The role of stratospheric ozone in modulating the solar radiative forcing of climate

Haigh, Joanna D.

doi:10.1038/370544a0

Cited by 403 publications

(352 citation statements)

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“…Rozanov et al, 2002), 2-D models (e.g. Haigh, 1994) and CCMs (e.g. Shindell et al, 1999;Tourpali et al, 2003;Egorova et al, 2004;Rozanov et al, 2004).…”

Section: Results From Simulations With Constant Solar Irradiancementioning

confidence: 99%

A simple framework for modelling the photochemical response to solar spectral irradiance variability in the stratosphere

et al. 2012

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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 determinationR 2 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 (R 2 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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“…Rozanov et al, 2002), 2-D models (e.g. Haigh, 1994) and CCMs (e.g. Shindell et al, 1999;Tourpali et al, 2003;Egorova et al, 2004;Rozanov et al, 2004).…”

Section: Results From Simulations With Constant Solar Irradiancementioning

confidence: 99%

A simple framework for modelling the photochemical response to solar spectral irradiance variability in the stratosphere

et al. 2012

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“…The climate response to solar variability depends not only on the "direct" impact of changes in TSI and SSI on atmospheric and surface heating rates, but also on the "indirect" effects on stratospheric and mesospheric ozone abundances (e.g., Haigh, 1994). In some regions, the associated solar-ozone response can contribute to more than 50 % of the change in stratospheric heating rates between solar-cycle minimum and maximum (Shibata and Kodera, 2005;Gray et al, 2009).…”

Section: Solar-cycle Signal In Stratospheric Ozonementioning

confidence: 99%

“…Whereas relative TSI variations in the 11-year solar cycle are small, about 0.1 %, SSI changes are wavelength-dependent, and may vary by up to 10 % at 200 nm in the ultraviolet (UV) wavelength range (Lean, 1997). Variations in UV radiation over the solar cycle have significant impacts on the radiative heating and ozone budget of the middle atmosphere (Haigh, 1994).…”

Section: Introductionmentioning

confidence: 99%

Solar forcing for CMIP6 (v3.2)

et al. 2017

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Abstract. This paper describes the recommended solar forcing dataset for CMIP6 and highlights changes with respect to CMIP5. The solar forcing is provided for radiative properties, namely total solar irradiance (TSI), solar spectral irradiance (SSI), and the F10.7 index as well as particle forcing, including geomagnetic indices Ap and Kp, and ionization rates to account for effects of solar protons, electrons, and galactic cosmic rays. This is the first time that a recommendation for solar-driven particle forcing has been provided for a CMIP exercise. The solar forcing datasets are provided at daily and monthly resolution separately for the CMIP6 preindustrial control, historical (1850CMIP6 preindustrial control, historical ( -2014, and future (2015-2300) simulations. For the preindustrial control simulation, both constant and time-varying solar forcing components are provided, with the latter including variability on 11-year and shorter timescales but no long-term changes. For the future, we provide a realistic scenario of what solar behavior could be, as well as an additional extreme Maunderminimum-like sensitivity scenario. This paper describes the forcing datasets and also provides detailed recommendations as to their implementation in current climate models.For the historical simulations, the TSI and SSI time series are defined as the average of two solar irradiance models that are adapted to CMIP6 needs: an empirical onePublished by Copernicus Publications on behalf of the European Geosciences Union. A new and lower TSI value is recommended: the contemporary solar-cycle average is now 1361.0 W m −2 . The slight negative trend in TSI over the three most recent solar cycles in the CMIP6 dataset leads to only a small global radiative forcing of −0.04 W m −2 . In the 200-400 nm wavelength range, which is important for ozone photochemistry, the CMIP6 solar forcing dataset shows a larger solar-cycle variability contribution to TSI than in CMIP5 (50 % compared to 35 %).We compare the climatic effects of the CMIP6 solar forcing dataset to its CMIP5 predecessor by using timeslice experiments of two chemistry-climate models and a reference radiative transfer model. The differences in the long-term mean SSI in the CMIP6 dataset, compared to CMIP5, impact on climatological stratospheric conditions (lower shortwave heating rates of −0.35 K day −1 at the stratopause), cooler stratospheric temperatures (−1.5 K in the upper stratosphere), lower ozone abundances in the lower stratosphere (−3 %), and higher ozone abundances (+1.5 % in the upper stratosphere and lower mesosphere). Between the maximum and minimum phases of the 11-year solar cycle, there is an increase in shortwave heating rates (+0.2 K day −1 at the stratopause), temperatures (∼ 1 K at the stratopause), and ozone (+2.5 % in the upper stratosphere) in the tropical upper stratosphere using the CMIP6 forcing dataset. This solar-cycle response is slightly larger, but not statistically significantly different from that for the CMIP5 forcing dataset.CMIP6 models wi...

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“…Note, however, that the strong, two-way coupling across the tropopause means that the appearance of the change first in the stratosphere is not necessarily an indication that the stratospheric changes are driving those in the troposphere. The latitudes of tropospheric jet streams have been shown to be sensitive to the solar forcing of stratospheric temperatures (Haigh 1994(Haigh , 2003Poore et al 2004). This could occur through disturbances to the stratospheric polar vortex (Gray et al 2004), which can propagate downwards to affect the tropospheric jets (Plumb and Semeniuk 2003) or through the effects of stratospheric temperature changes on stratospheric winds and the refraction of tropospheric eddies (Kushner and Polvani 2004;Simpson et al 2009).…”

Section: ''Top-down'' Solar Forcingmentioning

confidence: 99%

Solar Influence on Global and Regional Climates

Lockwood

2012

Surv Geophys

148

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The literature relevant to how solar variability influences climate is vast-but much has been based on inadequate statistics and non-robust procedures. The common pitfalls are outlined in this review. The best estimates of the solar influence on the global mean air surface temperature show relatively small effects, compared with the response to anthropogenic changes (and broadly in line with their respective radiative forcings). However, the situation is more interesting when one looks at regional and season variations around the global means. In particular, recent research indicates that winters in Eurasia may have some dependence on the Sun, with more cold winters occurring when the solar activity is low. Advances in modelling ''top-down'' mechanisms, whereby stratospheric changes influence the underlying troposphere, offer promising explanations of the observed phenomena. In contrast, the suggested modulation of low-altitude clouds by galactic cosmic rays provides an increasingly inadequate explanation of observations.

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The role of stratospheric ozone in modulating the solar radiative forcing of climate

Cited by 403 publications

References 28 publications

A simple framework for modelling the photochemical response to solar spectral irradiance variability in the stratosphere

A simple framework for modelling the photochemical response to solar spectral irradiance variability in the stratosphere

Solar forcing for CMIP6 (v3.2)

Solar Influence on Global and Regional Climates

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