Graduate Thesis Or Dissertation
 

Sudden changes in local mean values demarcate geophysical regimes

Public Deposited

Downloadable Content

Download PDF
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/nz806188s

Descriptions

Attribute NameValues
Creator
Abstract
  • Sudden changes occur where the mean values associated with two adjacent non-overlapping windows of data are anomalously different, and the transition between the window means occurs over a scale that is small relative to the scale of the windows. Positions of sudden changes can be economically retrieved. The sudden change positions demarcate the data in a manner that can be physically interpreted. Associated with this thesis, are data analyses in terms of the scales, positions, and magnitudes of sudden changes in local (window) mean data values. A sudden change ideally includes an anomalously steep small scale gradient that is associated with change on a much larger scale. Preserving this structure when filtering small scale variance requires an adaptive cutoff scale, as constructed in the third study. The filter adapts a local cutoff scale to the scales, locations and relative magnitudes of the local extremes in the Haar transform, which ideally responds to sudden changes. In the fourth study a filter using a variable cutoff scale is applied in order to partition a nine hour time series of wind velocity. The variable cutoff scale filter separated a transport mode from an isotropic small scale mode more cleanly, in terms of traditional statistics, than did a constant cutoff scale filter. Generally, the positions of sudden changes distinguish windows of data. Windows can be centered on the sudden changes or between them. In the fifth study the sudden changes define boundaries of data windows. The within-window data then contains less variance associated with sudden changes, which deterministically occur between adjacent windows. A sampling procedure based on the locations of the sudden changes is applied in the sixth study in an analysis of surface layer measurements. The "non-random" sampling helps to clarify spatial and temporal patterns in samples of the mean wind and the turbulence stress; the "mesoscale effect" is less ambiguous.
Resource Type
Date Available
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Academic Affiliation
Non-Academic Affiliation
Subject
Rights Statement
Publisher
Peer Reviewed
Language
Digitization Specifications
  • File scanned at 300 ppi (Monochrome, 8-bit Grayscale) using ScandAll PRO 1.8.1 on a Fi-6670 in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
Replaces

Relationships

Parents:

This work has no parents.

In Collection:

Items

Thumbnail Title Date Uploaded Visibility Actions
file details HowellJamesF1996.pdf 2017-08-03 Public Download