Modelling the effects of (short-term) solar variability on stratospheric chemistry

The photochemical response of the stratosphere to short-term solar variability is investigated using a photochemistry column model with interactive photolysis calculation. The solar variability is here simply represented using the Lean (1997) solar minimum and maximum spectra. In order to isolate the photochemistry effect, simulations are devoid of diffusion or any other external forcing and the temperature is held constant. The solar mininum/maximum response is estimated for all chemical families and partitioning ratios, and the underlying photochemical mechanisms are described in detail. The ozone response peaks at 0.18 ppmv (approximatively 3%) at 37 km altitude. In an attempt to find the simplest statistical model able to represent the effect of solar variability in the stratosphere, the diurnal-average response of ozone from an ensemble of 200 simulations is regressed linearly following two auto-regressive 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 skills of the two auto-regressive models at representing the effect of solar variability are then evaluated independently when coupled either on-line or off-line with the comprehensive photochemistry column model driven by the solar average spectrum. In all cases, the magnitude of the bias and the RMS error are found smaller than 5% and 20% of the ozone response, respectively. When used on-line, the 3-predictor model captures the ozone response to solar variability throughout the stratosphere with bias and RMS error lower than 1% and 15% of the ozone response, respectively. The results are found to be insensitive to an increase in the magnitude of the solar variability by a factor three, when this increase is applied uniformly throughout the solar spectrum. These statistical models offer accurate, computationally inexpensive parameterisations of the effect of solar variability in the stratosphere for climate-chemistry models with simplified chemistry that can be driven by any solar variability index. Finally, the statistical approach introduced here, based on ensemble photochemical simulations, provides an effective gauge to measure the effects of using more realistic solar variability spectra on the ozone response.