Uncertainty in Atlantic Multidecadal Oscillation derived from different observed datasets and their possible causes

As a leading mode of sea surface temperature (SST) variability over the North Atlantic in both observations and model simulations, the Atlantic Multidecadal Oscillation (AMO) can have a substantial influence on regional and global climate. By using Low-Frequency Component Analysis, we explore the un...

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Published in:Frontiers in Marine Science
Main Authors: Bowen Zhao, Pengfei Lin, Aixue Hu, Hailong Liu, Mengrong Ding, Zipeng Yu, Yongqiang Yu
Format: Article in Journal/Newspaper
Language:English
Published: Frontiers Media S.A. 2022
Subjects:
Q
Online Access:https://doi.org/10.3389/fmars.2022.1007646
https://doaj.org/article/169be57efceb4522b05cc4ca96dc9040
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spelling ftdoajarticles:oai:doaj.org/article:169be57efceb4522b05cc4ca96dc9040 2023-05-15T17:28:34+02:00 Uncertainty in Atlantic Multidecadal Oscillation derived from different observed datasets and their possible causes Bowen Zhao Pengfei Lin Aixue Hu Hailong Liu Mengrong Ding Zipeng Yu Yongqiang Yu 2022-10-01T00:00:00Z https://doi.org/10.3389/fmars.2022.1007646 https://doaj.org/article/169be57efceb4522b05cc4ca96dc9040 EN eng Frontiers Media S.A. https://www.frontiersin.org/articles/10.3389/fmars.2022.1007646/full https://doaj.org/toc/2296-7745 2296-7745 doi:10.3389/fmars.2022.1007646 https://doaj.org/article/169be57efceb4522b05cc4ca96dc9040 Frontiers in Marine Science, Vol 9 (2022) AMO pattern coherence warming trend bias-adjustment sampling size Science Q General. Including nature conservation geographical distribution QH1-199.5 article 2022 ftdoajarticles https://doi.org/10.3389/fmars.2022.1007646 2022-12-30T22:56:45Z As a leading mode of sea surface temperature (SST) variability over the North Atlantic in both observations and model simulations, the Atlantic Multidecadal Oscillation (AMO) can have a substantial influence on regional and global climate. By using Low-Frequency Component Analysis, we explore the uncertainties of the resulting AMO indices and the corresponding spatial patterns derived from three observational SST datasets. We found that the known coherent spatial pattern of the AMO at the basin scale over the North Atlantic appears in two out of the three datasets. Further analysis indicates that both the warming trend and the different techniques used to construct these observed gridded SSTs contribute to the AMO’s spatial coherence over the North Atlantic, especially during periods of sparse data sampling. The SST in the Extended Reconstructed SST dataset version 5 (ERSSTv5), changes from being systematically below the other datasets during the dense sampling periods on either side of the Second World War (WWII), to systematically above the other datasets during WWII, thereby introducing an artificial 10–20-year variability that affects the AMO’s spatial coherence. This coherence in the AMO’s spatial pattern is also affected by bias adjustment in ERSSTv5 at relative cool (i.e., non-summer) seasons, and by the heterogeneous North Atlantic warming pattern. The different AMO patterns can induce the different effects of wind, surface heat fluxes, and then drive ocean circulation and its heat transport convergence, especially for some seasons. For AMO indices, both the different detrending methods and different observational data result in uncertainty for the period 1935–1950. Such SST uncertainty is important to detect the relative role of the atmosphere and ocean in shaping the AMO. Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Frontiers in Marine Science 9
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic AMO pattern
coherence
warming trend
bias-adjustment
sampling size
Science
Q
General. Including nature conservation
geographical distribution
QH1-199.5
spellingShingle AMO pattern
coherence
warming trend
bias-adjustment
sampling size
Science
Q
General. Including nature conservation
geographical distribution
QH1-199.5
Bowen Zhao
Pengfei Lin
Aixue Hu
Hailong Liu
Mengrong Ding
Zipeng Yu
Yongqiang Yu
Uncertainty in Atlantic Multidecadal Oscillation derived from different observed datasets and their possible causes
topic_facet AMO pattern
coherence
warming trend
bias-adjustment
sampling size
Science
Q
General. Including nature conservation
geographical distribution
QH1-199.5
description As a leading mode of sea surface temperature (SST) variability over the North Atlantic in both observations and model simulations, the Atlantic Multidecadal Oscillation (AMO) can have a substantial influence on regional and global climate. By using Low-Frequency Component Analysis, we explore the uncertainties of the resulting AMO indices and the corresponding spatial patterns derived from three observational SST datasets. We found that the known coherent spatial pattern of the AMO at the basin scale over the North Atlantic appears in two out of the three datasets. Further analysis indicates that both the warming trend and the different techniques used to construct these observed gridded SSTs contribute to the AMO’s spatial coherence over the North Atlantic, especially during periods of sparse data sampling. The SST in the Extended Reconstructed SST dataset version 5 (ERSSTv5), changes from being systematically below the other datasets during the dense sampling periods on either side of the Second World War (WWII), to systematically above the other datasets during WWII, thereby introducing an artificial 10–20-year variability that affects the AMO’s spatial coherence. This coherence in the AMO’s spatial pattern is also affected by bias adjustment in ERSSTv5 at relative cool (i.e., non-summer) seasons, and by the heterogeneous North Atlantic warming pattern. The different AMO patterns can induce the different effects of wind, surface heat fluxes, and then drive ocean circulation and its heat transport convergence, especially for some seasons. For AMO indices, both the different detrending methods and different observational data result in uncertainty for the period 1935–1950. Such SST uncertainty is important to detect the relative role of the atmosphere and ocean in shaping the AMO.
format Article in Journal/Newspaper
author Bowen Zhao
Pengfei Lin
Aixue Hu
Hailong Liu
Mengrong Ding
Zipeng Yu
Yongqiang Yu
author_facet Bowen Zhao
Pengfei Lin
Aixue Hu
Hailong Liu
Mengrong Ding
Zipeng Yu
Yongqiang Yu
author_sort Bowen Zhao
title Uncertainty in Atlantic Multidecadal Oscillation derived from different observed datasets and their possible causes
title_short Uncertainty in Atlantic Multidecadal Oscillation derived from different observed datasets and their possible causes
title_full Uncertainty in Atlantic Multidecadal Oscillation derived from different observed datasets and their possible causes
title_fullStr Uncertainty in Atlantic Multidecadal Oscillation derived from different observed datasets and their possible causes
title_full_unstemmed Uncertainty in Atlantic Multidecadal Oscillation derived from different observed datasets and their possible causes
title_sort uncertainty in atlantic multidecadal oscillation derived from different observed datasets and their possible causes
publisher Frontiers Media S.A.
publishDate 2022
url https://doi.org/10.3389/fmars.2022.1007646
https://doaj.org/article/169be57efceb4522b05cc4ca96dc9040
genre North Atlantic
genre_facet North Atlantic
op_source Frontiers in Marine Science, Vol 9 (2022)
op_relation https://www.frontiersin.org/articles/10.3389/fmars.2022.1007646/full
https://doaj.org/toc/2296-7745
2296-7745
doi:10.3389/fmars.2022.1007646
https://doaj.org/article/169be57efceb4522b05cc4ca96dc9040
op_doi https://doi.org/10.3389/fmars.2022.1007646
container_title Frontiers in Marine Science
container_volume 9
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