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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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 |
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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 |
op_rights |
https://creativecommons.org/licenses/by/4.0 https://creativecommons.org/licenses/by/4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1038/s41598-020-64785-9 |
container_title |
Scientific Reports |
container_volume |
10 |
container_issue |
1 |
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1766019626786881536 |