Bony Sandrine, Stevens Bjorn, Ament Felix, Bigorre Sebastien, Chazette Patrick, Crewell Susanne, Delanoë Julien, Emanuel Kerry, Farrell David, Flamant Cyrille, Gross Silke, Hirsch Lutz, Karstensen Johannes, Mayer Bernhard, Nuijens Louise, Ruppert James H, Sandu Irina, Siebesma Pier, Speich Sabrina, Szczap Frédéric, Totems Julien, Vogel Raphaela, Wendisch Manfred, Wirth Martin
1LMD/IPSL, CNRS, Sorbonne Université, UPMC, 4 Place Jussieu, 75252 Paris, France.
2Max Planck Institute for Meteorology, Bundesstr. 53, 20146 Hamburg, Germany.
Surv Geophys. 2017;38(6):1529-1568. doi: 10.1007/s10712-017-9428-0. Epub 2017 Sep 27.
Trade-wind cumuli constitute the cloud type with the highest frequency of occurrence on Earth, and it has been shown that their sensitivity to changing environmental conditions will critically influence the magnitude and pace of future global warming. Research over the last decade has pointed out the importance of the interplay between clouds, convection and circulation in controling this sensitivity. Numerical models represent this interplay in diverse ways, which translates into different responses of trade-cumuli to climate perturbations. Climate models predict that the area covered by shallow cumuli at cloud base is very sensitive to changes in environmental conditions, while process models suggest the opposite. To understand and resolve this contradiction, we propose to organize a field campaign aimed at quantifying the physical properties of trade-cumuli (e.g., cloud fraction and water content) as a function of the large-scale environment. Beyond a better understanding of clouds-circulation coupling processes, the campaign will provide a reference data set that may be used as a benchmark for advancing the modelling and the satellite remote sensing of clouds and circulation. It will also be an opportunity for complementary investigations such as evaluating model convective parameterizations or studying the role of ocean mesoscale eddies in air-sea interactions and convective organization.
信风云是地球上出现频率最高的云类型，并且已经表明它们对不断变化的环境条件的敏感性将严重影响未来全球变暖的幅度和速度。过去十年的研究指出了云、对流和环流之间的相互作用在控制这种敏感性方面的重要性。数值模型以不同方式表示这种相互作用，这转化为信风云对气候扰动的不同响应。气候模型预测，云底浅积云覆盖的面积对环境条件变化非常敏感，而过程模型则显示相反情况。为了理解和解决这一矛盾，我们提议组织一次实地考察活动，旨在量化信风云的物理特性（如云量分数和含水量）与大尺度环境之间的函数关系。除了更好地理解云 - 环流耦合过程之外，该活动还将提供一个参考数据集，可作为推进云与环流建模及卫星遥感的基准。这也将是进行补充研究的契机，比如评估模型对流参数化或研究海洋中尺度涡旋在海气相互作用和对流组织中的作用。
