Evidence map›Paper›PMID 32999530›Full record

ArticleGlobal biogeochemical cycles2020

Time of Emergence and Large Ensemble Intercomparison for Ocean Biogeochemical Trends.

Sarah Schlunegger, Keith B Rodgers, Jorge L Sarmiento, Tatiana Ilyina, John P Dunne, Yohei Takano, James R Christian, Matthew C Long, Thomas L Frölicher, Richard Slater and 1 more

Abstract read
In one paragraph

Article in Global biogeochemical cycles, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Emergence time of COScientific reports · 2026
    Article
  2. Long-term declines in chlorophyllProceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Sarah SchluneggerProgram in Atmospheric and Oceanic Sciences Princeton University Princeton NJ USA.ORCID https://orcid.org/0000-0002-6668-9088
Keith B RodgersProgram in Atmospheric and Oceanic Sciences Princeton University Princeton NJ USA.ORCID https://orcid.org/0000-0002-6465-8923
Jorge L SarmientoProgram in Atmospheric and Oceanic Sciences Princeton University Princeton NJ USA.ORCID https://orcid.org/0000-0001-5219-2604
Tatiana IlyinaMax Plank Institute for Meteorology Hamburg Germany.ORCID https://orcid.org/0000-0002-3475-4842
John P DunneNOAA Geophysical Fluid Dynamics Laboratory Princeton NJ USA.ORCID https://orcid.org/0000-0002-8794-0489
Yohei TakanoMax Plank Institute for Meteorology Hamburg Germany.ORCID https://orcid.org/0000-0001-7984-8810
James R ChristianCanadian Center for Climate Modeling and Analysis Victoria British Columbia Canada.
Matthew C LongNational Center for Atmospheric Research Boulder CO USA.ORCID https://orcid.org/0000-0003-1273-2957
Thomas L FrölicherClimate and Environmental Physics, Physics Institute University of Bern Bern Switzerland.ORCID https://orcid.org/0000-0003-2348-7854
Richard SlaterProgram in Atmospheric and Oceanic Sciences Princeton University Princeton NJ USA.ORCID https://orcid.org/0000-0001-8868-1338
Flavio LehnerNational Center for Atmospheric Research Boulder CO USA.ORCID https://orcid.org/0000-0003-4632-9701

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

anthropogenic trendsEarth system modelsmodel intercomparisonocean biogeochemistryTime of Emergenceuncertainty quantification

Identifiers

PMID32999530
PMCPMC7507776

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.