Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, MSIN K9-30, Richland, WA, 99354, USA.
Laboratoire Météorologie Dynamique, Institute Pierre Simon Laplace, Sorbonne Université, 4, Place Jussieu, 75005, Paris, France.
Nat Commun. 2018 Jul 6;9(1):2640. doi: 10.1038/s41467-018-05028-4.
Aerosol-cloud interactions remain a major uncertainty in climate research. Studies have indicated that model estimates of cloud susceptibility to aerosols frequently exceed satellite estimates, motivating model reformulations to increase agreement. Here we show that conventional ways of using satellite information to estimate susceptibility can serve as only a weak constraint on models because the estimation is sensitive to errors in the retrieval procedures. Using instrument simulators to investigate differences between model and satellite estimates of susceptibilities, we find that low aerosol loading conditions are not well characterized by satellites, but model clouds are sensitive to aerosol perturbations in these conditions. We quantify the observational requirements needed to constrain models, and find that the nighttime lidar measurements of aerosols provide a better characterization of tenuous aerosols. We conclude that observational uncertainties and limitations need to be accounted for when assessing the role of aerosols in the climate system.
气溶胶-云相互作用仍然是气候研究中的一个主要不确定因素。研究表明,模型对云受气溶胶影响的估计值经常超过卫星估计值,这促使模型重新制定以增加一致性。在这里,我们表明,利用卫星信息来估计敏感性的传统方法只能对模型起到较弱的约束作用,因为估计值对检索过程中的误差很敏感。我们使用仪器模拟器来研究模型和卫星对敏感性估计的差异,发现卫星不能很好地描述低气溶胶负荷条件,但模型云对这些条件下的气溶胶干扰很敏感。我们量化了约束模型所需的观测要求,发现夜间气溶胶激光雷达测量可以更好地描述稀薄的气溶胶。我们的结论是,在评估气溶胶在气候系统中的作用时,需要考虑观测的不确定性和局限性。