Improved Cloud Detection in Along Track Scanning Radiometer (ATSR) Data over the Ocean
Improved Cloud Detection in Along Track Scanning Radiometer (ATSR) Data over the Ocean
复制标题
改进了海洋上沿轨道扫描辐射计 (ATSR) 数据的云检测
DOI：
10.1016/s0034-4257(98)00025-x
复制
发表时间：
1998
影响因子：
13.5
通讯作者：
Andrew Harris
中科院分区：
文献类型：
--
作者：
James J. Simpson;Andrew H. Schmidt;Andrew Harris
根据卫星数据对海表温度（SST）的有效估计[例如，沿着扫描辐射计（ATSR）]的云屏蔽算法主要依赖于云的识别和去除，但目前文献中还没有针对ATSR数据的云屏蔽算法。提出了一种新的算法，ATSR分裂和合并聚类（ATSR/SMC）算法，云遮蔽ATSR数据，评估图像中的每一个像素，是统计上可重复的，计算效率高，不需要云类型的知识。此外，它是有效的检测多层云结构的场景，这是一个困难的任务，因为这样的系统通常具有双峰统计分布。它还能准确地探测闪烁辐射，这在1.6 μm视图、云边界附近的亚像素云污染和低洼海洋层状云中的至少一个视图中很常见。从历史上看，这些问题干扰了基于ATSR的SST检索[参见Jones等人的工作，（1996 a，B）和其中引用的参考文献]。从无云海洋像素中获得的SST与96个浮标观测值进行了验证，平均差异（浮标-SST）为+0.24 ° C ±0.51°C。对于测试的103对图像（前向/最低点视图），SADIST（标准ATSR处理）与ATSR/SMC云检测结果的平均11 μm BT对于SADIST比ATSR/SMC低0.4°C（白天）和0.6°C（夜间），即使SADIST云掩模相对于ATSR/SMC云掩模通常过度检测云。这些结果，加上其他讨论的文本，支持的结论是，新的程序产生的云掩模是上级的标准ATSR业务云掩模产品，它保留了更多的有效像素。该算法适用于热带和中纬度地区。它不是用来探测海冰的，因此不应该在极地地区使用。最后，该方法可以很容易地适用于ATSR-2数据和其他即将发射的传感器的数据。
Valid estimates of sea surface temperature (SST) from satellite data [e.g., the Along Track Scanning Radiometer (ATSR)] are critically dependent upon the identification and removal of cloud from the data, but few cloud-screening algorithms for ATSR data have appeared in the literature. A new algorithm, the ATSR Split-and-Merge Clustering (ATSR/SMC) algorithm, for cloud masking ATSR data is presented which evaluates every pixel in the image, is statistically reproducible, computationally efficient, and requires no knowledge of cloud type. Moreover, it is effective in detecting multilayer cloud structures in a scene, which is a difficult task because such systems generally have bimodal statistical distributions. It also accurately detects glint radiance, which is quite common in at least one of the 1.6 μm views, subpixel cloud contamination near cloud boundaries and low-lying marine stratiform cloud. Historically, these issues have interfered with ATSR-based SST retrieval [see the work of Jones et al., (1996a,b) and the references cited therein]. The SSTs derived from the cloud-free ocean pixels were validated with 96 buoy observations and the mean difference (buoy−SST) was +0.24°C±0.51°C. For the 103 pairs of images (forward/nadir views) tested, the mean 11 μm BTs that result from SADIST (standard ATSR processing) vs. ATSR/SMC cloud detection are 0.4°C (daytime) and 0.6°C (nighttime) colder for SADIST than for ATSR/SMC, even though the SADIST cloud masks generally overdetect clouds relative to ATSR/SMC cloud masks. These results, plus others discussed in the text, support the conclusion that the new procedure produces cloud masks which are superior to the standard ATSR operational cloud mask product and it retains substantially more valid pixels. The algorithm can be used in tropical and midlatitude regions. It is not designed to detect sea ice, and consequently should not be used in polar regions. Finally, the approach can easily be adapted to ATSR-2 data and to other data to be taken from soon to be launched sensors.