Thesis (Ph. D.)--University of Missouri-Columbia, 2003. / Typescript. Vita. Includes bibliographical references (leaves [71]-74). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2003. / Typescript. Vita. Includes bibliographical references (leaves [71]-74). Also available on the Internet.

Since the atmosphere is a chaotic system, small errors in the initial condition of any numerical weather prediction (NWP) model amplify as the forecast evolves. To estimate and possibly reduce the uncertainty of NWP associated with initial-condition uncertainty (ICU), ensemble forecasting has been proposed which is a method of, differently from the traditional deterministic forecasting, running several model forecasts starting from slightly different initial states. In this dissertation, the impact of ICU and short-range ensemble forecasting (SREF) on quantitative precipitation forecasts (QPFs), as well as on sea-level cyclone position and central pressure, is examined for a case of explosive cyclogenesis that occurred over the contiguous United States. A limited-area model (the PSU/NCAR MM4) is run at 80-km horizontal resolution and 15 layers to produce a 25-member, 36-h forecast ensemble. Lateral boundary conditions for the MM4 model are provided by ensemble forecasts from a global spectral model (the NCAR CCM1). The initial perturbations of the ensemble members possess a magnitude and spatial decomposition which closely match estimates of global analysis error, but they were not dynamically-conditioned. Results for 80-km ensemble forecast are compared to forecasts from the then operational Nested Grid Model (NGM), a single 40-km MM4 forecast, and a second 25-member MM4 ensemble based on a different cumulus parameterization and slightly different initial conditions. Acute sensitivity to ICU marks ensemble QPF and the forecasts of cyclone position and central pressure. Ensemble averaging always reduces the rms error for QPF. Nearly 90% of the improvement is obtainable using ensemble sizes as small as 8-10. However, ensemble averaging can adversely affect the forecasts related to precipitation areal coverage because of its smoothing nature. Probabilistic forecasts for five mutually exclusive, completely exhaustive categories are found to be skillful relative to a climatological forecast. Ensemble sizes of --, 10 can account for 90% of improvement in probability density function. Our results indicate that SREF techniques can now provide useful QPF guidance and increase the accuracy of precipitation, cyclone position, and cyclone's central pressure forecasts. With current analysis/forecast systems, the benefit from simple ensemble averaging is comparable to or exceed that obtainable from improvement in the analysis/forecast system.

This document proposes an objective technique to estimate the intensity and predict the formation of tropical cyclones using infrared satellite imagery. As the tropical cyclone develops from an unstructured cloud cluster and intensifies the cloud structures become more axisymmetric around an identified reference point or center. This methodology processes the image gradient to measure the level of symmetry of cloud structures, which characterizes the degree of cloud organization of the tropical cyclone.The center of a cloud system is calculated by projecting and accumulating parallel lines to the gradient vectors. The point where the highest number of line intersections is located pinpoints a common point where the corresponding gradients are directed. This location is used as the center of the system. Next, a procedure that characterizes the departure of the weather system structure from axisymmetry is implemented. The deviation angle of each gradient vector relative to a radial line projected from the center is calculated. The variance of the set of deviation angles enclosed by a circular area around the center describes the axisymmetry of the system, and its behavior through time depicts its dynamics. Results are presented that show the time series of the deviation angle variances is well correlated with the National Hurricane Center best-track estimates.The formation of tropical cyclones is detected by extending the deviation-angle variance technique, it is calculated using every pixel in the scene as the center of the cloud system. Low angle variances indicate structures with high levels of axisimmetry, and these values are compared to a set of thresholds to determine whether a cloud structure can be considered as a vortex. The first detection in a sequence indicates a nascent storm. It was found that 86% of the tropical cyclones during 2004 and 2005 were detected 27 h on average before the National Hurricane Center classified them as tropical storms (33kt).Finally, two procedures to locate the center of a tropical cyclone are compared to the National Hurricane Center best-track center database. Results show that both techniques provide similar accuracy, which increases as the tropical cyclone evolves.

Thesis (M.S. in Meteorology and Physical Oceanography)--Naval Postgraduate School, September 2002. / Thesis advisor(s): Russell L. Elsberry, Patrick A. Harr, Mark A. Boothe. Includes bibliographical references (p. 119-120). Also available online.

Thesis (Ph. D.)--Ohio State University, 1998. / Includes bibliographical references (leaves 104-115).

Thesis (M.S.)--Florida State University, 2005. / Advisor: T. N. Krishnamurti, Florida State University, College of Arts and Sciences, Dept. of Meteorology. Title and description from dissertation home page (viewed Jan. 26, 2006). Document formatted into pages; contains xi, 64 pages. Includes bibliographical references.

Thesis (M.S. in Meteorology)--Naval Postgraduate School, March 2005. / Thesis Advisor(s): C.-P. Chang. Includes bibliographical references (p. 49-51). Also available online.

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 187-192).

Thesis (Ph. D.)--Texas State University-San Marcos, 2006. / Vita. Appendices: leaves 119-142. Includes bibliographical references (leaves 143-147).