Algorithmic improvements and consistency checks of the NOAA global gridded super-collated SSTs from low Earth orbiting satellites (L3S-LEO)

O. Jonasson, I. Gladkova, A. Ignatov, Y. Kihai
{"title":"Algorithmic improvements and consistency checks of the NOAA global gridded super-collated SSTs from low Earth orbiting satellites (L3S-LEO)","authors":"O. Jonasson, I. Gladkova, A. Ignatov, Y. Kihai","doi":"10.1117/12.2585819","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":184582,"journal":{"name":"Ocean Sensing and Monitoring XIII","volume":"776 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ocean Sensing and Monitoring XIII","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2585819","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Algorithmic improvements and consistency checks of the NOAA global gridded super-collated SSTs from low Earth orbiting satellites (L3S-LEO) Front Matter: Volume 11752
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1