSO). An examination of long-term temperature records in the SE US show clear multi-decadal variations in temperature, with relative warm periods in the 1920's through the mid 1950's and a cool period in the late 1950's through the late 1990's. This substantial shift in multi-decadal variability is not well understood and has not been fully investigated. It appears to account for the long-term downward trend in temperatures. An accurate characterization of this variability could lead to improved interannual and long-term forecasts, which would be useful for agricultural planning, drought mitigation, water management, and preparation for extreme temperature events. Statistical methods are employed to determine the spatial coherence of the observed variability on seasonal time scales. The goal of this study is to characterize the nature of this variability through the analysis of National Weather Service Cooperative Observer Program (COOP) station data in Florida, Georgia, Alabama, North Carolina, and South Carolina. One finding is a shift in the temperature Probability Distribution Function (PDF) between warm regimes and cool regimes.
Winterbottom, H. (2010). The Development of a High-Resolution Coupled Atmosphere-Ocean Model and Applications Toward Understanding the Limiting Factors for Tropical Cyclone Intensity Prediction . Ph.D. thesis, Florida State University, Tallahassee, FL.
Abstract: The prediction of tropical cyclone (TC) motion has improved greatly in recent decades. However, similar trends remain absent with respect to TC intensity prediction. Several hypotheses have been proposed attempting to explain why dynamical NWP models struggle to predict TC intensity. The leading candidates are as follows: (1) the lack of an evolving ocean (i.e., sea-surface temperature) boundary condition which responds as a function of the atmosphere (e.g., TC) forcing, (2) inappropriate initial conditions for the TC vortex (e.g., lack of data assimilation methods), (3) NWP model grid-length resolutions which are unable to resolve the temporal and length scale for the features believed responsible for TC vortex intensity. modulations (i.e., eye-wall dynamics, momentum transport, vortex Rossby wave interactions, etc.), and (4) physical parametrization which do not adequately represent the air-sea interactions observed during TC passage. In this study, a coupling algorithm for two independent, high-resolution, and state-of-the-art atmosphere and ocean models is developed. The atmosphere model -- the Advanced Weather Research and Forecasting (WRF-ARW) model is coupled to the HYbrid Coordinate Ocean Model (HYCOM) using a (UNIX) platform independent and innovative coupling methodology. Further, within the WRF-ARW framework, a dynamic initialization algorithm is developed to specify the TC vortex initial condition while preserving the synoptic-scale environment. Each of the tools developed in this study is implemented for a selected case-study: TC Bertha (2008) and TC Gustav (2008) for the coupled-model and TC vortex initialization, respectively. The experiment results suggest that the successful prediction (with respect to the observations) for both the ocean response and the TC intensity cannot be achieved by simply incorporating (i.e., coupling) an ocean model and/or by improving the initial structure for the TC. Rather the physical parametrization governing the air-sea interactions is suggested as the one of the weaknesses for the NWP model. This hypothesis is (indirectly) supported through a diagnostic evaluation of the synoptic-scale features (e.g., sea-level pressure and the deep-layer mean wind beyond the influence of the TC) while the assimilated TC vortex is nudged toward the observed intensity value. It is found -- in the case of TC Gustav (2008) using WRF-ARW, that as the assimilated TC vortex intensity approaches that of the observed, the balance between the mass and momentum states for WRF-ARW is compromised leading to unrealistic features for the environmental sea-level pressure and deep-layer (800- to 200-hPa) mean wind surrounding the TC. Forcing WRF-ARW to assimilate a TC vortex of the observed maximum wind-speed intensity may ultimately compromise the prediction for the TC's motion and subsequently mitigate any gains for the corresponding intensity prediction.Suggestions for additions to the coupled atmosphere-ocean model include a wave-model (WAVEWATCH3), the assimilation of troposphere thermodynamic observations, and modifications to the existing atmospheric boundary-layer parametrization. The current suite of atmosphere model parametrizations do not accurately simulate the observed azimuthal and radial variations for the exchange coefficients (e.g., drag and enthalpy) that have been indicated as potentialpredictor variables for TC intensity modulation. However, these modifications should be implemented only after the limitations for the current coupled-model and TC vortex initialization methods are fully evaluated.
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.
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.
Putnam, W. M. (2007). Development of the Finite-Volume Dynamical Core on the Cubed-Sphere . Ph.D. thesis, Florida State University, Tallahassee, FL.
Abstract: The finite-volume dynamical core has been developed for quasi-uniform cubed-sphere grids within a flexible modeling framework for direct implementation as a modular component within the global modeling efforts at NASA, GFDL-NOAA, NCAR, DOE and other interested institutions. The shallow water equations serve as a dynamical framework for testing the implementation and the variety of quasi-orthogonal cubed-sphere grids ranging from conformal mappings to those numerically generated via elliptic solvers. The cubed-sphere finite-volume dynamical core has been parallelized with a 2-dimensional X-Y domain decomposition to achieve optimal scalability to 100,000s of processors on today's high-end computing platforms at horizontal resolutions of 0.25-degrees and finer. The cubed-sphere fvcore is designed to serve as a framework for hydrostatic and non-hydrostatic global simulations at climate (4- to 1-deg) and weather (25- to 5-km) resolutions, pushing the scale of global atmospheric modeling from the climate/synoptic scale to the meso- and cloud-resolving scale.
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.
Smith, R. A. (2007). Trends in Maximum and Minimum Temperature Deciles in Select Regions of the United States . Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Daily maximum and minimum temperature data from 758 COOP stations in nineteen states are used to create temperature decile maps. All stations used contain records from 1948 through 2004 and could not be missing more than 5 consecutive years of data. Missing data are replaced using a multiple linear regression technique from surrounding stations. For each station, the maximum and minimum temperatures are first sorted in ascending order for every two years (to reduce annual variability) and divided into ten equal parts (or deciles). The first decile represents the coldest temperatures, and the last decile contains the warmest temperatures. Patterns and trends in these deciles can be examined for the 57-year period. A linear least-squares regression method is used to calculate best-fit lines for each decile to determine the long-term trends at each station. Significant warming or cooling is determined using the Student's t-test, and bootstrapping the decile data will further examine the validity of significance. Two stations are closely examined. Apalachicola, Florida shows significant warming in its maximum deciles and significant cooling in its minimum deciles. The maximum deciles seem to be affected by some localized change. The minimum deciles are discontinuous, and the trends are a result of a minor station move. Columbus, Georgia has experienced significant warming in its minimum deciles, and this appears to be the result of an urban heat-island effect. The discontinuities seen in the Apalachicola case study illustrate the need for a quality control method. This method will eliminate stations from the regional analysis that experience large changes in the ten-year standard deviations within their time series. The regional analysis shows that most of the region is dominated by significant cooling in the maximum deciles and significant warming in the minimum deciles, with more variability in the lower deciles. Field significance testing is performed on subregions (based on USGS 2000 land cover data) and supports the findings from the regional analysis; it also isolates regions, such as the Florida peninsula and the Maryland/Delaware region, that appear to be affected by more local forcings.
