solar signal
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2021 ◽  
Vol 21 (1) ◽  
pp. 201-216
Author(s):  
Arseniy Karagodin-Doyennel ◽  
Eugene Rozanov ◽  
Ales Kuchar ◽  
William Ball ◽  
Pavle Arsenovic ◽  
...  

Abstract. Water vapor (H2O) is the source of reactive hydrogen radicals in the middle atmosphere, whereas carbon monoxide (CO), being formed by CO2 photolysis, is suitable as a dynamical tracer. In the mesosphere, both H2O and CO are sensitive to solar irradiance (SI) variability because of their destruction/production by solar radiation. This enables us to analyze the solar signal in both models and observed data. Here, we evaluate the mesospheric H2O and CO response to solar irradiance variability using the Chemistry-Climate Model Initiative (CCMI-1) simulations and satellite observations. We analyzed the results of four CCMI models (CMAM, EMAC-L90MA, SOCOLv3, and CESM1-WACCM 3.5) operated in CCMI reference simulation REF-C1SD in specified dynamics mode, covering the period from 1984–2017. Multiple linear regression analyses show a pronounced and statistically robust response of H2O and CO to solar irradiance variability and to the annual and semiannual cycles. For periods with available satellite data, we compared the simulated solar signal against satellite observations, namely the GOZCARDS composite for 1992–2017 for H2O and Aura/MLS measurements for 2005–2017 for CO. The model results generally agree with observations and reproduce an expected negative and positive correlation for H2O and CO, respectively, with solar irradiance. However, the magnitude of the response and patterns of the solar signal varies among the considered models, indicating differences in the applied chemical reaction and dynamical schemes, including the representation of photolyzes. We suggest that there is no dominating thermospheric influence of solar irradiance in CO, as reported in previous studies, because the response to solar variability is comparable with observations in both low-top and high-top models. We stress the importance of this work for improving our understanding of the current ability and limitations of state-of-the-art models to simulate a solar signal in the chemistry and dynamics of the middle atmosphere.


2020 ◽  
Author(s):  
Arseniy Karagodin-Doyennel ◽  
Eugene Rozanov ◽  
Ales Kuchar ◽  
William Ball ◽  
Pavle Arsenovic ◽  
...  

Abstract. Water vapor (H2O) is the source of reactive hydrogen radicals in the middle atmosphere, whereas carbon monoxide (CO), being formed by CO2 photolysis, is suitable as a dynamical tracer. In the mesosphere, both H2O and CO are sensitive to solar irradiance variability because of their destruction/production by solar radiation. This enables to analyze the solar signal in both, models and observed data. Here, we evaluate the mesospheric H2O and CO response to solar irradiance variability using the Chemistry-Climate Model Initiative (CCMI-1) simulations and satellite data. We analyzed the results of four CCMI models (CMAM, EMAC-L90MA, SOCOLv3, CESM1-WACCM 3.5) operated in CCMI reference simulation REF-C1SD in specified dynamics mode, covering the period from 1984 to 2017. Multiple linear regression analysis shows a pronounced and statistically robust response of H2O and CO to solar irradiance variability, and to the annual and semiannual cycles. For periods with available satellite data, we compared the simulated solar signal against satellite observations, namely during 1992–2017 for H2O and 2005–2017 for CO. The model results generally agree with observations and reproduce an expected negative and positive correlation for H2O and CO, respectively, with solar irradiance. However, the magnitude of the response and patterns of the solar signal varies among the considered models, indicating differences in the applied chemical reaction and dynamical schemes including the representation of photolyses. We suggest that there is no dominating thermospheric influence of solar irradiance in CO, as reported in previous studies because the response to solar variability is comparable with observations in both, low-top and high-top models. We stress the importance of this work for improving our understanding of the current ability and limitations of state-of-the-art models to simulate a solar signal in the chemistry and dynamic of the middle atmosphere.


2020 ◽  
Author(s):  
Markus Kunze ◽  
Tim Kruschke ◽  
Ulrike Langematz ◽  
Miriam Sinnhuber ◽  
Thomas Reddmann ◽  
...  

Abstract. Variations of 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 ANOVA identifies the SSI data set with the strongest influence on the variability of the solar signal in shortwave heating rates in the upper mesosphere and in the upper stratosphere/lower mesosphere. The strongest influence on the variability of the solar signal in ozone and temperature is identified in the upper stratosphere/lower mesosphere. 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.


2018 ◽  
Vol 52 (9-10) ◽  
pp. 5173-5187 ◽  
Author(s):  
Delin Li ◽  
Ziniu Xiao ◽  
Liang Zhao

2018 ◽  
Vol 177 ◽  
pp. 257-265 ◽  
Author(s):  
Lucian Sfîcă ◽  
Iulian Iordache ◽  
Mirela Voiculescu
Keyword(s):  

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