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Time of Emergence and Large Ensemble Intercomparison for Ocean Biogeochemical Trends
Anthropogenically forced changes in ocean biogeochemistry are underway and critical for the ocean carbon sink and marine habitat. Detecting such changes in ocean biogeochemistry will require quantification of the magnitude of the change (anthropogenic signal) and the natural variability inherent to...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507776/ https://www.ncbi.nlm.nih.gov/pubmed/32999530 http://dx.doi.org/10.1029/2019GB006453 |
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author | Schlunegger, Sarah Rodgers, Keith B. Sarmiento, Jorge L. Ilyina, Tatiana Dunne, John P. Takano, Yohei Christian, James R. Long, Matthew C. Frölicher, Thomas L. Slater, Richard Lehner, Flavio |
author_facet | Schlunegger, Sarah Rodgers, Keith B. Sarmiento, Jorge L. Ilyina, Tatiana Dunne, John P. Takano, Yohei Christian, James R. Long, Matthew C. Frölicher, Thomas L. Slater, Richard Lehner, Flavio |
author_sort | Schlunegger, Sarah |
collection | PubMed |
description | Anthropogenically forced changes in ocean biogeochemistry are underway and critical for the ocean carbon sink and marine habitat. Detecting such changes in ocean biogeochemistry will require quantification of the magnitude of the change (anthropogenic signal) and the natural variability inherent to the climate system (noise). Here we use Large Ensemble (LE) experiments from four Earth system models (ESMs) with multiple emissions scenarios to estimate Time of Emergence (ToE) and partition projection uncertainty for anthropogenic signals in five biogeochemically important upper‐ocean variables. We find ToEs are robust across ESMs for sea surface temperature and the invasion of anthropogenic carbon; emergence time scales are 20–30 yr. For the biological carbon pump, and sea surface chlorophyll and salinity, emergence time scales are longer (50+ yr), less robust across the ESMs, and more sensitive to the forcing scenario considered. We find internal variability uncertainty, and model differences in the internal variability uncertainty, can be consequential sources of uncertainty for projecting regional changes in ocean biogeochemistry over the coming decades. In combining structural, scenario, and internal variability uncertainty, this study represents the most comprehensive characterization of biogeochemical emergence time scales and uncertainty to date. Our findings delineate critical spatial and duration requirements for marine observing systems to robustly detect anthropogenic change. |
format | Online Article Text |
id | pubmed-7507776 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75077762020-09-28 Time of Emergence and Large Ensemble Intercomparison for Ocean Biogeochemical Trends Schlunegger, Sarah Rodgers, Keith B. Sarmiento, Jorge L. Ilyina, Tatiana Dunne, John P. Takano, Yohei Christian, James R. Long, Matthew C. Frölicher, Thomas L. Slater, Richard Lehner, Flavio Global Biogeochem Cycles Research Articles Anthropogenically forced changes in ocean biogeochemistry are underway and critical for the ocean carbon sink and marine habitat. Detecting such changes in ocean biogeochemistry will require quantification of the magnitude of the change (anthropogenic signal) and the natural variability inherent to the climate system (noise). Here we use Large Ensemble (LE) experiments from four Earth system models (ESMs) with multiple emissions scenarios to estimate Time of Emergence (ToE) and partition projection uncertainty for anthropogenic signals in five biogeochemically important upper‐ocean variables. We find ToEs are robust across ESMs for sea surface temperature and the invasion of anthropogenic carbon; emergence time scales are 20–30 yr. For the biological carbon pump, and sea surface chlorophyll and salinity, emergence time scales are longer (50+ yr), less robust across the ESMs, and more sensitive to the forcing scenario considered. We find internal variability uncertainty, and model differences in the internal variability uncertainty, can be consequential sources of uncertainty for projecting regional changes in ocean biogeochemistry over the coming decades. In combining structural, scenario, and internal variability uncertainty, this study represents the most comprehensive characterization of biogeochemical emergence time scales and uncertainty to date. Our findings delineate critical spatial and duration requirements for marine observing systems to robustly detect anthropogenic change. John Wiley and Sons Inc. 2020-08-23 2020-08 /pmc/articles/PMC7507776/ /pubmed/32999530 http://dx.doi.org/10.1029/2019GB006453 Text en ©2020. The Authors. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Schlunegger, Sarah Rodgers, Keith B. Sarmiento, Jorge L. Ilyina, Tatiana Dunne, John P. Takano, Yohei Christian, James R. Long, Matthew C. Frölicher, Thomas L. Slater, Richard Lehner, Flavio Time of Emergence and Large Ensemble Intercomparison for Ocean Biogeochemical Trends |
title | Time of Emergence and Large Ensemble Intercomparison for Ocean Biogeochemical Trends |
title_full | Time of Emergence and Large Ensemble Intercomparison for Ocean Biogeochemical Trends |
title_fullStr | Time of Emergence and Large Ensemble Intercomparison for Ocean Biogeochemical Trends |
title_full_unstemmed | Time of Emergence and Large Ensemble Intercomparison for Ocean Biogeochemical Trends |
title_short | Time of Emergence and Large Ensemble Intercomparison for Ocean Biogeochemical Trends |
title_sort | time of emergence and large ensemble intercomparison for ocean biogeochemical trends |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507776/ https://www.ncbi.nlm.nih.gov/pubmed/32999530 http://dx.doi.org/10.1029/2019GB006453 |
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