Thesis (Ph. D.)--Oregon State University, 2008. / Printout. Includes bibliographical references. Also available on the World Wide Web.

An idealized atmospheric model consisting of energy and moisture conservation equations is developed for studies of the ocean's role in climate. Testing under fixed oceanic conditions yields a climatology comparable with direct observations, as does the case when the interpentadal (1955–59; 1970–74) sea surface temperature fields are applied. The atmospheric model is then coupled to an ocean general circulation model as well as a thermodynamic ice model without the use of flux adjustments. When configured for a global realistic geometry, the model faithfully represents deep water formation in the Atlantic and Southern Oceans with upwelling throughout the Pacific and Indian Oceans. The model is then utilized to investigate the influence of meltwater discharge on the stability of North Atlantic Deep Water (NADW) production and the Younger Dryas (YD ∼ 14ka). Results suggest pre-YD meltwater is capable of diminishing NADW to the point where diversion of meltwater from the Gulf of Mexico to the St. Lawrence completely inhibits its production. The coupled model appears to be stable in this state, equivalent to the “Southern Sinking” equilibrium identified in previous models. Inclusion of the wind stress/speed feedback, however, has a dramatic effect causing a reestablishment of NADW production. The model is then configured in a four basin-two hemisphere sector geometry, crudely representative of the global oceans. Two identically formulated models (one of which employs flux adjustments) are then perturbed to assess the role of flux adjustments on the ocean's response to a “global warming-like” scenario. Significant global and basin-scale differences exist between the cases which is linked to the influence of the salt-flux adjustment on the overturning cells within the model Atlantic and Southern Oceans. Results further suggest that minimizing the coupling shock prior to applying the perturbation leads to results slightly closer between the models, although large differences still persist. The model is then configured for a highly idealized 60° sector geometry to study the influence of horizontal resolution and parameterized eddy processes on poleward heat transport. As resolution increases, the total oceanic heat transport steadily increases. This result is also evidenced in a parallel series of ocean-only model studies driven by restoring boundary conditions. In each case the increase in heat transport is associated with the steady currents. In particular the baroclinic gyre transport (our model analog of the transport associated with the “Warm Core” jet region of the Gulf Stream) increases by a factor of 5 between coarsest and finest resolution. Spontaneous decadal-scale variability is also found to exist in the higher resolution experiments (with the exception of one of the restoring cases). The oscillation is thermally driven by an advective-convective mechanism and linked to the value of the horizontal diffusivity employed. Increasing the diffusivity in the high resolution cases is enough to destroy the variability, while decreasing the diffusivity in the moderately coarse resolution case is enough to induce the variability. These results point to the importance of higher resolution in the oceanic component of current climate models, yielding enhanced poleward heat transports and revealing the existence of richer decadal-scale variability in models which require less parameterized viscosity and diffusion. / Graduate

Thesis. 1975. M.S.--Massachusetts Institute of Technology. Dept. of Meteorology. / Bibliography: leaf 42. / by David G. Strimaitis. / M.S.

Graduation date: 2000

Thesis (Ph.D.). / Written for the Dept. of Atmospheric and Oceanic Sciences. Title from title page of PDF (viewed 2008/02/12). Includes bibliographical references.

Thesis (M.S. in Meteorology)--Naval Postgraduate School, March 2005. / Thesis Advisor(s): Patrick Harr. Includes bibliographical references (p. 91-92). Also available online.

Thesis (Ph.D.)--Memorial University of Newfoundland, 1999. / Bibliography: leaves 234-240.

Thesis (Ph. D.)--University of Washington, 1973. / Vita. Includes bibliographical references (leaves 155-157).

Thesis (Ph. D.)--Johns Hopkins University, 1996. / Vita. Includes bibliographical references (leaves 137-150).

Atmospheric CO₂ is projected to increase for the foreseeable future. The amount of CO₂ that remains in the atmosphere is regulated, in large part, by the ocean. As the long-term response to the changing atmospheric pCO₂ unfolds, the ocean sink will continue to be modified on seasonal to decadal timescales by climate variability and change. The magnitude of this variability is an active area of research. Accurately quantifying this variability is a challenge given the paucity of direct in-situ observations. In order calculate the global air-sea CO₂ sink, ocean pCO₂ needs to be known, or at least accurately estimated, at all locations at regular intervals. Two approaches to estimate air-sea CO₂ flux are, 1) from simulations of the Earth system and 2) data gap-filling mapping techniques. The goals of this thesis are to 1) rigorously quantify errors in a leading pCO₂ and ocean CO₂ sink mapping technique and 2) to evaluate the efficacy of adding Earth system model based estimates of ocean pCO₂ as a first guess into machine learning based mapping techniques. To meet the first goal, we use a suite of Large Ensemble model members as a testbed to evaluate a leading pCO₂ gap-filling approach (SOM-FFN). We find that the SOM-FFN performs well when sufficient data is available, but overestimates Southern Ocean decadal variability by about 39%. To meet our second goal, we incorporate Earth system model pCO₂ output into machine learning techniques either by adding the output as an additional feature or by post-processing the model output by learning the misfit (misfit=observation-model) and correcting for it. We find that blending model output and observations using machine learning marginally improves prediction accuracy. In addition, we discuss the potential of the learned misfits as a new model diagnostic tool, which can be used to visualize spatiotemporal pCO₂ estimates. Taken together, this study has significant implications in the development of carbon monitoring systems, in turn aiding policy making and improving our understanding of the evolution of the air-sea CO₂ sink.