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Parameter estimation in a stochastic model of ocean currents

ScholarsArchive at Oregon State University

Field Value
Title Parameter estimation in a stochastic model of ocean currents
Names Burnett, Thomas Danforth (creator)
Guthrie, Donald Jr. (advisor)
Date Issued 1964-05-15 (iso8601)
Note Graduation date: 1964
Abstract In 1962 a large amount of data was collected in an effort to
establish the existence of subsurface ocean currents off the coast of
Oregon. The presence of several phenomena, including tides and
measurement errors not directly associated with the hypothetical
currents, complicates the interpretation of the data and the estimation
of current velocities.
This thesis advances a stochastic model to represent the
sources of the data, and discusses alternative procedures for the
estimation of parameters in the model.
The local motion of a small volume of water is, in the first
approximation, assumed a sum of a linear drift current plus a
periodic tidal current. The motion of any given particle of water is
then a sum of the above mentioned currents plus a random motion
due to the characteristic turbulence of the ocean's waters. This
random motion is shown similar to Brownian motion or more
specifically the motion of the Wiener process.
From the properties of the Wiener process the joint probability
distribution of the observed displacements of the parachute drogue is
found to be Normal with a given variance-covariance structure.
By suitable linear transformation of the observed displacements,
a new set of independent random variables may be obtained,
where the variances due to random motion and measurement inaccuracies
are combined in a known manner to form variances of the
new set.
A Maximum Likelihood procedure for estimating the mean
velocity of the currents is proposed, and shown to coincide with the
methods of Least Squares in certain special cases.
Genre Thesis/Dissertation
Topic Oceanography -- Statistics
Identifier http://hdl.handle.net/1957/48619

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