Main Title |
Temporal Signatures of Air Quality Observations and Model Outputs: Do Time Series Decomposition Methods Capture Relevant Time Scales. |
Author |
Porter, P.S. ;
Swall, J. ;
Gilliam, R. ;
Gego, E. L. ;
Hogrefe, C. ;
|
CORP Author |
Environmental Protection Agency, Research Triangle Park, NC. National Exposure Research Lab. ;National Oceanic and Atmospheric Administration, Research Triangle Park, NC. Atmospheric Sciences Modeling Div. ;State Univ. of New York at Albany. |
Publisher |
2004 |
Year Published |
2004 |
Report Number |
EPA/600/A-04/110 ;NERL-RTP-AMD-04-086; |
Stock Number |
PB2005-101228 |
Additional Subjects |
Air quality ;
Meteorology ;
Time series analysis ;
Decomposition ;
Performance ;
Numerical analysis ;
Time scales
|
Holdings |
Library |
Call Number |
Additional Info |
Location |
Last Modified |
Checkout Status |
NTIS |
PB2005-101228 |
Some EPA libraries have a fiche copy filed under the call number shown. |
|
07/26/2022 |
|
Collation |
10p |
Abstract |
Time series decomposition methods were applied to meteorological and air quality data and their numerical model estimates. Decomposition techniques express a time series as the sum of a small number of independent modes which hypothetically represent identifiable forcings, thereby helping to untangle complex processes. Mode-to-mode comparison of observed and modeled data provides a mechanism for model evaluation. The decomposition methods included empirical orthogonal functions (EOF), empirical mode decomposition (EMD), and wavelet filters (WF). EOF, a linear method designed for stationary time series, is principal component analysis (PCA) applied to time-lagged copies of a given time series. EMD is a relatively new nonlinear method that operates locally in time and is suitable for nonstationary and nonlinear processes; it is not, in theory, bandwidth limited, and the number of modes is automatically determined. Wavelet filters are linear and band-width guided with the number of modes set by the analyst. The purpose of this paper is to compare the performance of decomposition techniques in characterizing time scales in meteorological and air quality variables. Aiding this comparison is an analysis of simulated time series that have features in common with observations. |
Supplementary Notes |
Prepared in cooperation with National Oceanic and Atmospheric Administration, Research Triangle Park, NC. Atmospheric Sciences Modeling Div. and State Univ. of New York at Albany. |
Availability Notes |
Also available on CD-ROM. Product reproduced from digital image. Order this product from NTIS by: phone at 1-800-553-NTIS (U.S. customers); (703)605-6000 (other countries); fax at (703)605-6900; and email at orders@ntis.gov. NTIS is located at 5285 Port Royal Road, Springfield, VA, 22161, USA. |
Highlights Notes |
%AUT:A. /Gilliland ;J. S. /Irwin |
Category Codes |
55C; 68A |
NTIS Prices |
PC A02/MF A01 |
Document Type |
NT |
Cataloging Source |
NTIS/MT |
Control Number |
001801030 |
Origin |
NTIS |
Type |
CAT |