Thesis (M.S.)--University of Wisconsin--Madison. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 103-104).

Thesis (M.S.)--University of Wisconsin--Madison, 1981. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 112-114).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1918. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.S.)--University of Wisconsin--Madison. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 41-42).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1976. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 171-175).

Thesis (M.S.)--University of Wisconsin--Madison, 1962. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 40-42).

Thesis (Ph. D.)--University of Illinois at Urbana-Champaign, 2006. / Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 3651. Adviser: Donald J. Wuebbles. Includes bibliographical references (leaves 130-148). Available on microfilm from Pro Quest Information and Learning.

<p> This dissertation explores the interactions between the atmosphere and wind turbines from numerous perspectives. The work presented here outlines three subjects: the characterization of wind-turbine wakes in the evening, the evaluation of simulated wind-power productions in a numerical weather prediction model, and the attempt to systematically quantify wind-speed (WS) variability over decades. </p><p> After introducing the background of wind-energy meteorology, the first part of this dissertation discusses the evolution of wind-turbine wakes during the evening transition. In observations as well as simulations from the Weather Research and Forecasting (WRF) model, turbine wakes, namely the in downwind WS reduction and turbulence enhancement, become more prominent in the evening. Hence, the power generations of downwind turbines decrease when the atmosphere changes from unstable to stable. </p><p> The second section of this dissertation focuses on validating the power-production predictions of the wind farm parameterization (WFP) scheme in the WRF model. Using the WFP with fine (&sim;12 m) vertical grid resolution leads to the most accurate power simulations. Compared to the actual power generations, the WFP tends to underestimate power in stable conditions with high winds and low turbulence. Overall, the accuracy of the WRF model in WS prediction dictates the skill of the WFP in simulating wind power. </p><p> The third topic of this dissertation explores optimal methods to assess the variability of WS and energy production. Among the 27 methods tested, the Robust Coefficient of Variation (RCoV), as a normalized, statistically robust and resistant spread metric, yields the strongest correlation in connecting the variations between monthly mean WS and monthly net energy generation. By comparison to a long data record from a reanalysis product, the RCoV also requires 6 years of WS data to effectively quantify the long-term variability of a location. </p><p> Finally, this dissertation ends with a remark on the importance of correctly using the WRF WFP and statistics. Future work includes improving the power curve and applying the variability metrics in evaluating financial risk.</p><p>

<p> The development of offshore wind energy is moving forward as one of several options for carbon-free energy generation along the populous US east coast. Accurate assessments of the wind resource are essential and can significantly lower financing costs that have been a barrier to development. Wind resource assessment in the Mid-Atlantic region is challenging since there are no long-term measurements of winds across the rotor span. Features of the coastal and inland terrain, such as such as the Appalachian mountains and the Chesapeake Bay, are known to lead to complex mesoscale wind regimes onshore, including low-level jets (LLJs), downslope winds and sea breezes. Little is known, however, about whether or how the inland physiography impacts the winds offshore. This research is based on the first comprehensive set of offshore wind observations in the Maryland Wind Energy Area gathered during a UMBC measurement campaign. The presentation will include a case study of a strong nocturnal LLJ that persisted for several hours before undergoing a rapid breakdown and loss of energy to smaller scales. Measurements from an onshore wind profiler and radiosondes, together with North American Regional Analysis (NARR) and a high resolution Weather Research and Forecast (WRF) model simulation, are used to untangle the forcing mechanisms on synoptic, regional and local scales that led to the jet and its collapse. The results suggest that the evolution of LLJs were impacted by a downslope wind from the Appalachians that propagated offshore riding atop a shallow near-surface boundary layer across the coastal plain. Baroclinic forcing from low sea surface temperatures (SSTs) due to coastal upwelling is also discussed. Smaller scale details of the LLJ breakdown are analyzed using a wave/mean flow/turbulence interaction approach. The case study illustrates several characteristics of low-level winds offshore that are important for wind energy, including LLJs, strong wind shear, turbulence and rapid changes in the wind, so-called "ramp events&rdquo;. A 3-year survey based on NARR analyses is used to estimate the likelihood that similar events could occur under the same meteorological conditions.</p><p>

Temperature variability and change over land and ocean exhibit characteristic spatial and temporal structures. Understanding the physical mechanisms underlying these structures provides information about the movement and storage of heat in the climate system. In this thesis, I first analyze, and present an energy balance model for, seasonal temperature variability in the extratropics, which supports the idea that the advection of heat between land and ocean by the mean atmospheric circulation can explain the regional characteristics of seasonal variability over both land and ocean. The model is subsequently combined with a large, representative ensemble of Lagrangian atmospheric trajectories to provide a realistic model of the seasonal cycle in the Northern Hemisphere mid-latitudes. Second, based on the Lagrangian trajectories, a new spatially-resolved metric, termed Relative Land Influence, is developed. The metric quantifies the role of land as compared to ocean in influencing the temperature variability at a given location. In addition to explaining the majority of the spatial pattern of seasonal variability, Relative Land Influence is a significant predictor of the observed temperature change over both land and ocean independently since 1950, suggesting that similar physical processes influence temperature variability on seasonal and decadal timescales. Finally, I explore the tails of temperature distributions in the context of identifying the causes of anomalously hot days in the Eastern United States during peak summer. A coupled ocean-atmosphere mode in the central mid-latitude Pacific is identified, which evolves on a characteristic timescale and ultimately leads to the amplification of a mid-latitude wave train that includes a blocking high over the Eastern United States. The early identification of the sea surface temperature precursors to this mode allows for skillful prediction of heat events at lead times greater than 40 days. The identification of physical processes underlying temperature variability on a range of timescales can inform predictions of how temperature variability may change in the future. / Earth and Planetary Sciences