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学術論文

Opportunities for Earth Observation to Inform Risk Management for Ocean Tipping Points

Authors

Wood,  Richard A.
External Organizations;

Baker,  Jonathan A.
External Organizations;

Beaugrand,  Grégory
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Boutin,  Jacqueline
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Conversi,  Alessandra
External Organizations;

/persons/resource/Reik.Donner

Donner,  Reik V.
Potsdam Institute for Climate Impact Research;

Frenger,  Ivy
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Goberville,  Eric
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Hayashida,  Hakase
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Koeve,  Wolfgang
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Kvale,  Karin
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Landolfi,  Angela
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Maslowski,  Wieslaw
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Oschlies,  Andreas
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Romanou,  Anastasia
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Somes,  Christopher J.
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Stocker,  Thomas F.
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Swingedouw,  Didier
External Organizations;

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フルテキスト (公開)

31561oa.pdf
(出版社版), 3MB

付随資料 (公開)
There is no public supplementary material available
引用

Wood, R. A., Baker, J. A., Beaugrand, G., Boutin, J., Conversi, A., Donner, R. V., Frenger, I., Goberville, E., Hayashida, H., Koeve, W., Kvale, K., Landolfi, A., Maslowski, W., Oschlies, A., Romanou, A., Somes, C. J., Stocker, T. F., & Swingedouw, D. (2024). Opportunities for Earth Observation to Inform Risk Management for Ocean Tipping Points. Surveys in Geophysics. doi:10.1007/s10712-024-09859-3.


引用: https://publications.pik-potsdam.de/pubman/item/item_31561
要旨
As climate change continues, the likelihood of passing critical thresholds or tipping points increases. Hence, there is a need to advance the science for detecting such thresholds. In this paper, we assess the needs and opportunities for Earth Observation (EO, here understood to refer to satellite observations) to inform society in responding to the risks associated with ten potential large-scale ocean tipping elements: Atlantic Meridional Overturning Circulation; Atlantic Subpolar Gyre; Beaufort Gyre; Arctic halocline; Kuroshio Large Meander; deoxygenation; phytoplankton; zooplankton; higher level ecosystems (including fisheries); and marine biodiversity. We review current scientific understanding and identify specific EO and related modelling needs for each of these tipping elements. We draw out some generic points that apply across several of the elements. These common points include the importance of maintaining long-term, consistent time series; the need to combine EO data consistently with in situ data types (including subsurface), for example through data assimilation; and the need to reduce or work with current mismatches in resolution (in both directions) between climate models and EO datasets. Our analysis shows that developing EO, modelling and prediction systems together, with understanding of the strengths and limitations of each, provides many promising paths towards monitoring and early warning systems for tipping, and towards the development of the next generation of climate models.