The role of the solar irradiance variability in the evolution of the middle atmosphere during 2004–2009. Issue 9 (8th May 2013)

• Record Type: Journal Article
• Authors: Shapiro, A. V.; Rozanov, E. V.; Shapiro, A. I.; Egorova, T. A.; Harder, J.; Weber, M.; Smith, A. K.; Schmutz, W.; Peter, T.
• Is Part Of: Journal of geophysical research. Volume 118:Issue 9(2013:Sep.)
• Page Start: 3781
• Page End: 3793
• Publication Date: 2013-05-08
• Subjects: SSI variability -- middle atmosphere -- modeling -- observations; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1002/jgrd.50208
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: [1] Recent measurements by the Spectral Irradiance Monitor (SIM) and the Solar Stellar Irradiance Comparison Experiment (SOLSTICE) onboard the Solar Radiation and Climate Experiment satellite have revealed the spectral solar irradiance (SSI) changes in the ultraviolet between 2004 and 2009 to be several times higher than it was shown by all previous SSI measurements and reconstructions. In this paper, we simulate the O3, OH, and temperature responses to solar irradiance variability using four different SSI data sets trying to define which one gives the best agreement between the simulated and observed responses. First, we apply the 1‐D radiative‐convective model with interactive photochemistry to determine the regions of the atmosphere where the O3, OH, and temperature are most sensitive to the spectrum discrepancies between the different SSI data sets. As the comparison with observations can be only made taking into account dynamics and all known forcings of the atmosphere, we then apply the 3‐D chemistry‐climate model SOCOL to simulate the atmosphere evolution from May 2004 to February 2009. We compare the modeled OH, O3, and temperature changes with atmospheric data measured by several space instruments. Overall, the comparison shows that the atmospheric changes simulated with the 3‐D SOCOL model driven by the SIM and SOLSTICE SSI are closest to the atmospheric measurements. Key Points: We found the most sensitive to the SSI discrepancy atmospheric regions. The 3D model with various forcings is used to simulate the atmospheric evolution The simulated responses are confronted with the atmospheric observations.