Abstract

Abstract. At scales much longer than the deterministic predictability limits (about 10 days), the statistics of the atmosphere undergoes a drastic transition, the high-frequency weather acts as a random forcing on the lower-frequency macroweather. In addition, up to decadal and centennial scales the equivalent radiative forcings of solar, volcanic and anthropogenic perturbations are small compared to the mean incoming solar flux. This justifies the common practice of reducing forcings to radiative equivalents (which are assumed to combine linearly), as well as the development of linear stochastic models, including for forecasting at monthly to decadal scales. In order to clarify the validity of the linearity assumption and determine its scale range, we use last millennium simulations, with both the simplified Zebiak–Cane (ZC) model and the NASA GISS E2-R fully coupled GCM. We systematically compare the statistical properties of solar-only, volcanic-only and combined solar and volcanic forcings over the range of timescales from 1 to 1000 years. We also compare the statistics to multiproxy temperature reconstructions. The main findings are (a) that the variability in the ZC and GCM models is too weak at centennial and longer scales; (b) for longer than ≈ 50 years, the solar and volcanic forcings combine subadditively (nonlinearly) compounding the weakness of the response; and (c) the models display another nonlinear effect at shorter timescales: their sensitivities are much higher for weak forcing than for strong forcing (their intermittencies are different) and we quantify this with statistical scaling exponents.

Highlights

  • The general circulation model (GCM) approach to climate modelling is based on the idea that whereas weather is an initial value problem, the climate is a boundary value problem (Bryson, 1997; Pielke, 1998)

  • The importance of volcanic forcings was demonstrated by Minnis et al (1993), who investigated the volcanic radiative forcing caused by the 1991 eruption of Mount Pinatubo, and found that volcanic aerosols produced a strong cooling effect

  • From the point of view of GCMs, climate change is a consequence of changing boundary conditions; the latter are the climate forcings

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Summary

Introduction

The general circulation model (GCM) approach to climate modelling is based on the idea that whereas weather is an initial value problem, the climate is a boundary value problem (Bryson, 1997; Pielke, 1998) This means that the weather’s sensitive dependence on initial conditions (chaos, the “butterfly effect”) leads to a loss of predictability at timescales of about 10 days, averaging over enough “weather” leads to a convergence to the model’s “climate”. These numbers are of the order of 1 % of the mean solar radiative flux; we may anticipate that the atmosphere responds fairly linearly. At long enough scales, linearity clearly breaks down; starting with the celebrated “Daisyworld” model (Watson and Lovelock, 1983), there is a whole body of literature that uses

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