Abstract. The ATLID-CPR-MSI retrieval of Clouds, Aerosols and Precipitation (ACM-CAP) product provides a synergistic “best-estimate” retrieval of the quantities and properties of all aerosols and hydrometeors detected by EarthCARE. While synergistic retrieval algorithms are now mature in many contexts, ACM-CAP is unique in providing a single unified retrieval product for all classes of hydrometeor—ice cloud and snow, drizzle and rain, and liquid clouds—and aerosol species, informed by the synergistic target classification (AC-TC). The simultaneous retrieval of the entire atmosphere with a single optimal estimation retrieval, called Cloud, Aerosol and Precipitation from mulTiple Instruments using a VAriational TEchnique (CAPTIVATE), allows for a robust accounting of observational and retrieval errors and the contributions of passive and integrated measurements in the context of layered and complex regimes, and for enforcing physical relationships between components (e.g. the conservation of precipitating mass flux through the melting layer). We have demonstrated and evaluated the ACM-CAP product as applied to the three EarthCARE test scenes simulated from numerical weather model forecasts, using both case studies and statistical evaluation against the simulated measurements and the “true” quantities from the numerical model. We show that the retrievals are both strongly constrained by the observations from the active and passive instruments, and overall closely resemble the underlying model fields in terms of bulk quantities (e.g. cloud water content, precipitation mass flux, and aerosol extinction) and microphysical properties (e.g. cloud effective radius, median volume diameter, and aerosols lidar ratio). The retrieval performs best where the active instruments have strong and unambiguous signal: in ice clouds and snow, which is observed by both ATLID and CPR, and in light to moderate rain, where CPR signal is strong. In precipitation, CPR's Doppler capability permits enhanced retrievals of snow particle density and raindrop size. In complex and layered scenes where ATLID is obscured, we have shown that making a simple assumption about the presence and vertical distribution of liquid cloud in rain and mixed-phase clouds allows improved assimilation of MSI solar radiances. In combination with a constraint on CPR path-integrated attenuation from the ocean surface, this leads to improved retrievals of both liquid cloud and rain in mid-latitude stratiform precipitation. In the heaviest convective precipitation (i.e. greater than around 10 mm h^-1), both active instruments are strongly attenuated and dominated by multiple scattering; in these situations ACM-CAP provides a seamless retrieval of cloud and precipitation, but one which is subject to a high degree of uncertainty. ACM-CAP's aerosol retrieval, constrained by ATLID and MSI solar radiances, is performed in hydrometeor-free parts of the atmosphere. The lidar backscatter is subject to high noise, while the solar radiances are expected to be dominated by uncertainties in surface properties especially over land. While the aerosol optical depth is well-constrained in the test scenes, there is a high degree of noise at the ~1 km resolution of the ACM-CAP product. The use of numerical forecast models to simulate test scenes for testing and evaluation puts EarthCARE L2 processors at an unprecedented degree of readiness ahead of launch. While exposure to further simulated test scenes, campaign data, and ultimately in-flight EarthCARE measurements will motivate ongoing improvements to the representation of cloud and precipitation, the instrument forward-models, and their uncertainties, the present evaluation demonstrates that ACM-CAP will provide a novel unified and synergistic retrieval of clouds, aerosols and precipitation of high quality, including a robust accounting of the contributions of observations, and of measurement and retrieval errors.

中文翻译：

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来自 EarthCARE 的云、气溶胶和降水的统一协同检索：ACM-CAP 产品

摘要。云、气溶胶和降水 (ACM-CAP) 产品的 ATLID-CPR-MSI 反演提供了对 EarthCARE 检测到的所有气溶胶和水凝物的数量和特性的协同“最佳估计”反演。虽然协同反演算法现在在许多情况下已经成熟，但 ACM-CAP 在为所有类别的水凝物（冰云和雪、毛毛雨和雨以及液态云）和气溶胶物种提供单一统一反演产品方面是独一无二的，由协同目标分类（AC-TC）。使用可变技术（CAPTIVATE）从多个仪器中通过单一最佳估计检索同时检索整个大气，称为云、气溶胶和降水，允许在分层和复杂机制的背景下对观测和检索误差以及被动和集成测量的贡献进行稳健的计算，并用于加强组件之间的物理关系（例如通过熔化层的沉淀质量通量的守恒）。我们已经演示和评估了 ACM-CAP 产品应用于从数值天气模型预报模拟的三个 EarthCARE 测试场景，使用案例研究和统计评估对模拟测量和数值模型的“真实”数量。我们表明，反演都受到有源和无源仪器观测的强烈限制，并且总体上在大量数量（例如云水含量、降水质量通量、和气溶胶消光）和微物理特性（例如云有效半径、中值体积直径和气溶胶激光雷达比）。在有源仪器具有强烈且明确的信号的情况下，检索表现最佳：在 ATLID 和 CPR 都观察到的冰云和雪中，以及在 CPR 信号强的小雨到中雨中。在降水方面，CPR 的多普勒功能允许增强对雪粒子密度和雨滴大小的检索。在 ATLID 被遮挡的复杂和分层场景中，我们已经表明，对雨和混合相云中液态云的存在和垂直分布做出简单假设可以改善 MSI 太阳辐射的同化。结合来自海洋表面的 CPR 路径综合衰减的约束，这导致改进了对中纬度层状降水的液态云和雨的反演。在最强烈的对流降水（即大于约 10 mm h^-1), 两种有源仪器都被强烈衰减并以多次散射为主; 在这些情况下，ACM-CAP 提供了云和降水的无缝检索，但这种检索具有高度的不确定性。ACM-CAP 的气溶胶回收受 ATLID 和 MSI 太阳辐射的限制，是在大气中无水凝物的部分进行的。激光雷达反向散射受到高噪声的影响，而太阳辐射预计将受表面特性的不确定性影响，尤其是在陆地上。虽然气溶胶光学深度在测试场景中受到很好的约束，但在 ACM-CAP 产品的约 1 公里分辨率下存在高度噪声。使用数值预测模型模拟测试场景进行测试和评估，使 EarthCARE L2 处理器在发布前处于前所未有的准备状态。