Investigation of solar induced climate variability in chemistry-climate model simulations

太阳引起的气候变化是自然气候变化的重要组成部分，可以在大气化学和动力学参数中检测到。驱动这一大气太阳信号的物理过程涉及太阳光谱辐照度(SSI)、太阳总辐照度(TSI)以及在高地磁纬度向热层和中间层沉淀的高能粒子(EPP)的变化。虽然太阳信号的强度在大气层的上部很大，在那里可以观察到SSI变化对臭氧化学和温度的直接影响，但在地球的S表面，TSI变化的直接影响相当小。由于太阳信号向下传输的动力过程，太阳信号在对流层发生间接放大。然而，在量化太阳信号和将物理过程归因于地表探测到的太阳信号方面仍然存在很大的不确定性。SolVarCCM项目旨在通过探索最新的模式模拟来进一步提高我们对太阳引起的气候变异性的理解。化学气候模式初始(CCMI)为分析从对流层到中间层上层的大气化学和动力学中的太阳信号提供了一个很好的数据库。SolVarCCM的第一部分介绍了一种方法相互比较，以确定最合适的方法来探测依赖于位置和数量的太阳信号。这一点特别重要，因为平流层下部的年代际信号仍然不能明确地归因于太阳的可变性。然后，优化的方法将被应用于近50年来CCMI模拟中的太阳信号与观测结果的验证。SolVarCCM的这一目标将直接促进WCRP/SPARC-Solaris-HEPPA的国际倡议。由于CCM数据库在太阳强迫替代方案方面有一些限制，SolVarCCM还将运行与交互海洋相耦合的CCM，以处理在两种不同的未来预测情景下替代CMIP6-SSI/TSI-数据集和EPP对太阳信号的影响。这些数据集与CCMI数据库一起，将能够分析若干模型子集中的太阳信号，以确定负责将太阳信号从中层大气层转移到对流层的过程。特定的太阳作用力(EPP和SSI)或模式配置(模式顶部和海洋耦合)对太阳引起的地表气候变率大小的作用仍不确定，将比以前的研究更有把握地估计。SolVarCCM将要研究的另一个新问题是太阳诱导的气候变化在气候变化中的作用。

Solar induced climate variability is an important part of natural climate variability, detectable in atmospheric chemical and dynamical quantities. The physical processes driving this atmospheric solar signal involve variability in the spectral solar irradiances (SSI), the total solar irradiance (TSI) and also energetic particles precipitating (EPP) at high geomagnetic latitudes into the thermosphere and mesosphere. While the magnitude of the solar signal is large in the upper part of the atmosphere, where a direct impact of SSI variations on ozone chemistry and temperature is observed, the direct impact of TSI variations at the Earth´s surface is rather small. Due to dy-namical processes, which transfer the solar signal downward, an indirect amplification of the solar signal occurs in the troposphere. However, there still exist large uncertainties in quantifying the solar signal and in attributing physical processes to detected solar signals at the surface.The SolVarCCM project aims at further improving our understanding of solar induced climate variability by exploring the most recent model simulations. The Chemistry Climate Model Initia-tive (CCMI) provides an excellent database for the analysis of the solar signal in atmospheric chemistry and dynamics extending from the troposphere to the upper mesosphere. The first part of SolVarCCM addresses a method intercomparison to identify the most appropriate approach to detect the solar signal dependent on the location and quantity. This is of particular importance as the lower stratospheric decadal signal can still not unambiguously be attributed to solar variability. The optimized methods will then be applied to validate the solar signal in CCMI simulations of the recent five decades against observations. This objective of SolVarCCM will contribute directly to the international WCRP/SPARC-SOLARIS-HEPPA initiative. As the CCM-database has some limitations concerning solar forcing alternatives, SolVarCCM will also run a CCM coupled to an interactive ocean to address the influence of the alternative CMIP6-SSI/TSI-dataset and EPP on the solar signal under two different future prediction scenarios. These datasets together with the CCMI-database will allow for the analysis of the solar signal in a number of model subsets to identify processes responsible for the transfer of the solar signal from the middle atmosphere to the troposphere. The still uncertain role of specific solar forcings (EPP and SSI) or the role of model configuration (model top and ocean coupling), on the magnitude of the solar induced cli-mate variability at the surface will be estimated with more confidence than was possible in previ-ous studies. Another new issue to be investigated in SolVarCCM is the role of solar induced cli-mate variability in a changing climate.