Autoregressive modeling for the spectral analysis of oceanographic data
Date of Original Version
Over the last decade there has been a dramatic increase in the number and volume of data sets useful for oceanographic studies. Many of these data sets consist of long temporal or spatial series derived from satellites and large-scale oceanographic experiments. These data sets are, however, often "gappy' in space, irregular in time, and always of finite length. The conventional Fourier transform (FT) approach to the spectral analysis is thus often inapplicable, or where applicable, it provides questionable results. Here, through comparative analysis with the FT for different oceanographic data sets, we discuss the possibilities offered by autoregressive (AR) modeling to perform spectral analysis of gappy, finite-length series. -from Authors
Publication Title, e.g., Journal
Journal of Geophysical Research
Gangopadhyay, A., P. Cornillon, and L. B. Jackson. "Autoregressive modeling for the spectral analysis of oceanographic data." Journal of Geophysical Research 94, C11 (1989). doi: 10.1029/jc094ic11p16215.