Abstract We present comparisons of cloud droplet size distributions (DSDs) retrieved from the research scanning polarimeter (RSP) data with correlative in situ measurements made during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). The airborne portion of this field experiment was based out of St. John's airport, Newfoundland, Canada with the focus of this paper being on the deployment in May–June 2016. RSP was onboard the NASA C-130 aircraft together with an array of in situ and other remote sensing instrumentation. The RSP is an along-track scanner measuring the polarized and total reflectance in 9 spectral channels. Its uniquely high angular resolution allows for characterization of liquid water droplet sizes using the rainbow structure observed in the polarized reflectance over the scattering angle range from 135° to 165°. The rainbow is dominated by single scattering of light by cloud droplets, so its structure is characteristic specifically of the droplet sizes at cloud top (within unit optical depth into the cloud, equivalent to approximately 50 m). A parametric fitting algorithm applied to the polarized reflectance provides retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, the Rainbow Fourier Transform (RFT), which allows us to retrieve the droplet size distribution itself. The latter is important in the case of clouds with complex microphysical structure, or multiple layers of cloud, which result in multi-modal DSDs. During NAAMES the aircraft performed a number of flight patterns specifically designed for comparisons between remote sensing retrievals and in situ measurements. These patterns consisted of two flight segments above the same straight ground track. One of these segments was flown above clouds allowing for remote sensing measurements, while the other was near the cloud top where cloud droplets were sampled. We compare the DSDs retrieved from the RSP data with in situ measurements made by the Cloud Droplet Probe (CDP). The comparisons generally show good agreement (better than 1 μm for effective radius and in most cases better than 0.02 for effective variance) with deviations explainable by the position of the aircraft within the cloud, or by the presence of additional cloud layers between the cloud being sampled by the in situ instrumentation and the altitude of the remote sensing segment. In the latter case, the multi-modal DSDs retrieved from the RSP data were consistent with the multi-layer cloud structures observed in the correlative High Spectral Resolution Lidar (HSRL) profiles. The results of these comparisons provide a rare validation of polarimetric droplet size retrieval techniques, demonstrating their accuracy and robustness and the potential of satellite data of this kind on a global scale.

中文翻译：

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从研究扫描旋光仪数据中检索云滴大小：使用原位测量进行验证

摘要 我们比较了从研究扫描旋光仪 (RSP) 数据中提取的云滴尺寸分布 (DSD) 与在北大西洋气溶胶和海洋生态系统研究 (NAAMES) 期间进行的相关原位测量。该现场实验的机载部分基于加拿大纽芬兰的圣约翰机场，本文重点介绍 2016 年 5 月至 6 月的部署。RSP 与 NASA C-130 飞机以及一系列现场和其他遥感仪器。RSP 是一种沿轨道扫描仪，可测量 9 个光谱通道中的偏振反射率和总反射率。其独特的高角度分辨率允许使用在 135° 至 165° 散射角范围内在偏振反射率中观察到的彩虹结构表征液态水滴的大小。彩虹以云滴对光的单次散射为主，因此它的结构是云顶（在进入云的单位光学深度内，相当于大约 50 m）的液滴尺寸的特征。应用于偏振反射率的参数拟合算法提供了假设规定的尺寸分布形状（伽马分布）的液滴有效半径和方差的检索。除此之外，我们还使用了一种非参数方法，即彩虹傅立叶变换 (RFT)，它允许我们检索液滴尺寸分布本身。后者在具有复杂微物理结构的云或多层云的情况下很重要，这会导致多模态 DSD。在 NAAMES 期间，飞机执行了许多飞行模式，专门设计用于比较遥感检索和原位测量。这些模式由同一直线地面轨道上方的两个飞行段组成。其中一个部分飞过云层，以便进行遥感测量，而另一个部分则在云滴采样的云顶附近。我们将从 RSP 数据中检索到的 DSD 与 Cloud Droplet Probe (CDP) 进行的原位测量进行比较。比较通常显示出良好的一致性（有效半径优于 1 μm，在大多数情况下优于 0。02 有效方差），其偏差可通过飞机在云中的位置来解释，或者通过原位仪器采样的云与遥感段的高度之间存在额外的云层来解释。在后一种情况下，从 RSP 数据中检索到的多模态 DSD 与在相关高光谱分辨率激光雷达 (HSRL) 剖面中观察到的多层云结构一致。这些比较的结果为极化液滴尺寸检索技术提供了罕见的验证，证明了它们的准确性和稳健性以及此类卫星数据在全球范围内的潜力。或通过原位仪器采样的云与遥感段的高度之间存在额外的云层。在后一种情况下，从 RSP 数据中检索到的多模态 DSD 与在相关高光谱分辨率激光雷达 (HSRL) 剖面中观察到的多层云结构一致。这些比较的结果为极化液滴尺寸检索技术提供了罕见的验证，证明了它们的准确性和稳健性以及此类卫星数据在全球范围内的潜力。或者通过原位仪器采样的云和遥感段的高度之间存在额外的云层。在后一种情况下，从 RSP 数据中检索到的多模态 DSD 与在相关高光谱分辨率激光雷达 (HSRL) 剖面中观察到的多层云结构一致。这些比较的结果为极化液滴尺寸检索技术提供了罕见的验证，证明了它们的准确性和稳健性以及此类卫星数据在全球范围内的潜力。