Show simple item record

dc.contributor.authorBenton, Brandon Norton
dc.date.accessioned2020-06-23T18:01:55Z
dc.date.available2020-06-23T18:01:55Z
dc.date.issued2019-12
dc.identifier.otherBenton_cornellgrad_0058F_11805
dc.identifier.otherhttp://dissertations.umi.com/cornellgrad:11805
dc.identifier.urihttps://hdl.handle.net/1813/70060
dc.description144 pages
dc.description.abstractThis work looks at low-frequency variability with new tools that give us unprecedented insight into decadal and centennial timescales. First, thermodynamic and dynamic effects of volcanic eruptions on hurricane statistics are examined using two long simulations from the Community Earth System Model (CESM) Last Millennium Ensemble (LME). The first is an unforced control simulation, wherein all boundary conditions were held constant at their 850 CE values. The second is a “fully forced” simulation with time evolving radiative changes from solar, volcanic, solar, and land use changes from 850 through present. The largest magnitude radiative forcings during this time period are the large tropical volcanic eruptions, which comprise the focus of this study. Potential and simulated hurricane statistics are computed from both the control and forced simulations. Potential Intensity is evaluated using model output at its native (nominally 2 degree lat/long) spatial resolution, while the weather research and forecasting (WRF) model is used for dynamically downscaling a total of 100 control years and an additional 100 years following the largest volcanic eruptions in the fully forced simulation. Limitations of the downscaling methodology are examined by applying the same approach to historical ERAI reanalysis data and comparing the downscaled storm tracks and intensities to the IBTrACS database. Results suggest small effects are observed in averages over all last millennium eruptions which are non-significant in comparison tothe control. However, for many of the major eruptions, significant reductions are seen in hurricane frequency, intensity, and lifetime. Strong evidence is also shown for correlation between eruption strength and changes in these diagnostics. Second, we present preliminary efforts to synthesize raw tree-ring data into comprehensive paleoclimate data sets, to detrend this data using a suite of detrending models, and to analyze the resulting chronologies. The methodology developed uses four primary types of detrending models to construct tree-ring chronologies using data from the International Tree Ring Database (ITRDB). The detrending models use varying combinations of splines, negative exponential functions, tree-ring segment length constraints, and variance thresholds. These combinations range from less to more aggressive (i.e. filtering variance and segment length requirements) in constraints on tree-ring segment properties and in preserving low-frequency content. Information encoded in trees reflects a combination of biological effects on long timescales and climate effects on shorter ones. Detrending is necessary to remove these biological effects. Analysis of chronologies is made possible using a combination of multiple-taper spectrum estimation methods (MTM) and principal-components analysis using singular value decomposition (SVD). The MTM-SVD approach is selected in order to overcome the estimation bias inherent in Fourier analysis and because of the large-scale spatial structure of climatic variations. This MTM-SVD analysis provides an approach for signal detection and reconstruction, along with significance assessment. A robust null hypothesis is used to determine significance of signals in the local fractional variance spectrum, derived from the set of singular values. The methodology presented will be used to explore the effect of detrending schemes on climatology extracted from chronologies. It will also be used in future work to quantify the amplitude of low-frequency hydroclimate variability in models, proxies, and observations, while at the same time utilizing an ensemble of last millennium numerical climate models produced by the National Center for Atmospheric Research (NCAR).
dc.language.isoen
dc.subjectClimate variability
dc.subjectHurricanes
dc.subjectTree-rings
dc.subjectVolcanoes
dc.titleAnalysis of Low-Frequency Climate Variability Through Computational Modeling and Tree-Ring Data Synthesis
dc.typedissertation or thesis
thesis.degree.disciplinePhysics
thesis.degree.levelDoctor of Philosophy
thesis.degree.namePh. D., Physics
dc.contributor.chairAult, Toby Rollin
dc.contributor.committeeMemberBodenschatz, Eberhard
dc.contributor.committeeMemberMyers, Christopher
dcterms.licensehttps://hdl.handle.net/1813/59810
dc.identifier.doihttps://doi.org/10.7298/ysk0-qc65


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Statistics