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Tendencies, variability and persistence of sea surface temperature anomalies

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...

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Autores principales: Bulgin, Claire E., Merchant, Christopher J., Ferreira, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7224223/
https://www.ncbi.nlm.nih.gov/pubmed/32409718
http://dx.doi.org/10.1038/s41598-020-64785-9
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author Bulgin, Claire E.
Merchant, Christopher J.
Ferreira, David
author_facet Bulgin, Claire E.
Merchant, Christopher J.
Ferreira, David
author_sort Bulgin, Claire E.
collection PubMed
description 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.
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spelling pubmed-72242232020-05-20 Tendencies, variability and persistence of sea surface temperature anomalies Bulgin, Claire E. Merchant, Christopher J. Ferreira, David Sci Rep Article 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. Nature Publishing Group UK 2020-05-14 /pmc/articles/PMC7224223/ /pubmed/32409718 http://dx.doi.org/10.1038/s41598-020-64785-9 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Bulgin, Claire E.
Merchant, Christopher J.
Ferreira, David
Tendencies, variability and persistence of sea surface temperature anomalies
title 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_short Tendencies, variability and persistence of sea surface temperature anomalies
title_sort tendencies, variability and persistence of sea surface temperature anomalies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7224223/
https://www.ncbi.nlm.nih.gov/pubmed/32409718
http://dx.doi.org/10.1038/s41598-020-64785-9
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