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Title: Using Lomb–Scargle Analysis to Derive Empirical Orthogonal Functions from Gappy Meteorological Data

Authors:
 [1];  [2]
  1. Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey
  2. Department of Atmospheric Sciences, Texas A&,M University, College Station, Texas
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1471161
Grant/Contract Number:  
SC0016245
Resource Type:
Published Article
Journal Name:
Journal of Applied Meteorology and Climatology
Additional Journal Information:
Journal Name: Journal of Applied Meteorology and Climatology Journal Volume: 57 Journal Issue: 10; Journal ID: ISSN 1558-8424
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English

Citation Formats

Dupuis, Christopher, and Schumacher, Courtney. Using Lomb–Scargle Analysis to Derive Empirical Orthogonal Functions from Gappy Meteorological Data. United States: N. p., 2018. Web. doi:10.1175/JAMC-D-17-0250.1.
Dupuis, Christopher, & Schumacher, Courtney. Using Lomb–Scargle Analysis to Derive Empirical Orthogonal Functions from Gappy Meteorological Data. United States. doi:10.1175/JAMC-D-17-0250.1.
Dupuis, Christopher, and Schumacher, Courtney. Mon . "Using Lomb–Scargle Analysis to Derive Empirical Orthogonal Functions from Gappy Meteorological Data". United States. doi:10.1175/JAMC-D-17-0250.1.
@article{osti_1471161,
title = {Using Lomb–Scargle Analysis to Derive Empirical Orthogonal Functions from Gappy Meteorological Data},
author = {Dupuis, Christopher and Schumacher, Courtney},
abstractNote = {},
doi = {10.1175/JAMC-D-17-0250.1},
journal = {Journal of Applied Meteorology and Climatology},
number = 10,
volume = 57,
place = {United States},
year = {2018},
month = {10}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1175/JAMC-D-17-0250.1

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