Cloudiness change with aerosol trend reversal over China: data-model synergy from regional to large scale

在对全球气候变化的有效强迫进行量化时，云对大气成分人为变化的反应构成了很大的不确定性。一个关键因素是云对气溶胶排放的反应。在这些气溶胶-云相互作用中，云的水平范围或云的比例如何变化以适应云滴数浓度的变化成为当前的关键问题。CloudTrend将以三个关键概念为基础，大大改进对这一问题的理解和量化：(I)21世纪中国上空人为气溶胶排放的非常强烈的增加和减少趋势为探测和确定地面和卫星可获得的高质量数据中气溶胶引起的云量变化提供了独特的机会；(Ii)提供了新的模拟和数据分析工具，包括更好的卫星反演云微物理和新的制度定义，以及新的CMIP6多模式数据；建议开展大规模的数据分析和全球气候模拟，系统地借鉴区域、高质量的数据和模拟。由于南京信息科技大学(区域重点)和莱比锡大学(大规模重点)团队的专业知识协同作用，该项目成为可能。

The response of clouds to anthropogenic changes in atmospheric composition constitutes a large uncertainty when quantifying the effective forcing of global climate change. One key ele­ment is the response of clouds to aerosol emissions. In these aerosol-cloud interactions, it emerges currently as the key question how cloud horizontal extent, or cloud fraction, changes in adjustment to cloud droplet number concentration changes. Cloudtrend will substantially im­prove the understanding and quantification for this problem by building on three key ideas: (i) the very strong increasing then decreasing trends in anthropogenic aerosol emissions over China in the 21st Century provide a unique opportunity for a detection and attribution of aerosol-induced cloudiness changes in the high-quality data available from the surface and from satel­lites; (ii) new modelling and data analysis tools are available, including better satellite retrievals of cloud microphysics and new regime definitions, as well as the new CMIP6 multi-model data; and (iii) the large-scale data analysis and global climate modelling is proposed to systematically learn from the regional, high-quality data and modelling. The project is possible thanks to the synergy between the expertise in the teams at the Nanjing University of Information Science and Technology (regional focus) and the University of Leipzig (large-scale focus).