This study is concerned with the intrinsic temporal scales ofthe variability in the surface solar irradiance (SSI). The data consist ofdecennial time series of daily means of the SSI obtained from high-qualitymeasurements of the broadband solar radiation impinging on a horizontal planeat ground level, issued from different Baseline Surface Radiation Network(BSRN) ground stations around the world. First, embedded oscillations sortedin terms of increasing timescales of the data are extracted by empirical modedecomposition (EMD). Next, Hilbert spectral analysis is applied to obtain anamplitude-modulation–frequency-modulation (AM–FM) representation of thedata. The time-varying nature of the characteristic timescales ofvariability, along with the variations in the signal intensity, are thusrevealed. A novel, adaptive null hypothesis based on the general statisticalcharacteristics of noise is employed in order to discriminate between thedifferent features of the data, those that have a deterministic origin andthose being realizations of various stochastic processes. The data have asignificant spectral peak corresponding to the yearly variability cycle andfeature quasi-stochastic high-frequency variability components, irrespectiveof the geographical location or of the local climate. Moreover, the amplitudeof this latter feature is shown to be modulated by variations in the yearlycycle, which is indicative of nonlinear multiplicative cross-scale couplings.The study has possible implications on the modeling and the forecast of thesurface solar radiation, by clearly discriminating the deterministic from thequasi-stochastic character of the data, at different local timescales.
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