Applications of the cyclic spectral analysis to the surface temperature fluctuations in a stochastic climate model and a gcm simulation

Abstract

In this paper, we introduce the cyclostationary processes into climate analysis and undertake a systematic study of the cyclic spectra of surface temperature fluctuations. The technique is adapted from cyclostationarity theory in signal processing. To demonstrate the usefulness of this technique, a very simple cyclostationary stochastic climate model is constructed. Our results show that the seasonal cycle strongly modulates the amplitudes of the covariance and the spectrum. The technique was also applied to the surface temperature fluctuations in a fifteen-year seasonal run of the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM2, R15) using a zonally symmetric all-land surface as the lower boundary. The results indicate that intraseasonal oscillations localized according to time of year are still present even after the surface temperature fields have been normalized using the commonly used procedure. Both examples suggest that the “annual cycle” cannot be “removed” by simply using a normalization procedure. The climate is not as completely represented when modelled as stationary processes. © 1996 Canadian Meteorological and Oceanographic Society.