Degree Type

Dissertation

Date of Award

1993

Degree Name

Doctor of Philosophy

Department

Geological and Atmospheric Sciences

First Advisor

Tsing-Chang Chen

Second Advisor

Herbert T. David

Abstract

This study presents a statistical technique to partition numerical model forecast mean squared error into model deficiency components and components due to random errors in the initial conditions. In addition to the partitioning technique, this study presents a procedure to evaluate if each component's contribution to the total error, in the presence of the residual (unpartitioned) error, is negligible. The application of the partitioning techniques in an operational environment is discussed briefly;The partitioning technique and component evaluation procedure were applied to a hierarchy of global spectral models. The hierarchy consisted of a barotropic model, a "classic" two-layer baroclinic model, an "improved" two-layer baroclinic model, and a two-layer linear balance model. The models were initialized with a sample of data generated with Monte-Carlo techniques; details are presented in an appendix;The application demonstrated the relative ease in which partitioning and evaluations may be applied to model forecasts. From the analyses, the forecast time at which model differences were no longer "negligible", and how this time varied with latitude, was evident. The effectiveness of "incremental" model improvements, represented by the difference between the classical and "improved" baroclinic models were also evaluated and discussed.

DOI

https://doi.org/10.31274/rtd-180813-9609

Publisher

Digital Repository @ Iowa State University, http://lib.dr.iastate.edu/

Copyright Owner

David Giles McDonald

Language

en

Proquest ID

AAI9334999

File Format

application/pdf

File Size

273 pages

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