PERIODIC CORRELATION IN STRATOSPHERIC OZONE DATA

Peter Bloomfield, Harry L. Hurd and Robert B. Lund

Journal of Time Series Analysis, 1994, vol. 15, issue 2, 127-150

Abstract: Abstract. A 50‐year time series of monthly stratospheric ozone readings from Arosa, Switzerland, is analyzed. The time series exhibits the properties of a periodically correlated (PC) random sequence with annual periodicities. Spectral properties of PC random sequences are reviewed and a test to detect periodic correlation is presented. An autoregressive moving‐average (ARMA) model with periodically varying coefficients (PARMA) is fitted to the data in two stages. First, a periodic autoregressive model is fitted to the data. This fit yields residuals that are stationary but non‐white. Next, a stationary ARMA model is fitted to the residuals and the two models are combined to produce a larger model for the data. The combined model is shown to be a PARMA model and yields residuals that have the correlation properties of white noise.

Date: 1994
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jtsera:v:15:y:1994:i:2:p:127-150

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