Tendencies, variability and persistence of sea surface temperature anomalies

Abstract Quantifying global trends and variability in sea surface temperature (SST) is of fundamental importance to understanding changes in the Earth’s climate. One approach to observing SST is via remote sensing. Here we use a 37-year gap-filled, daily-mean analysis of satellite SSTs to quantify S...

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Published in:Scientific Reports
Main Authors: Bulgin, Claire E., Merchant, Christopher J., Ferreira, David
Format: Article in Journal/Newspaper
Language:English
Published: Springer Science and Business Media LLC 2020
Subjects:
Online Access:http://dx.doi.org/10.1038/s41598-020-64785-9
http://www.nature.com/articles/s41598-020-64785-9.pdf
http://www.nature.com/articles/s41598-020-64785-9
id crspringernat:10.1038/s41598-020-64785-9
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spelling crspringernat:10.1038/s41598-020-64785-9 2023-05-15T16:29:55+02:00 Tendencies, variability and persistence of sea surface temperature anomalies Bulgin, Claire E. Merchant, Christopher J. Ferreira, David 2020 http://dx.doi.org/10.1038/s41598-020-64785-9 http://www.nature.com/articles/s41598-020-64785-9.pdf http://www.nature.com/articles/s41598-020-64785-9 en eng Springer Science and Business Media LLC https://creativecommons.org/licenses/by/4.0 https://creativecommons.org/licenses/by/4.0 CC-BY Scientific Reports volume 10, issue 1 ISSN 2045-2322 Multidisciplinary journal-article 2020 crspringernat https://doi.org/10.1038/s41598-020-64785-9 2022-01-04T08:57:52Z Abstract Quantifying global trends and variability in sea surface temperature (SST) is of fundamental importance to understanding changes in the Earth’s climate. One approach to observing SST is via remote sensing. Here we use a 37-year gap-filled, daily-mean analysis of satellite SSTs to quantify SST trends, variability and persistence between 1981–2018. The global mean warming trend is 0.09 K per decade globally, with 95% of local trends being between −0.1 K and + 0.35 K. Excluding perennial sea-ice regions, the mean warming trend is 0.11 K per decade. After removing the long-term trend we calculate the SST power spectra over different time periods. The maximum variance in the SST power spectra in the equatorial Pacific is 1.9 K 2 on 1–5 year timescales, dominated by ENSO processes. In western boundary currents characterised by an intense mesoscale activity, SST power on sub-annual timescales dominates, with a maximum variance of 4.9 K 2 . Persistence timescales tend to be shorter in the summer hemisphere due to the shallower mixed layer. The median short-term persistence length is 11–14 days, found over 71–79% of the global ocean area, with seasonal variations. The mean global correlation between monthly SST anomalies with a three-month time-lag is 0.35, with statistically significant correlations over 54.0% of the global oceans, and notably in the northern and equatorial Pacific, and the sub-polar gyre south of Greenland. At six months, the mean global SST anomaly correlation falls to 0.18. The satellite data record enables the detailed characterisation of temporal changes in SST over almost four decades. Article in Journal/Newspaper Greenland Sea ice Springer Nature (via Crossref) Greenland Pacific Scientific Reports 10 1
institution Open Polar
collection Springer Nature (via Crossref)
op_collection_id crspringernat
language English
topic Multidisciplinary
spellingShingle Multidisciplinary
Bulgin, Claire E.
Merchant, Christopher J.
Ferreira, David
Tendencies, variability and persistence of sea surface temperature anomalies
topic_facet Multidisciplinary
description Abstract Quantifying global trends and variability in sea surface temperature (SST) is of fundamental importance to understanding changes in the Earth’s climate. One approach to observing SST is via remote sensing. Here we use a 37-year gap-filled, daily-mean analysis of satellite SSTs to quantify SST trends, variability and persistence between 1981–2018. The global mean warming trend is 0.09 K per decade globally, with 95% of local trends being between −0.1 K and + 0.35 K. Excluding perennial sea-ice regions, the mean warming trend is 0.11 K per decade. After removing the long-term trend we calculate the SST power spectra over different time periods. The maximum variance in the SST power spectra in the equatorial Pacific is 1.9 K 2 on 1–5 year timescales, dominated by ENSO processes. In western boundary currents characterised by an intense mesoscale activity, SST power on sub-annual timescales dominates, with a maximum variance of 4.9 K 2 . Persistence timescales tend to be shorter in the summer hemisphere due to the shallower mixed layer. The median short-term persistence length is 11–14 days, found over 71–79% of the global ocean area, with seasonal variations. The mean global correlation between monthly SST anomalies with a three-month time-lag is 0.35, with statistically significant correlations over 54.0% of the global oceans, and notably in the northern and equatorial Pacific, and the sub-polar gyre south of Greenland. At six months, the mean global SST anomaly correlation falls to 0.18. The satellite data record enables the detailed characterisation of temporal changes in SST over almost four decades.
format Article in Journal/Newspaper
author Bulgin, Claire E.
Merchant, Christopher J.
Ferreira, David
author_facet Bulgin, Claire E.
Merchant, Christopher J.
Ferreira, David
author_sort Bulgin, Claire E.
title Tendencies, variability and persistence of sea surface temperature anomalies
title_short Tendencies, variability and persistence of sea surface temperature anomalies
title_full Tendencies, variability and persistence of sea surface temperature anomalies
title_fullStr Tendencies, variability and persistence of sea surface temperature anomalies
title_full_unstemmed Tendencies, variability and persistence of sea surface temperature anomalies
title_sort tendencies, variability and persistence of sea surface temperature anomalies
publisher Springer Science and Business Media LLC
publishDate 2020
url http://dx.doi.org/10.1038/s41598-020-64785-9
http://www.nature.com/articles/s41598-020-64785-9.pdf
http://www.nature.com/articles/s41598-020-64785-9
geographic Greenland
Pacific
geographic_facet Greenland
Pacific
genre Greenland
Sea ice
genre_facet Greenland
Sea ice
op_source Scientific Reports
volume 10, issue 1
ISSN 2045-2322
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https://creativecommons.org/licenses/by/4.0
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op_doi https://doi.org/10.1038/s41598-020-64785-9
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