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Automated classification of rainfall...

Baldwin, Michael Eugene.

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Automated classification of rainfall systems using statistical characterization.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Automated classification of rainfall systems using statistical characterization./
Author:	Baldwin, Michael Eugene.
Description:	195 p.
Notes:	Adviser: Frederick H. Carr.
Contained By:	Dissertation Abstracts International64-03B.
Subject:	Geophysics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3085711
ISBN:	9780496335183

Automated classification of rainfall systems using statistical characterization.
Baldwin, Michael Eugene.

Automated classification of rainfall systems using statistical characterization. - 195 p.

Adviser: Frederick H. Carr.

Thesis (Ph.D.)--The University of Oklahoma, 2003.

A general, completely automated procedure for classifying rainfall systems is developed. The technique is flexible and universally applicable, in that any rainfall system can be classified regardless of size, location, time of day or year, degree of organization, etc. The knowledge obtained from previous research was used to develop a relatively straightforward and unique classification system. To test the performance of the method, results were validated against a subjective classification based upon objective criteria. From an independent random sample, the automated classification system accurately placed events into stratiform, linear, and cellular classes 85% of the time.

ISBN: 9780496335183Subjects--Topical Terms:

535228
Geophysics.

Automated classification of rainfall systems using statistical characterization.
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020 $a 9780496335183
035 $a (UMI)AAI3085711
035 $a AAI3085711
040 $a UMI $c UMI
100 1 $a Baldwin, Michael Eugene. $3 1271959
245 1 0 $a Automated classification of rainfall systems using statistical characterization.
300 $a 195 p.
500 $a Adviser: Frederick H. Carr.
500 $a Source: Dissertation Abstracts International, Volume: 64-03, Section: B, page: 1290.
502 $a Thesis (Ph.D.)--The University of Oklahoma, 2003.
520 $a A general, completely automated procedure for classifying rainfall systems is developed. The technique is flexible and universally applicable, in that any rainfall system can be classified regardless of size, location, time of day or year, degree of organization, etc. The knowledge obtained from previous research was used to develop a relatively straightforward and unique classification system. To test the performance of the method, results were validated against a subjective classification based upon objective criteria. From an independent random sample, the automated classification system accurately placed events into stratiform, linear, and cellular classes 85% of the time.
590 $a School code: 0169.
650 4 $a Geophysics. $3 535228
650 4 $a Physics, Atmospheric Science. $3 1019431
690 $a 0373
690 $a 0608
710 2 $a The University of Oklahoma. $3 1021915
773 0 $t Dissertation Abstracts International $g 64-03B.
790 $a 0169
790 1 0 $a Carr, Frederick H., $e advisor
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3085711