Christensen Matthew W, Gettelman Andrew, Cermak Jan, Dagan Guy, Diamond Michael, Douglas Alyson, Feingold Graham, Glassmeier Franziska, Goren Tom, Grosvenor Daniel P, Gryspeerdt Edward, Kahn Ralph, Li Zhanqing, Ma Po-Lun, Malavelle Florent, McCoy Isabel L, McCoy Daniel T, McFarquhar Greg, Mülmenstädt Johannes, Pal Sandip, Possner Anna, Povey Adam, Quaas Johannes, Rosenfeld Daniel, Schmidt Anja, Schrödner Roland, Sorooshian Armin, Stier Philip, Toll Velle, Watson-Parris Duncan, Wood Robert, Yang Mingxi, Yuan Tianle
Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, OX1 3PU, UK.
Atmospheric Science & Global Change Division, Pacific Northwest National Laboratory, Richland, WA 99354, Washington, USA.
Atmos Chem Phys. 2022 Jan;22(1):641-674. doi: 10.5194/acp-22-641-2022. Epub 2022 Jan 17.
Aerosol-cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide "opportunistic experiments" (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.
气溶胶-云相互作用(ACIs)被认为是当前人类活动引起的辐射强迫中最不确定的驱动因素。云状态对气溶胶扰动的非线性变化使得在观测到的气溶胶辐射强迫关系中确定因果关系具有挑战性。当气象变率也独立驱动气溶胶和云的变化时,利用相关性来推断因果关系可能具有挑战性。来自明确源的自然和人为气溶胶扰动提供了“机会性实验”(也称为自然实验),以便在可以更有把握地推断因果关系的情况下研究气溶胶-云相互作用。这些扰动涵盖了广泛的位置和时空尺度,包括火山爆发或工业源等点源、生物质燃烧或森林火灾产生的羽流,以及个别船舶或航运走廊的轨迹。我们回顾了不同的实验条件,并对现有的卫星数据集和实地考察进行了综合分析,以便将这些机会性实验放在一个共同的基础上,促进新的见解,并更清楚地了解气溶胶辐射强迫中的关键不确定性。云反照率扰动对背景气象条件非常敏感。通过对实验进行平均,很大程度上排除了由于气溶胶扰动导致的强液态水路径增加。机会性实验显著提高了对气溶胶-云相互作用过程层面的理解,但目前尚不清楚所发现的关系能在多大程度上可靠地扩展到全球层面,因此表明需要进行更深入的研究,以改进对气溶胶辐射强迫和气候变化的评估。