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Ocean Sensing and Monitoring XIII最新文献

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Algorithmic improvements and consistency checks of the NOAA global gridded super-collated SSTs from low Earth orbiting satellites (L3S-LEO) 低地球轨道卫星(L3S-LEO) NOAA全球网格超整理海温数据的算法改进与一致性检验
Pub Date : 2021-04-12 DOI: 10.1117/12.2585819
O. Jonasson, I. Gladkova, A. Ignatov, Y. Kihai
NOAA provides satellite sea surface temperature (SST) products using the Advanced Clear-Sky Processor for Oceans (ACSPO) system. With the large number of earth-viewing sensors in orbit, data volume has become difficult to manage. In response, NOAA has developed gridded super-collated (L3S-LEO) SST products which collate L3U data from multiple Low-Earth-Orbiting satellites into a multi-sensor product. In this work we describe recent L3S algorithm improvements, aimed at improving spatial continuity of SST imagery and reducing impact of cloud leakages from individual sensor L3U data. We also present results of long-term validation of L3S-LEO products versus in-situ data in NOAA SQUAM system.
NOAA使用先进的晴空海洋处理器(ACSPO)系统提供卫星海面温度(SST)产品。随着在轨地球观测传感器数量的增加,数据量的管理变得越来越困难。为此,NOAA开发了网格超整理(L3S-LEO)海表温度产品,将来自多个低地球轨道卫星的L3U数据整理成一个多传感器产品。在这项工作中,我们描述了最近的L3S算法改进,旨在提高海温图像的空间连续性,减少单个传感器L3U数据的云泄漏的影响。我们还介绍了L3S-LEO产品与NOAA SQUAM系统中原位数据的长期验证结果。
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引用次数: 5
Front Matter: Volume 11752 前题:卷11752
Pub Date : 1900-01-01 DOI: 10.1117/12.2598635
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引用次数: 0
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Ocean Sensing and Monitoring XIII
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