Creation of a composite solar ultraviolet irradiance data set

DeLand, Matthew T.; Cebula, R. P.

doi:10.1029/2008ja013401

Cited by 66 publications

(77 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Comparisons with the three-component model of Woods et aI. (2000) give consistent results where these models overlap, as discussed by DeLand and Cebula (2008). (Criscuoli et aI., 2010).…”

Section: Short-term Variationssupporting

confidence: 61%

“…Significant data sets available from these measurements include Solar Mesosphere Explorer (SME) (Rottman, 1988), Solar Backscatter Ultraviolet spectrometer (SBUV) (DeLand and Cebula, 2001), NOAA-9 SBUV model 2 (SBUV/2) (DeLand et aI., 2004), NOAA-II SBUV/2 (DeLand and , Shuttle SBUV (SSBUV) (Cebula et aI., 1996), Upper Atmosphere Research Satellite (UARS) Solar Ultraviolet Spectral Irradiance Monitor (SUSIM) (Floyd et aI., 2003), and UARS Solar Stellar Irradiance Comparisou Experiment (SOLSTICE) (Rottman et aI., 2001). Additional historical infonnation about many of these measurements is given in DeLand and Cebula (2008).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Solar UV variations during the decline of Cycle 23

DeLand

Cebula

2012

Journal of Atmospheric and Solar-Terrestrial Physics

Self Cite

View full text Add to dashboard Cite

change in solar physics. Our analysis of short-tenn solar variability is much less sensitive to residual instrument response changes than the observations of long-term variations. The SORCE long-term UV results can be explained by undercorrection of instrument response changes during the first few years of measurements, rather than requiring an unexpected change in the physical behavior of the Sun.

show abstract

“…Comparisons with the three-component model of Woods et aI. (2000) give consistent results where these models overlap, as discussed by DeLand and Cebula (2008). (Criscuoli et aI., 2010).…”

Section: Short-term Variationssupporting

confidence: 61%

Section: Introductionmentioning

confidence: 99%

Solar UV variations during the decline of Cycle 23

DeLand

Cebula

2012

Journal of Atmospheric and Solar-Terrestrial Physics

Self Cite

View full text Add to dashboard Cite

show abstract

“…If confirmed, this is a considerable change in our understanding in spectral irradiance variability as it means that TSI change is predominantly caused by UV changes and that the changes at IR/Visible wavelengths are actually in the opposite direction to those in the UV and TSI. This contrasts sharply with previous models in which the waveform of temporal variations was taken to be similar at all wavelengths (Lean 2000;DeLand and Cebula 2008;Krivova et al 2009). At present, there is no consensus as to how these new results should be used and incorporated into models.…”

Section: Paleoclimate Studies and Solar Proxiescontrasting

confidence: 52%

Solar Influence on Global and Regional Climates

Lockwood

2012

Surv Geophys

148

View full text Add to dashboard Cite

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.

show abstract

“…Evaluation against solar observations is possible with some acceptable reliability for recent times (from 1978 on, e.g. DeLand and Cebula, 2008). An alternative approach is to evaluate the reconstructed/modelled SSI time series from the perspective of their effects on the stratosphere (e.g.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2012

View full text Add to dashboard Cite

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.

show abstract

Creation of a composite solar ultraviolet irradiance data set

Cited by 66 publications

References 35 publications

Solar UV variations during the decline of Cycle 23

Solar UV variations during the decline of Cycle 23

Solar Influence on Global and Regional Climates

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

Contact Info

Product

Resources

About