Using Lomb-Scargle Analysis to Derive Empirical Orthogonal Functions from Gappy Meteorological Data Academic Article

abstract

• AbstractThe LombScargle discrete Fourier transform (LSDFT) is a well-known technique for analyzing time series. In this study, a solution for empirical orthogonal functions (EOFs) based on irregularly sampled data is derived from the LSDFT. It is demonstrated that this particular algorithm has no hard limit on its accuracy and yields results comparable to those of complex Hilbert EOF analysis. Two LSDFT algorithms are compared in terms of their performance in evaluating EOFs for precipitation observations from the Tropical Rainfall Measuring Mission satellite. Both are shown to be able to capture the pattern of the diurnal cycle of rainfall over the complex topography and diverse land cover of South America, and both also show other consistent features in the 012-day frequency band.

authors

• Schumacher, Courtney

published proceedings

• JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY

author list (cited authors)

• Dupuis, C., & Schumacher, C.

citation count

• 2

complete list of authors

• Dupuis, Christopher||Schumacher, Courtney

publication date

• October 2018

publisher

• American Meteorological Society  Publisher

published in

• Journal of Applied Meteorology and Climatology  Journal

keywords

• Distribution
• Empirical Orthogonal Functions
• Models
• Spectral Analysis
• Time Series

Digital Object Identifier (DOI)

• 10.1175/JAMC-D-17-0250.1

start page

• 2217

end page

• 2229

volume

• 57

issue

• 10

URL

• http://dx.doi.org/10.1175/jamc-d-17-0250.1