Interannual variability in the oxygen isotopes of atmospheric CO2 driven by El Niño

Journal name:
Nature
Volume:
477,
Pages:
579–582
Date published:
DOI:
doi:10.1038/nature10421
Received
Accepted
Published online

The stable isotope ratios of atmospheric CO2 (18O/16O and 13C/12C) have been monitored since 1977 to improve our understanding of the global carbon cycle, because biosphere–atmosphere exchange fluxes affect the different atomic masses in a measurable way1. Interpreting the 18O/16O variability has proved difficult, however, because oxygen isotopes in CO2 are influenced by both the carbon cycle and the water cycle2. Previous attention focused on the decreasing 18O/16O ratio in the 1990s, observed by the global Cooperative Air Sampling Network of the US National Oceanic and Atmospheric Administration Earth System Research Laboratory. This decrease was attributed variously to a number of processes including an increase in Northern Hemisphere soil respiration3; a global increase in C4 crops at the expense of C3 forests4; and environmental conditions, such as atmospheric turbulence5 and solar radiation6, that affect CO2 exchange between leaves and the atmosphere. Here we present 30 years’ worth of data on 18O/16O in CO2 from the Scripps Institution of Oceanography global flask network and show that the interannual variability is strongly related to the El Niño/Southern Oscillation. We suggest that the redistribution of moisture and rainfall in the tropics during an El Niño increases the 18O/16O ratio of precipitation and plant water, and that this signal is then passed on to atmospheric CO2 by biosphere–atmosphere gas exchange. We show how the decay time of the El Niño anomaly in this data set can be useful in constraining global gross primary production. Our analysis shows a rapid recovery from El Niño events, implying a shorter cycling time of CO2 with respect to the terrestrial biosphere and oceans than previously estimated. Our analysis suggests that current estimates of global gross primary production, of 120 petagrams of carbon per year7, may be too low, and that a best guess of 150–175 petagrams of carbon per year better reflects the observed rapid cycling of CO2. Although still tentative, such a revision would present a new benchmark by which to evaluate global biospheric carbon cycling models.

At a glance

Figures

  1. Measurements of [dgr]18O-CO2 from the SIO flask network and CSIRO.
    Figure 1: Measurements of δ18O-CO2 from the SIO flask network and CSIRO.

    Monthly mean deseasonalized δ18O-CO2 station data (black dots) with long-term spline fits (grey lines). All stations (latitude, longitude and altitude as shown) are from the SIO flask network with the exception of the CSIRO station CGO, at the bottom of the figure. A seasonal harmonic fit was subtracted from the monthly means to produce the deseasonalized observations presented here. The 1σ mass spectrometer precision of both laboratories since 1990 is ~0.014‰. The SIO estimates that the 1σ error of duplicate flask measurements is ~0.025‰. Measurement uncertainties for both laboratories are larger before 1990.

  2. Correlations between precipitation [dgr]18O from IsoGSM and ENSO.
    Figure 2: Correlations between precipitation δ18O from IsoGSM and ENSO.

    We use the ENSO precipitation index (ESPI) as a proxy for ENSO variability. Positive correlation indicates that precipitation is enriched in 18O during the El Niño phase.

  3. Correlations between flask [dgr]18O-CO2 records and precipitation [dgr]18O and relative humidity from IsoGSM.
    Figure 3: Correlations between flask δ18O-CO2 records and precipitation δ18O and relative humidity from IsoGSM.

    a, b, Correlation between the previous 9-month running mean of precipitation δ18O and the monthly mean deseasonalized δ18O-CO2 from station MLO (a) and station SPO (b). Positive correlations indicate that δ18O-CO2 increases when precipitation δ18O increases. c, d, Correlation between the NPP-weighted, 9-month running mean of negative relative humidity and deseasonalized δ18O-CO2 from MLO (c) and SPO (d). Positive correlations indicate that δ18O-CO2 increases when relative humidity decreases. NPP-weighted relative humidity was used here to give weight to months with higher vegetation productivity when leaf-water isotope anomalies are passed onto CO2.

  4. ENSO index and two-box model results.
    Figure 4: ENSO index and two-box model results.

    a, ESPI was used as a proxy for ENSO variability. Arrows denote El Niño events. b, Empirical ENSO model fit for the Northern Hemisphere (δN, black line), compared with the deseasonalized monthly flask observations (black dots) and spline fit or interannual variability at station MLO (grey line). c, Same as in b but for the Southern Hemisphere model fit (δS) and station SPO.

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Author information

Affiliations

  1. Scripps Institution of Oceanography, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093-0244, USA

    • Lisa R. Welp,
    • Ralph F. Keeling,
    • Alane F. Bollenbacher,
    • Stephen C. Piper,
    • Kei Yoshimura &
    • Martin Wahlen
  2. Center for Isotope Research, University of Groningen, Nijenborgh 4, 9747 AG Groningen, The Netherlands

    • Harro A. J. Meijer
  3. CSIRO Marine and Atmospheric Research, PB 1, Aspendale, Victoria 3195, Australia

    • Roger J. Francey &
    • Colin E. Allison
  4. Present address: Atmosphere and Ocean Research Institute, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8568, Japan.

    • Kei Yoshimura

Contributions

L.R.W. analysed the data. R.F.K. supervised the project. L.R.W. and R.F.K. wrote the paper. H.A.J.M., A.F.B., R.J.F., C.E.A. and M.W. provided data. K.Y. provided the IsoGSM output. All authors discussed the results and commented on the manuscript.

Competing financial interests

The authors declare no competing financial interests.

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  1. Supplementary Information (1.5M)

    This file contains Supplementary Text 1-6, which includes a Supplementary Discussion and Supplementary Methods, Supplementary References, Supplementary Figure 1 with a legend and Supplementary Tables 1-3.

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