Weak Mesoscale Variability in the Optimum Interpolation Sea Surface Temperature (OISST)-AVHRR-Only Version 2 Data before 2007
Mesoscale sea surface temperature (SST) variability triggers mesoscale air-sea interactions and is linked to ocean subsurface mesoscale dynamics. The National Oceanic and Atmospheric Administration (NOAA) daily Optimum Interpolation SST (OISST) products, based on various satellite and in situ SST da...
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Online Access: | http://ir.qdio.ac.cn/handle/337002/178136 https://doi.org/10.3390/rs14020409 |
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ftchinacasciocas:oai:ir.qdio.ac.cn:337002/178136 2023-05-15T18:25:58+02:00 Weak Mesoscale Variability in the Optimum Interpolation Sea Surface Temperature (OISST)-AVHRR-Only Version 2 Data before 2007 Zhu, Yanan Li, Yuanlong Wang, Fan Lv, Mingkun 2022 http://ir.qdio.ac.cn/handle/337002/178136 https://doi.org/10.3390/rs14020409 英语 eng MDPI REMOTE SENSING http://ir.qdio.ac.cn/handle/337002/178136 doi:10.3390/rs14020409 mesoscale eddies mesoscale air-sea interaction mesoscale SST anomalies OISST data western boundary current Environmental Sciences & Ecology Geology Remote Sensing Imaging Science & Photographic Technology Environmental Sciences Geosciences Multidisciplinary SATELLITE-OBSERVATIONS SOUTHERN-OCEAN NORTH PACIFIC GULF-STREAM EDDIES KUROSHIO SUBSURFACE HEAT TRANSPORT DEPENDENCE 期刊论文 2022 ftchinacasciocas https://doi.org/10.3390/rs14020409 2022-06-27T05:46:45Z Mesoscale sea surface temperature (SST) variability triggers mesoscale air-sea interactions and is linked to ocean subsurface mesoscale dynamics. The National Oceanic and Atmospheric Administration (NOAA) daily Optimum Interpolation SST (OISST) products, based on various satellite and in situ SST data, are widely utilized in the investigation of multi-scale SST variabilities and reconstruction of subsurface and deep-ocean fields. The quality of OISST datasets is subjected to temporal inhomogeneity due to alterations in the merged data. Yet, whether this issue can significantly affect mesoscale SST variability is unknown. The analysis of this study detects an abrupt enhancement of mesoscale SST variability after 2007 in the OISST-AVHRR-only version 2 and version 2.1 datasets (hereafter OI.v2-AVHRR-only and OI.v2.1-AVHRR-only). The contrast is most stark in the subtropical western boundary current (WBC) regions, where the average mesoscale SST variance during 2007-2018 is twofold larger than that during 1993-2006. Further comparisons with other satellite SST datasets (TMI, AMSR-E, and WindSAT) suggest that the OISST-AVHRR-only datasets have severely underestimated mesoscale SST variability before 2007. An evaluation of related documents of the OISST data indicates that this bias is mainly caused by the change of satellite AVHRR instrument in 2007. There are no corresponding changes detected in the associated fields, such as the number and activity of mesoscale eddies or the background SST gradient in these regions, confirming that the underestimation of mesoscale SST variability before 2007 is an artifact. Another OISST product, OI.v2-AVHRR-AMSR, shows a similar abrupt enhancement of mesoscale SST variability in June 2002, when the AMSR-E instrument was incorporated. This issue leaves potential influences on scientific research that utilize the OISST datasets. The composite SST anomalies of mesoscale eddies based on the OI.v2-AVHRR-only data are underestimated by up to 37% before 2007 in the subtropical WBC ... Report Southern Ocean Institute of Oceanology, Chinese Academy of Sciences: IOCAS-IR Southern Ocean Pacific Remote Sensing 14 2 409 |
institution |
Open Polar |
collection |
Institute of Oceanology, Chinese Academy of Sciences: IOCAS-IR |
op_collection_id |
ftchinacasciocas |
language |
English |
topic |
mesoscale eddies mesoscale air-sea interaction mesoscale SST anomalies OISST data western boundary current Environmental Sciences & Ecology Geology Remote Sensing Imaging Science & Photographic Technology Environmental Sciences Geosciences Multidisciplinary SATELLITE-OBSERVATIONS SOUTHERN-OCEAN NORTH PACIFIC GULF-STREAM EDDIES KUROSHIO SUBSURFACE HEAT TRANSPORT DEPENDENCE |
spellingShingle |
mesoscale eddies mesoscale air-sea interaction mesoscale SST anomalies OISST data western boundary current Environmental Sciences & Ecology Geology Remote Sensing Imaging Science & Photographic Technology Environmental Sciences Geosciences Multidisciplinary SATELLITE-OBSERVATIONS SOUTHERN-OCEAN NORTH PACIFIC GULF-STREAM EDDIES KUROSHIO SUBSURFACE HEAT TRANSPORT DEPENDENCE Zhu, Yanan Li, Yuanlong Wang, Fan Lv, Mingkun Weak Mesoscale Variability in the Optimum Interpolation Sea Surface Temperature (OISST)-AVHRR-Only Version 2 Data before 2007 |
topic_facet |
mesoscale eddies mesoscale air-sea interaction mesoscale SST anomalies OISST data western boundary current Environmental Sciences & Ecology Geology Remote Sensing Imaging Science & Photographic Technology Environmental Sciences Geosciences Multidisciplinary SATELLITE-OBSERVATIONS SOUTHERN-OCEAN NORTH PACIFIC GULF-STREAM EDDIES KUROSHIO SUBSURFACE HEAT TRANSPORT DEPENDENCE |
description |
Mesoscale sea surface temperature (SST) variability triggers mesoscale air-sea interactions and is linked to ocean subsurface mesoscale dynamics. The National Oceanic and Atmospheric Administration (NOAA) daily Optimum Interpolation SST (OISST) products, based on various satellite and in situ SST data, are widely utilized in the investigation of multi-scale SST variabilities and reconstruction of subsurface and deep-ocean fields. The quality of OISST datasets is subjected to temporal inhomogeneity due to alterations in the merged data. Yet, whether this issue can significantly affect mesoscale SST variability is unknown. The analysis of this study detects an abrupt enhancement of mesoscale SST variability after 2007 in the OISST-AVHRR-only version 2 and version 2.1 datasets (hereafter OI.v2-AVHRR-only and OI.v2.1-AVHRR-only). The contrast is most stark in the subtropical western boundary current (WBC) regions, where the average mesoscale SST variance during 2007-2018 is twofold larger than that during 1993-2006. Further comparisons with other satellite SST datasets (TMI, AMSR-E, and WindSAT) suggest that the OISST-AVHRR-only datasets have severely underestimated mesoscale SST variability before 2007. An evaluation of related documents of the OISST data indicates that this bias is mainly caused by the change of satellite AVHRR instrument in 2007. There are no corresponding changes detected in the associated fields, such as the number and activity of mesoscale eddies or the background SST gradient in these regions, confirming that the underestimation of mesoscale SST variability before 2007 is an artifact. Another OISST product, OI.v2-AVHRR-AMSR, shows a similar abrupt enhancement of mesoscale SST variability in June 2002, when the AMSR-E instrument was incorporated. This issue leaves potential influences on scientific research that utilize the OISST datasets. The composite SST anomalies of mesoscale eddies based on the OI.v2-AVHRR-only data are underestimated by up to 37% before 2007 in the subtropical WBC ... |
format |
Report |
author |
Zhu, Yanan Li, Yuanlong Wang, Fan Lv, Mingkun |
author_facet |
Zhu, Yanan Li, Yuanlong Wang, Fan Lv, Mingkun |
author_sort |
Zhu, Yanan |
title |
Weak Mesoscale Variability in the Optimum Interpolation Sea Surface Temperature (OISST)-AVHRR-Only Version 2 Data before 2007 |
title_short |
Weak Mesoscale Variability in the Optimum Interpolation Sea Surface Temperature (OISST)-AVHRR-Only Version 2 Data before 2007 |
title_full |
Weak Mesoscale Variability in the Optimum Interpolation Sea Surface Temperature (OISST)-AVHRR-Only Version 2 Data before 2007 |
title_fullStr |
Weak Mesoscale Variability in the Optimum Interpolation Sea Surface Temperature (OISST)-AVHRR-Only Version 2 Data before 2007 |
title_full_unstemmed |
Weak Mesoscale Variability in the Optimum Interpolation Sea Surface Temperature (OISST)-AVHRR-Only Version 2 Data before 2007 |
title_sort |
weak mesoscale variability in the optimum interpolation sea surface temperature (oisst)-avhrr-only version 2 data before 2007 |
publisher |
MDPI |
publishDate |
2022 |
url |
http://ir.qdio.ac.cn/handle/337002/178136 https://doi.org/10.3390/rs14020409 |
geographic |
Southern Ocean Pacific |
geographic_facet |
Southern Ocean Pacific |
genre |
Southern Ocean |
genre_facet |
Southern Ocean |
op_relation |
REMOTE SENSING http://ir.qdio.ac.cn/handle/337002/178136 doi:10.3390/rs14020409 |
op_doi |
https://doi.org/10.3390/rs14020409 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
2 |
container_start_page |
409 |
_version_ |
1766207714194620416 |