Warm boundary-layer cloud properties and cloud susceptibilities product at the ARM ENA observatory

Cloud liquid water path, albedo, and cloud fraction susceptibilities for marine warm boundary-layer clouds are quantified using the Meteosat retrieved cloud microphysical properties at the ARM Eastern North Atlantic (ENA) observatory in the Azores. The Meteosat cloud retrievals are based on the methods applied by the Clouds and the Earth’s Radiant Energy System (CERES) project, which are specifically tailored to support the ARM user facility over the ARM ground-based observation sites (enavisstpx2dm11minnisX1.c1). Cloud susceptibility is quantified as the slope between cloud properties and Nd within a 1-degree-by-1-degree grid box at each satellite time step using a least-square regression. To reduce uncertainties associated with the adiabatic assumption in the Nd retrieval, for each cloud object, we exclude cloudy pixels at the cloud edge, defined as those adjacent to cloud-free pixels. To minimize influence of cloud heterogeneity and co-variability on the retrieved cloud susceptibility, cloud properties are averaged to 0.25-degree resolution using the 3-km pixel-level retrieval, and the 1-degree cloud susceptibilities are estimated using the smoothed data. Cloud type classification is applied to distinct cloud object, labeling all contiguous cloudy pixels. Marine warm boundary-layer clouds are defined as clouds with 90% of cloud tops below 3km, and Meteosat retrieved cloud phase as liquid.

针对海洋暖边界层云，本研究利用亚速尔群岛ARM东大西洋（ENA）观测站的Meteosat反演云微物理属性，量化了云液态水路径、反照率与云分数敏感性。本次采用的Meteosat云反演算法，基于云与地球辐射能量系统（Clouds and the Earth’s Radiant Energy System, CERES）项目所使用的方法，该方法专为ARM地面观测站点的ARM用户设施定制（enavisstpx2dm11minnisX1.c1）。云敏感性通过最小二乘回归法，以每个卫星时间步长下1°×1°网格盒内云属性与云滴数浓度（Nd）的斜率进行量化。为降低Nd反演过程中绝热假设带来的不确定性，针对每个云对象，我们剔除云边缘的云像素——云边缘被定义为与无云像素相邻的像素。为尽可能减小云异质性与协变特性对反演得到的云敏感性的影响，本研究利用3km像素级反演结果将云属性平均至0.25°分辨率，并基于平滑后的数据估算1°分辨率的云敏感性。研究对独立云对象开展云类型分类，标记所有连续云像素。海洋暖边界层云被定义为：云顶90%位于3km以下，且经Meteosat反演得到的云相态为液态的云。