Thesis (M.A.)--University of Wisconsin, 1974. / Bound typescript (Photocopy). eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaf 49).

Thesis (M.S.)--University of Wisconsin--Madison, 1970. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.S.)--University of Wisconsin-Madison, 1982. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 66-67).

Thesis (M.S. in Meteorology and Physical Oceanography)--Naval Postgraduate School, September 2009. / Thesis Advisor(s): Harr, Patrick A. "September 2009." Description based on title screen as viewed on November 10, 2009. Author(s) subject terms: Tropical Cyclone, Joint Typhoon Warning Center, Surface Wind Field, THORPEX Asian Regional Campaign, Tropical Cyclone Structure 2008, Western North Pacific Typhoons, H*Wind Analyses. Includes bibliographical references (p. 75-76). Also available in print.

Thesis (Ph. D.)--Ohio State University, 1997. / Includes bibliographical references (leaves 146-154).

No description available.

Interannual variability of temperature and cyclone frequencies for Eastern Canada and the New England States have been investigated for the winter seasons 1931-32 to 1984-85. Seasonal analyses have revealed that cyclone frequency has decreased by 21% over the research area; the highest losses occurring over the Maritimes and the New England States (30%) and in the southern Quebec-southwestern Ontario region (31%). The seasonal average temperature has remained fairly stable during the research period. However, the Temperature Variability Index (TVI) suggests that the interannual variability of temperature has been through some changes since 1931-32. The latest shift indicates that, since the early seventies, the temperature variability appears to be increasing during the winter season. Half-month periods were analyzed which revealed some features of the climatic variability during the winter season since 1931-32. Average temperature for the first 15 days of January recorded a significant decrease over the last 54 years. On the other hand, the last half of February presented a general increase in temperature. Parallel to that, the last half of January and the first 15 days of February have recorded substantial decreases in cyclone frequency. Thus, these half-month periods reveal trends which indicate that the overall winter season of the mid-seventies--early eighties differs from the prevailing winter climatic conditions of the thirties and forties.

Thesis (M.S.)--University of Hawaii at Manoa, 2006. / Includes bibliographical references (leaves 28-29). / vii, 58 leaves, bound 29 cm

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.

Forecast hurricane tracks using a multi-model ensemble that is comprised by linearly combining the individual model forecasts have greatly reduced the average forecast errors when compared to individual dynamic model forecast errors. In this experiment, a complex adaptive system, the Tropical Agent Forecaster (TAF), is created to fashion a 'smart' ensemble forecast. The TAF uses autonomous agents to assess the historical performance of individual models and model combinations, called predictors, and weights them based on their average error compared to the best track information. Agents continually monitor themselves and determine which predictors, for the life of the storm, perform the best in terms of the distance between forecast and best-track positions. A TAF forecast is developed using a linear combination of the highest weighted predictors. When applied to the 2004 Atlantic hurricane season, the TAF system with a requirement to contain a minimum of three predictors, consistently outperformed, although not statistically significant, the CONU forecast at 72 and 96 hours for a homogeneous data set. At 120 hours, the TAF system significantly decreased the average forecast errors when compared to the CONU.