Extreme climate events may be defined as atmospheric or oceanic phenomena that occupy the tails of a dataset's probability density function (PDF), where the magnitude of the event is large, but the probability of occurrence is rare. Though these types of events are statistically sparse, it is necessary to understand the distribution of events in the tails, as quantifying the likelihood of climate extremes is an important step in predicting overall climate variability. It has been known for some time that the PDFs of atmospheric phenomena are decidedly non-Gaussian, though the shape of PDF has not been specified explicitly. More recently, it has been shown from observations that many atmospheric variables follow a power law distribution in the tails. This is in agreement with stochastic theory, which asserts that power law distributions should exist in the tails. However, a statistically rigorous study of the resulting power law distributions has not yet been performed. To show the relationship systematically, we examine the PDF tails of dynamically significant atmospheric variables (such as geopotential height and relative vorticity) for evidence of power law behavior. This is achieved by using statistical algorithms that test PDFs for the bounds and magnitude of power law distributions, while estimating the statistical significance of the distribution compared with Gaussianity. Examples of power law distributions in the atmosphere are presented using local time series of atmospheric data.
|Commitee:||Ellingson, Robert, Wu, Zhaohua|
|School:||The Florida State University|
|Department:||Earth, Ocean & Atmospheric Science|
|School Location:||United States -- Florida|
|Source:||MAI 51/01M(E), Masters Abstracts International|
|Subjects:||Statistics, Meteorology, Atmospheric sciences|
|Keywords:||Climate dynamics, Climate variability, Extreme events, Non-Gaussian, Power law, Stochastic|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be