Solar Response In Ozone Research Articles

Quantifying uncertainties of climate signals in chemistry climate models related to the 11-year solar cycle – Part 1: Annual mean response in heating rates, temperature, and ozone

Abstract. Variations in the solar spectral irradiance (SSI) with the 11-year sunspot cycle have been shown to have a significant impact on temperatures and the mixing ratios of atmospheric constituents in the stratosphere and mesosphere. Uncertainties in modelling the effects of SSI variations arise from uncertainties in the empirical models reconstructing the prescribed SSI data set as well as from uncertainties in the chemistry–climate model (CCM) formulation. In this study CCM simulations with the ECHAM/MESSy Atmospheric Chemistry (EMAC) model and the Community Earth System Model 1 (CESM1)–Whole Atmosphere Chemistry Climate Model (WACCM) have been performed to quantify the uncertainties of the solar responses in chemistry and dynamics that are due to the usage of five different SSI data sets or the two CCMs. We apply a two-way analysis of variance (ANOVA) to separate the influence of the SSI data sets and the CCMs on the variability of the solar response in shortwave heating rates, temperature, and ozone. The solar response is derived from climatological differences of time slice simulations prescribing SSI for the solar maximum in 1989 and near the solar minimum in 1994. The SSI values for the solar maximum of each SSI data set are created by adding the SSI differences between November 1994 and November 1989 to a common SSI reference spectrum for near-solar-minimum conditions based on ATLAS-3 (Atmospheric Laboratory of Applications and Science-3). The ANOVA identifies the SSI data set with the strongest influence on the variability of the solar response in shortwave heating rates in the upper mesosphere and in the upper stratosphere–lower mesosphere. The strongest influence on the variability of the solar response in ozone and temperature is identified in the upper stratosphere–lower mesosphere. However, in the region of the largest ozone mixing ratio, in the stratosphere from 50 to 10 hPa, the SSI data sets do not contribute much to the variability of the solar response when the Spectral And Total Irradiance REconstructions-T (SATIRE-T) SSI data set is omitted. The largest influence of the CCMs on variability of the solar responses can be identified in the upper mesosphere. The solar response in the lower stratosphere also depends on the CCM used, especially in the tropics and northern hemispheric subtropics and mid-latitudes, where the model dynamics modulate the solar responses. Apart from the upper mesosphere, there are also regions where the largest fraction of the variability of the solar response is explained by randomness, especially for the solar response in temperature.

The representation of solar cycle signals in stratospheric ozone – Part 1: A comparison of recently updated satellite observations

Abstract. Changes in incoming solar ultraviolet radiation over the 11-year solar cycle affect stratospheric ozone abundances. It is important to quantify the magnitude, structure, and seasonality of the associated solar-ozone response (SOR) to understand the impact of the 11-year solar cycle on climate. Part 1 of this two-part study uses multiple linear regression analysis to extract the SOR in a number of recently updated satellite ozone datasets covering different periods within the epoch 1970 to 2013. The annual mean SOR in the updated version 7.0 (v7.0) Stratospheric Aerosol and Gas Experiment (SAGE) II number density dataset (1984–2004) is very consistent with that found in the previous v6.2. In contrast, we find a substantial decrease in the magnitude of the SOR in the tropical upper stratosphere in the SAGE II v7.0 mixing ratio dataset (∼ 1 %) compared to the v6.2 (∼ 4 %). This difference is shown to be largely attributable to the change in the independent stratospheric temperature dataset used to convert SAGE II ozone number densities to mixing ratios. Since these temperature records contain substantial uncertainties, we suggest that datasets based on SAGE II number densities are currently most reliable for evaluating the SOR. We further analyse three extended ozone datasets that combine SAGE II v7.0 number densities with more recent GOMOS (Global Ozone Monitoring by Occultation of Stars) or OSIRIS (Optical Spectrograph and Infrared Imager System) measurements. The extended SAGE–OSIRIS dataset (1984–2013) shows a smaller and less statistically significant SOR across much of the tropical upper stratosphere compared to the SAGE II data alone. In contrast, the two SAGE–GOMOS datasets (1984–2011) show SORs that are in closer agreement with the original SAGE II data and therefore appear to provide a more reliable estimate of the SOR. We also analyse the SOR in the recent Solar Backscatter Ultraviolet Instrument (SBUV) Merged Ozone Dataset (SBUVMOD) version 8.6 (VN8.6) (1970–2012) and SBUV Merged Cohesive VN8.6 (1978–2012) datasets and compare them to the previous SBUVMOD VN8.0 (1970–2009). Over their full lengths, the three records generally agree in terms of the broad magnitude and structure of the annual mean SOR. The main difference is that SBUVMOD VN8.6 shows a smaller and less significant SOR in the tropical upper stratosphere and therefore more closely resembles the SAGE II v7.0 mixing ratio data than does the SBUV Merged Cohesive VN8.6, which has a more continuous SOR of ∼ 2 % in this region. The sparse spatial and temporal sampling of limb satellite instruments prohibits the extraction of sub-annual variations in the SOR from SAGE-based datasets. However, the SBUVMOD VN8.6 dataset suggests substantial month-to-month variations in the SOR, particularly in the winter extratropics, which may be important for the proposed high-latitude dynamical response to the solar cycle. Overall, the results highlight substantial uncertainties in the magnitude and structure of the observed SOR from different satellite records. The implications of these uncertainties for understanding and modelling the effects of solar variability on climate should be explored.

Direct and indirect effects of solar variations on stratospheric ozone and temperature

We have used a fully coupled chemistry-climate model (WACCM) to investigate the relative importance of the direct and indirect effects of 11a solar variations on stratospheric temperature and ozone. Although the model does not contain a quasi-biennial oscillation (QBO) and uses fixed sea surface temperature (SST), it is able to produce a second maximum solar response in tropical lower stratospheric (TLS) temperature and ozone of approximately 0.5 K and 3%, respectively. In the TLS, the solar spectral variations in the chemistry scheme play a more important role than solar spectral variations in the radiation scheme in generating temperature and ozone responses. The chemistry effect of solar variations causes significant changes in the Brewer-Dobson (BD) circulation resulting in ozone anomalies in the TLS. The model simulations also show a negative feedback in the upper stratosphere between the temperature and ozone responses. A wavelet analysis of the modeled ozone and temperature time series reveals that the maximum solar responses in ozone and temperature caused by both chemical and radiative effects occur at different altitudes in the upper stratosphere. The analysis also confirms that both the direct radiative and indirect ozone feedback effects are important in generating a solar response in the upper stratospheric temperatures, although the solar spectral variations in the chemistry scheme give the largest solar cycle power in the upper stratospheric temperature.

Solar response in tropical stratospheric ozone: a 3-D chemical transport model study using ERA reanalyses

Abstract. We have used an off-line 3-D chemical transport model (CTM) to investigate the 11-yr solar cycle response in tropical stratospheric ozone. The model is forced with European Centre for Medium-Range Weather Forecasts (ECMWF) (re)analysis (ERA-40/operational and ERA-Interim) data for the 1979–2005 time period. We have compared the modelled solar response in ozone to observation-based data sets that are constructed using satellite instruments such as Total Ozone Mapping Spectrometer (TOMS), Solar Backscatter UltraViolet instrument (SBUV), Stratospheric Aerosol and Gas Experiment (SAGE) and Halogen Occultation Experiment (HALOE). A significant difference is seen between simulated and observed ozone during the 1980s, which is probably due to inhomogeneities in the ERA-40 reanalyses. In general, the model with ERA-Interim dynamics shows better agreement with the observations from 1990 onwards than with ERA-40. Overall both standard model simulations are partially able to simulate a "double peak"-structured ozone solar response with a minimum around 30 km, and these are in better agreement with HALOE than SAGE-corrected SBUV (SBUV/SAGE) or SAGE-based data sets. In the tropical lower stratosphere (TLS), the modelled solar response with time-varying aerosols is amplified through aliasing with a volcanic signal, as the model overestimates ozone loss during high aerosol loading years. However, the modelled solar response with fixed dynamics and constant aerosols shows a positive signal which is in better agreement with SBUV/SAGE and SAGE-based data sets in the TLS. Our model simulations suggests that photochemistry contributes to the ozone solar response in this region. The largest model-observation differences occur in the upper stratosphere where SBUV/SAGE and SAGE-based data show a significant (up to 4%) solar response whereas the standard model and HALOE do not. This is partly due to a positive solar response in the ECMWF upper stratospheric temperatures which reduces the modelled ozone signal. The large positive upper stratospheric solar response seen in SBUV/SAGE and SAGE-based data can be reproduced in model runs with fixed dynamical fields (i.e. no inter-annual meteorological changes). As these runs effectively assume no long-term temperature changes (solar-induced or otherwise), it should provide an upper limit of the ozone solar response. Overall, full quantification of the solar response in stratospheric ozone is limited by differences in the observed data sets and by uncertainties in the solar response in stratospheric temperatures.