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| Titel |
A simple framework for modelling the photochemical response to solar spectral irradiance variability in the stratosphere |
| VerfasserIn |
R. Muncaster, M. S. Bourqui, S. Chabrillat, S. Viscardy, S. M. L. Melo, P. Charbonneau |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 12, no. 16 ; Nr. 12, no. 16 (2012-08-23), S.7707-7724 |
| Datensatznummer |
250011411
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| Publikation (Nr.) |
 copernicus.org/acp-12-7707-2012.pdf |
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| Zusammenfassung |
| 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. |
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