Abstract
Abstract. The stratosphere is thought to play a central role in the atmospheric response to solar irradiance variability. Recent observations suggest that the spectral solar irradiance (SSI) variability involves significant time-dependent spectral variations, with variable degrees of correlation between wavelengths, and new reconstructions are being developed. In this paper, we propose a simplified modelling framework to characterise the effect of short term SSI variability on stratospheric ozone. We focus on the pure photochemical effect, for it is the best constrained one. The photochemical effect is characterised using an ensemble simulation approach with multiple linear regression analysis. A photochemical column model is used with interactive photolysis for this purpose. Regression models and their coefficients provide a characterisation of the stratospheric ozone response to SSI variability and will allow future inter-comparisons between different SSI reconstructions. As a first step in this study, and to allow comparison with past studies, we take the representation of SSI variability from the Lean (1997) solar minimum and maximum spectra. First, solar maximum-minimum response is analysed for all chemical families and partitioning ratios, and is compared with past studies. The ozone response peaks at 0.18 ppmv (approximately 3%) at 37 km altitude. Second, ensemble simulations are regressed following two linear models. In the simplest case, an adjusted coefficient of determination R2 larger than 0.97 is found throughout the stratosphere using two predictors, namely the previous day's ozone perturbation and the current day's solar irradiance perturbation. A better accuracy (R2 larger than 0.9992) is achieved with an additional predictor, the previous day's solar irradiance perturbation. The regression models also provide simple parameterisations of the ozone perturbation due to SSI variability. Their skills as proxy models are evaluated independently against the photochemistry column model. The bias and RMS error of the best regression model are found smaller than 1% and 15% of the ozone response, respectively. Sensitivities to initial conditions and to magnitude of the SSI variability are also discussed.
Highlights
Solar variability has gained much attention over the past decade for its potential effect on the Earth climate and as a natural modulator of anthropogenic climate change
We limit the study to the pre-defined solar maximum and minimum spectra from Lean (1997) and assume that the spectral solar irradiance (SSI) follows a linear wavelength time variability between these two spectra. This allows comparison with previous studies in the context of constant solar maximum/minimum simulations. This first application of this simplified modelling framework presented in this paper provides a reference for further studies that will apply this framework to more advanced SSI variability reconstructions
Haigh et al (2010) showed that observed spectra from the Spectral Irradiance Monitor (SIM) and the Solar Stellar irradiance Comparison Experiment (SOLSTICE) instruments on satellite Solar Radiation and Climate Experiment (SORCE) (Harder et al, 2005) differ very significantly from the Lean (1997) spectra for the period 2004 to 2007, with variability larger by factors of four to six in the range 200 to 400 nm, and an inversed variability between 400 and 700 nm. It is beyond the scope of this paper to apply the method developed here to these new observations, we present additional experiments that illustrate the sensitivity of the ozone response to differences in the SSI variability pattern
Summary
Solar variability has gained much attention over the past decade for its potential effect on the Earth climate and as a natural modulator of anthropogenic climate change. In order to simulate the pure photochemical response, the chemistry is left to evolve alone with time as an initial condition problem, without any external sources/sinks nor any diffusion/advection representation This imposes a transient chemistry approach with a limit to the duration of the numerical experiments of about ten days This allows comparison with previous studies in the context of constant solar maximum/minimum simulations This first application of this simplified modelling framework presented in this paper provides a reference for further studies that will apply this framework to more advanced SSI variability reconstructions. It includes regression analyses with two and three predictors, the sensitivity to initial conditions, the independent evaluation of the regression models, and its sensitivity to the amplitude of solar variability.
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