Cloud and aerosol contribution to the Earth's radiative budget constitutes one of the most significant uncertainties in future climate projections. To distinguish between clouds and cloud-free air, atmospheric scientists have been using a wide range of instruments, techniques, and algorithms with various detection thresholds. However, since the change from a cloudy to a cloud-free atmosphere may be gradual and, in some cases, far from obvious, recent research is questioning where the threshold between both phases should be established. These considerations lead to contemplate a transition zone (TZ) between cloud and cloud-free conditions. In the present study, backscatter profiles obtained by a Vaisala CL31 ceilometer were processed to assess the transition zone. First, two widely used cloud detection algorithms were applied and compared: the method provided by the ceilometer manufacturer (Vaisala) and Cloudnetpy, the algorithm from ACTRIS Cloudnet, a project devoted to aerosol, clouds, and trace gases research. Second, a sensitivity analysis was applied to the backscatter and signal-to-noise ratio thresholds used for cloud detection in Cloudnetpy. This methodology has allowed us to assess the vertical distribution of clouds, aerosols, the TZ, and its frequency of occurrence. Results indicate a gradual transition in backscatter retrievals from cloud to cloud-free, where particles detected near cloud boundaries induced higher backscatter values than those found further away. Depending on the thresholds used, we observed a 9.3% (with an estimated range of uncertainty of 5.420%) variation in cloud occurrence which can be attributed to TZ conditions. Analysing the whole backscatter profile, we found as many TZ conditions as cloudy values, which emphasises the importance of studying the vertical distribution of the TZ. Moreover, the analysis of TZ occurrence in height and time revealed that such conditions concentrate below 800m during night periods, although annual height-hour distributions involve a remarkable variability among seasons. These findings highlight the importance of either including an additional phase between ‘pure clouds’ and ‘pure aerosols’ or treating them as a continuum of suspended particles in the atmosphere.

中文翻译：

---

一种通过云高计测量评估云-气溶胶过渡区的方法


云和气溶胶对地球辐射预算的贡献是未来气候预测中最重要的不确定因素之一。为了区分云和无云空气，大气科学家一直在使用各种具有不同检测阈值的仪器、技术和算法。然而，由于从多云到无云大气的变化可能是渐进的，并且在某些情况下，远非显而易见，因此最近的研究正在质疑应在哪里确定两个阶段之间的阈值。这些考虑导致考虑云和无云条件之间的过渡区 (TZ)。在本研究中，对维萨拉 CL31 云高仪获得的反向散射剖面进行了处理，以评估过渡区。首先，应用并比较了两种广泛使用的云检测算法：云高计制造商（Vaisala）提供的方法和Cloudnetpy，ACTRIS Cloudnet（一个致力于气溶胶、云和微量气体研究的项目）的算法。其次，对 Cloudnetpy 中用于云检测的反向散射和信噪比阈值进行了灵敏度分析。这种方法使我们能够评估云、气溶胶、TZ 的垂直分布及其发生频率。结果表明，反向散射检索从云到无云逐渐过渡，其中在云边界附近检测到的粒子比在更远的地方发现的粒子产生更高的反向散射值。根据所使用的阈值，我们观察到云发生率存在 9.3%（估计不确定性范围为 5.420%）的变化，这可归因于 TZ 条件。 分析整个后向散射剖面，我们发现了与多云值一样多的 TZ 条件，这强调了研究 TZ 垂直分布的重要性。此外，对 TZ 发生高度和时间的分析表明，尽管每年的高度-小时分布在季节之间存在显着的变化，但这种情况集中在夜间 800 m 以下。这些发现强调了在“纯云”和“纯气溶胶”之间添加一个附加阶段或将它们视为大气中悬浮颗粒的连续体的重要性。