Active Cloud Regimes of cloud vertical structure from active observations

We introduce a new type of cloud class, which we call “active cloud regime” (ACR), owing to its provenance from active (lidar and cloud radar) spaceborne cloud observations. The ACR flavor of this work describes prevalent monthly mixtures at ~400 km scales of previously introduced cloud vertical structures (CVS) inferred from instantaneous ~ 2 km observations. ACRs thus constitute a gridded cloud dataset generated from the vertically-resolved cloud mask available from the 2B-CLDCLASS-LIDAR CloudSat dataset fusing CALIPSO (lidar) and CloudSat (cloud radar) cloud retrievals. We show that the global classification of cloudiness under the ACR framework provides valuable insights on how the world’s cloud systems affect atmospheric energetics. Using NASA’s GEOS model, we also demonstrate that it is possible to apply the ACR concept to Earth System Models that have the capability to produce subgrid cloudiness obeying pre-specified vertical overlap rules, providing thus another means to assess the realism of simulated clouds. The Cloud Vertical Structure dataset, Active Cloud Regime for observation and the model, and data that supports the figures have been uploaded.本研究提出一种新型云类，命名为“主动云态（active cloud regime, ACR）”，其数据源自主动式（激光雷达与云雷达）星载云观测。本研究界定的ACR，表征了约400公里尺度下普遍存在的月度云混合状态——这类混合状态基于瞬时约2公里观测反演得到的、此前已提出的云垂直结构（cloud vertical structures, CVS）构建而成。ACR数据集属于网格化云数据集，其依托融合了云气溶胶激光雷达与红外轨道探测卫星（CALIPSO，激光雷达）和CloudSat（云雷达）云反演产品的2B-CLDCLASS-LIDAR CloudSat数据集所提供的垂直分辨云掩膜生成。本研究证实，基于ACR框架的全球云量分类，可为解析全球云系对大气能量学过程的影响机制提供极具价值的科学见解。本研究借助美国国家航空航天局（NASA）的GEOS模式，进一步证明可将ACR概念推广应用至具备生成符合预设垂直重叠规则的次网格云量能力的地球系统模式（Earth System Models），从而为评估模拟云系的真实性提供了另一可行路径。 云垂直结构数据集、面向观测与模式的主动云态数据集，以及支撑各图表的数据均已上传。