Abstract. Despite significant advances in atmospheric measurements and modeling, clouds response to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. Documenting how the cloud detailed vertical structure, the cloud cover and opacity evolve on a global scale over several decades is a necessary step towards understanding and predicting the cloud response to climate warming. Among satellite-based remote sensing techniques, active sounding plays a special role, owing to its high vertical and horizontal resolution and high sensitivity. The launch of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) in 2006 started the era of space-borne optical active sounding of the Earth’s atmosphere, which continued with the CATS (Cloud-Aerosol Transport System) lidar on-board ISS in 2015 and the Atmospheric Laser Doppler INstrument (ALADIN) lidar on-board Aeolus in 2018. The next important step is the ATmospheric LIDar (ATLID) instrument from the EarthCARE mission expected to launch in 2023. With ATLID, the scientific community will continue receiving invaluable vertically resolved information of atmospheric optical properties needed for the estimation of cloud occurrence frequency, thickness, and height. In this article, we define the ATLID Climate Product, Short-Term (CLIMP-ST) and ATLID Climate Product, Long-Term (CLIMP-LT). The purpose of CLIMP-ST is to help evaluate the description of cloud processes in climate models, beyond what is already done with existing space lidar observations, thanks to ATLID new capabilities. The CLIMP-LT will merge the ATLID cloud observations with previous space lidar observations to build a long-term cloud lidar record useful to evaluate the cloud climate variability predicted by climate models. We start with comparing the cloud detection capabilities of ATLID and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) in day- and night-time, on a profile-to-profile basis in analyzing virtual ATLID and CALIOP measurements over synthetic cirrus and stratocumulus cloud scenes. We show that solar background noise affects the cloud detectability in daytime conditions differently for ATLID and CALIPSO. We found that the simulated daytime ATLID measurements have lower noise than the CALIOP day-time simulated measurements. This allows lowering the cloud detection thresholds for ATLID compared to CALIOP and enables ATLID to detect optically thinner clouds than CALIOP in daytime at high horizontal resolution without false cloud detection. These lower threshold values will be used to build the ATLID-ST. Therefore, CLIMP-ST should provide an advance to evaluate optically thin clouds like cirrus or ice polar clouds in climate models compared to the current existing capability. We also found that ATLID and CALIPSO may detect similar clouds if we convert ATLID 355 nm profiles to 532 nm profiles and apply the same cloud detection thresholds as the ones used in GOCCCP (GCM Oriented Calipso Cloud Product). Therefore, this approach will be used to build the CLIMP-LT. The CLIMP-LT data will be merged with the GOCCP data to get a long-term (2006–2030’s) cloud climate record. Finally, we investigate the detectability of cloud changes induced by human-caused climate warming within a virtual long-term cloud monthly gridded lidar dataset over the 2008–2034 period that we obtained from two ocean-atmosphere-coupled climate models coupled with a lidar simulator. We found that a long-term trend of opaque cloud cover should emerge from short-term natural climate variability after 4 to 7 years of ATLID measurements (merged with CALIPSO measurements) according to predictions from the considered climate models. We conclude that a long-term lidar cloud record build from the merge of the actual ATLID-LT data with CALIPSO-GOCCP data will be a useful tool to monitor cloud changes and to evaluate the realism of the cloud changes predicted by climate models.

中文翻译：

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ATLID 云气候产品

摘要。尽管大气测量和建模取得了重大进展，但云对人为气候变暖的反应仍然是气候模型预测中最大的不确定性来源。记录云详细的垂直结构、云量和不透明度如何在几十年内在全球范围内演变是理解和预测云对气候变暖的响应的必要步骤。在基于卫星的遥感技术中，主动探测由于其高垂直和水平分辨率以及高灵敏度而发挥着特殊的作用。2006年云气溶胶激光雷达和红外探路者卫星观测（CALIPSO）的发射开启了地球大气层星载光学主动探测时代，继 2015 年 ISS 机载 CATS（云气溶胶传输系统）激光雷达和 2018 年 Aeolus 机载大气激光多普勒仪器（ALADIN）激光雷达之后，下一个重要步骤是大气激光雷达（ATLID）仪器EarthCARE 任务预计将于 2023 年发射。借助 ATLID，科学界将继续接收估算云出现频率、厚度和高度所需的大气光学特性的宝贵垂直分辨信息。在本文中，我们定义了 ATLID 短期气候产品 (CLIMP-ST) 和 ATLID 长期气候产品 (CLIMP-LT)。由于 ATLID 的新功能，CLIMP-ST 的目的是帮助评估气候模型中云过程的描述，超越现有空间激光雷达观测已经完成的工作。CLIMP-LT 将把 ATLID 云观测与以前的空间激光雷达观测相结合，以建立一个长期的云激光雷达记录，用于评估气候模型预测的云气候变异性。我们首先比较 ATLID 和 CALIOP（具有正交偏振的云气溶胶激光雷达）在白天和夜间的云检测能力，逐个分析合成卷云和层积云上的虚拟 ATLID 和 CALIOP 测量结果场景。我们表明，对于 ATLID 和 CALIPSO，太阳背景噪声在白天条件下对云可探测性的影响不同。我们发现模拟白天 ATLID 测量的噪声低于 CALIOP 白天模拟测量。与 CALIOP 相比，这允许降低 ATLID 的云检测阈值，并使 ATLID 能够在白天以高水平分辨率检测光学上比 CALIOP 更薄的云，而不会出现错误的云检测。这些较低的阈值将用于构建 ATLID-ST。因此，与当前现有能力相比，CLIMP-ST 应该提供一种进步来评估气候模型中的光学薄云，如卷云或极地冰云。我们还发现，如果我们将 ATLID 355 nm 配置文件转换为 532 nm 配置文件并应用与 GOCCCP（面向 GCM 的 Calipso 云产品）中使用的相同的云检测阈值，ATLID 和 CALIPSO 可能会检测到类似的云。因此，这种方法将用于构建 CLIMP-LT。CLIMP-LT 数据将与 GOCCP 数据合并以获得长期（2006-2030 年）的云气候记录。最后，我们研究了 2008 年至 2034 年期间从两个海洋-大气耦合气候模型和激光雷达模拟器获得的虚拟长期云每月网格化激光雷达数据集中人为气候变暖引起的云变化的可检测性. 我们发现，根据所考虑的气候模型的预测，经过 4 到 7 年的 ATLID 测量（与 CALIPSO 测量合并）后，短期自然气候变率应该会出现不透明云层覆盖的长期趋势。我们的结论是，通过合并实际 ATLID-LT 数据与 CALIPSO-GOCCP 数据构建的长期激光雷达云记录将成为监测云变化和评估气候模型预测的云变化真实性的有用工具。我们研究了 2008 年至 2034 年期间虚拟长期云每月网格化激光雷达数据集内人为气候变暖引起的云变化的可检测性，该数据集是我们从两个海洋-大气耦合气候模型和激光雷达模拟器获得的。我们发现，根据所考虑的气候模型的预测，经过 4 到 7 年的 ATLID 测量（与 CALIPSO 测量合并）后，短期自然气候变率应该会出现不透明云层覆盖的长期趋势。我们的结论是，通过合并实际 ATLID-LT 数据与 CALIPSO-GOCCP 数据构建的长期激光雷达云记录将成为监测云变化和评估气候模型预测的云变化真实性的有用工具。我们研究了 2008 年至 2034 年期间虚拟长期云每月网格化激光雷达数据集内人为气候变暖引起的云变化的可检测性，该数据集是我们从两个海洋-大气耦合气候模型和激光雷达模拟器获得的。我们发现，根据所考虑的气候模型的预测，经过 4 到 7 年的 ATLID 测量（与 CALIPSO 测量合并）后，短期自然气候变率应该会出现不透明云层覆盖的长期趋势。我们的结论是，通过合并实际 ATLID-LT 数据与 CALIPSO-GOCCP 数据构建的长期激光雷达云记录将成为监测云变化和评估气候模型预测的云变化真实性的有用工具。