Himawari-8 Sea Surface Temperature Products from the Australian Bureau of Meteorology

IF 4.2 2区 地球科学 Q2 ENVIRONMENTAL SCIENCES Remote Sensing Pub Date : 2024-09-11 DOI:10.3390/rs16183381
Pallavi Govekar, Christopher Griffin, Owen Embury, Jonathan Mittaz, Helen Mary Beggs, Christopher J. Merchant
{"title":"Himawari-8 Sea Surface Temperature Products from the Australian Bureau of Meteorology","authors":"Pallavi Govekar, Christopher Griffin, Owen Embury, Jonathan Mittaz, Helen Mary Beggs, Christopher J. Merchant","doi":"10.3390/rs16183381","DOIUrl":null,"url":null,"abstract":"As a contribution to the Integrated Marine Observing System (IMOS), the Bureau of Meteorology introduces new reprocessed Himawari-8 satellite-derived Sea Surface Temperature (SST) products. The Radiative Transfer Model and a Bayesian cloud clearing method is used to retrieve SSTs every 10 min from the geostationary satellite Himawari-8. An empirical Sensor Specific Error Statistics (SSES) model, introduced herein, is applied to calculate bias and standard deviation for the retrieved SSTs. The SST retrieval and compositing method, along with validation results, are discussed. The monthly statistics for comparisons of Himawari-8 Level 2 Product (L2P) skin SST against in situ SST quality monitoring (iQuam) in situ SST datasets, adjusted for thermal stratification, showed a mean bias of −0.2/−0.1 K and a standard deviation of 0.4–0.7 K for daytime/night-time after bias correction, where satellite zenith angles were less than 60° and the quality level was greater than 2. For ease of use, these native resolution SST data have been composited using a method introduced herein that retains retrieved measurements, to hourly, 4-hourly and daily SST products, and projected onto the rectangular IMOS 0.02 degree grid. On average, 4-hourly products cover ≈10% more of the IMOS domain, while one-night composites cover ≈25% more of the IMOS domain than a typical 1 h composite. All available Himawari-8 data have been reprocessed for the September 2015–December 2022 period. The 10 min temporal resolution of the newly developed Himawari-8 SST data enables a daily composite with enhanced spatial coverage, effectively filling in SST gaps caused by transient clouds occlusion. Anticipated benefits of the new Himawari-8 products include enhanced data quality for applications like IMOS OceanCurrent and investigations into marine thermal stress, marine heatwaves, and ocean upwelling in near-coastal regions.","PeriodicalId":48993,"journal":{"name":"Remote Sensing","volume":"44 1","pages":""},"PeriodicalIF":4.2000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/rs16183381","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

As a contribution to the Integrated Marine Observing System (IMOS), the Bureau of Meteorology introduces new reprocessed Himawari-8 satellite-derived Sea Surface Temperature (SST) products. The Radiative Transfer Model and a Bayesian cloud clearing method is used to retrieve SSTs every 10 min from the geostationary satellite Himawari-8. An empirical Sensor Specific Error Statistics (SSES) model, introduced herein, is applied to calculate bias and standard deviation for the retrieved SSTs. The SST retrieval and compositing method, along with validation results, are discussed. The monthly statistics for comparisons of Himawari-8 Level 2 Product (L2P) skin SST against in situ SST quality monitoring (iQuam) in situ SST datasets, adjusted for thermal stratification, showed a mean bias of −0.2/−0.1 K and a standard deviation of 0.4–0.7 K for daytime/night-time after bias correction, where satellite zenith angles were less than 60° and the quality level was greater than 2. For ease of use, these native resolution SST data have been composited using a method introduced herein that retains retrieved measurements, to hourly, 4-hourly and daily SST products, and projected onto the rectangular IMOS 0.02 degree grid. On average, 4-hourly products cover ≈10% more of the IMOS domain, while one-night composites cover ≈25% more of the IMOS domain than a typical 1 h composite. All available Himawari-8 data have been reprocessed for the September 2015–December 2022 period. The 10 min temporal resolution of the newly developed Himawari-8 SST data enables a daily composite with enhanced spatial coverage, effectively filling in SST gaps caused by transient clouds occlusion. Anticipated benefits of the new Himawari-8 products include enhanced data quality for applications like IMOS OceanCurrent and investigations into marine thermal stress, marine heatwaves, and ocean upwelling in near-coastal regions.
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
澳大利亚气象局的 Himawari-8 海洋表面温度产品
作为对综合海洋观测系统(IMOS)的贡献,气象局推出了经重新处理的向日葵-8 号卫星海面温度(SST)新产品。利用辐射传输模型和贝叶斯云清除方法,每 10 分钟从地球静止卫星 Himawari-8 获取一次 SST。本文介绍的传感器特定误差统计(SSES)经验模型用于计算检索到的 SST 的偏差和标准偏差。本文讨论了 SST 检索和合成方法以及验证结果。在卫星天顶角小于 60°、质量等级大于 2 级的情况下,经热分层调整后的向日葵-8 号二级产品(L2P)表层海温与原地海温质量监测(iQuam)原地海温数据集的月度统计比较显示,偏差校正后的日间/夜间平均偏差为-0.2/-0.1 K,标准偏差为 0.4-0.7 K。为便于使用,这些原始分辨率的海温数据已采用本文介绍的一种方法进行了合成,保留了检索到的测量数据,形成了每小时、每 4 小时和每天的海温产品,并投影到 IMOS 0.02 度的矩形网格上。平均而言,4 小时产品覆盖的 IMOS 域面积≈10%,而一夜合成数据覆盖的 IMOS 域面积比典型的 1 小时合成数据≈25%。所有可用的 Himawari-8 数据都经过重新处理,时间跨度为 2015 年 9 月至 2022 年 12 月。新开发的向日葵-8 SST 数据的时间分辨率为 10 分钟,因此能够生成空间覆盖范围更广的每日合成数据,有效填补了瞬时云遮挡造成的 SST 缺口。新的向日葵-8 产品的预期效益包括提高 IMOS OceanCurrent 等应用的数据质量,以及调查近海岸地区的海洋热应力、海洋热浪和海洋上升流。
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
Remote Sensing
Remote Sensing REMOTE SENSING-
CiteScore
8.30
自引率
24.00%
发文量
5435
审稿时长
20.66 days
期刊介绍: Remote Sensing (ISSN 2072-4292) publishes regular research papers, reviews, letters and communications covering all aspects of the remote sensing process, from instrument design and signal processing to the retrieval of geophysical parameters and their application in geosciences. Our aim is to encourage scientists to publish experimental, theoretical and computational results in as much detail as possible so that results can be easily reproduced. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
期刊最新文献
Mapping Field-Level Maize Yields in Ethiopian Smallholder Systems Using Sentinel-2 Imagery Development of a Background Filtering Algorithm to Improve the Accuracy of Determining Underground Cavities Using Multi-Channel Ground-Penetrating Radar and Deep Learning Enhancing Digital Twins with Human Movement Data: A Comparative Study of Lidar-Based Tracking Methods Development of a UAS-Based Multi-Sensor Deep Learning Model for Predicting Napa Cabbage Fresh Weight and Determining Optimal Harvest Time Mini-Satellite Fucheng 1 SAR: Interferometry to Monitor Mining-Induced Subsidence and Comparative Analysis with Sentinel-1
×
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