Abstract
The statistical characteristics of the atmospheric internal variability (hereafter internal atmospheric noise) for surface pressure (PS) in twentieth century simulations of a coupled general circulation model are documented. The atmospheric noise is determined from daily post-industrial (1871–1998) Community Climate System Model 3 simulations by removing the SST and externally forced responses from the total fields. The forced responses are found from atmosphere-only simulations forced by the SST and external forcing of the coupled runs. However, we do not address the influence of the SST variability on the synoptic scale high frequency weather noise.The spatial patterns of the main seasonal modes of atmospheric noise variability are found for boreal winter and summer from empirical orthogonal function analyses performed globally and for various regions, including the North Atlantic, the North Pacific, and the equatorial Pacific. The temporal characteristics of the modes are illustrated by power spectra and probability density functions (PDF) of the principal components (PC). Our findings show that, for two different realizations of noise, the variability is dominated by large scale spatial structures of the atmospheric noise that resemble observed patterns, and that their relative amplitudes in the CGCM and AGCM simulations are very similar. The regional expression of the dominant global mode, a seasonally dependent AO-like or AAO-like pattern is also found in the regional analyses, with similar time dependence. The PCs in the CGCM and the corresponding SST forced AGCM simulations are uncorrelated, but the spectra and PDFs of the CGCM and AGCM PCs are similar.The temporal structures of the noise PCs are white at timescales larger than few months, so that these modes can be thought of as stochastic forcings (in time) for the climate system. The PDFs of the noise PCs are not statistically distinguishable from Gaussian distributions with the same standard deviation. The PDFs do not change substantially between the first and second half of the twentieth century.
Highlights
IntroductionAn important role for intrinsic atmospheric noise (equivalently “noise” or “atmospheric noise” in the following) in forcing climate variability, and in particular, SST variability, was proposed by Hasselmann (1976)
An important role for intrinsic atmospheric noise in forcing climate variability, and in particular, SST variability, was proposed by Hasselmann (1976)
The paper addressed three main questions about the internal atmospheric noise occurring in twentieth century CGCM simulations: (1) What are the spatial characteristics of the noise; (2) What are its temporal characteristics, and in particular can it be represented by a stochastic process; (3) How do the noise characteristics change as climate changes
Summary
An important role for intrinsic atmospheric noise (equivalently “noise” or “atmospheric noise” in the following) in forcing climate variability, and in particular, SST variability, was proposed by Hasselmann (1976). Hasselmann’s single-point model represented forcing of SST by atmospheric noise as a specified white noise heat flux. The model solutions demonstrate that the large heat capacity of the ocean filters out the high frequencies, leading to a red noise SST response for intermediate frequencies and a white noise response for low frequencies that resembles the spectrum of observed SST variability. Where T represents the temperature of a slab mixed layer ocean of depth H, density ρ, and heat capacity c. The atmosphere is represented by the forcing N, and linear damping of T with coefficient.
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