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首页> 外文期刊>Quarterly Journal of the Royal Meteorological Society >A 3D cloud-construction algorithm for the EarthCARE satellite mission
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A 3D cloud-construction algorithm for the EarthCARE satellite mission

机译：EarthCARE卫星任务的3D云构建算法

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This article presents and assesses an algorithm that constructs 3D distributions of cloud from passive satellite imagery and collocated 2D nadir profiles of cloud properties inferred synergistically from lidar, cloud radar and imager data. It effectively widens the active-passive retrieved cross-section (RXS) of cloud properties, thereby enabling computation of radiative fluxes and radiances that can be compared with measured values in an attempt to perform radiative closure experiments that aim to assess the RXS. For this introductory study, A-train data were used to verify the scene-construction algorithm and only ID radiative transfer calculations were performed. The construction algorithm fills off-RXS recipient pixels by computing sums of squared differences (a cost function F) between their spectral radiances and those of potential donor pixels/columns on the RXS. Of the RXS pixels with F lower than a certain value, the one with the smallest Euclidean distance to the recipient pixel is designated as the donor, and its retrieved cloud properties and other attributes such as ID radiative heating rates are consigned to the recipient. It is shown that both the RXS itself and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery can be reconstructed extremely well using just visible and thermal infrared channels. Suitable donors usually lie within 10 km of the recipient. RXSs and their associated radiative heating profiles are reconstructed best for extensive planar clouds and less reliably for broken convective clouds. Domain-average 1D broadband radiative fluxes at the top of the atmosphere (TO A) for (21 km)~2 domains constructed from MODIS, CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data agree well with coincidental values derived from Clouds and the Earth's Radiant Energy System (CERES) radiances: differences between modelled and measured reflected shortwave fluxes are within ± 10 W m~(-2) for ~35% of the several hundred domains constructed for eight orbits. Correspondingly, for outgoing longwave radiation ~65% are within ±10Wm~(-2).
机译：本文提出并评估了一种算法，该算法可从被动卫星图像构建云的3D分布，并根据激光雷达，云雷达和成像器数据协同推断出的并置的2D云特征的最低点轮廓。它有效地拓宽了云特性的主动-被动检索横截面（RXS），从而能够计算辐射通量和辐射率，可以将其与测量值进行比较，以尝试进行旨在评估RXS的辐射封闭实验。对于本介绍性研究，使用A火车数据来验证场景构造算法，并且仅执行ID辐射传递计算。构造算法通过计算其光谱辐射率与RXS上潜在施主像素/列的辐射率之间的平方差之和（成本函数F）来填充RXS接收者像素。在F小于特定值的RXS像素中，与接收者像素的欧几里得距离最小的像素被指定为施主，并将其获取的云特性和其他属性（例如ID辐射加热速率）委托给接收者。结果表明，仅使用可见光和热红外通道，就可以很好地重建RXS本身和中等分辨率成像光谱仪（MODIS）图像。合适的捐助者通常位于接收者10公里以内。 RXS及其相关的辐射加热曲线对于大范围的平面云重构得最好，而对于破碎的对流云则不那么可靠。由MODIS，CloudSat和Cloud-Aerosol Lidar和红外探路者卫星观测（CALIPSO）数据构建的（21 km）〜2个域的大气顶部（TO A）的域平均一维宽带辐射通量与得出的巧合值非常吻合来自云和地球辐射能系统（CERES）辐射的数据：在为八个轨道建造的数百个域的约35％中，建模和测量的反射短波通量之间的差异在±10 W m〜（-2）以内。相应地，对于出射的长波辐射，〜65％在±10Wm〜（-2）以内。

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