Anthropogenic carbon release rate unprecedented during the past 66 million years

Journal name:
Nature Geoscience
Volume:
9,
Pages:
325–329
Year published:
DOI:
doi:10.1038/ngeo2681
Received
Accepted
Published online

Abstract

Carbon release rates from anthropogenic sources reached a record high of ~10Pg Cyr−1 in 2014. Geologic analogues from past transient climate changes could provide invaluable constraints on the response of the climate system to such perturbations, but only if the associated carbon release rates can be reliably reconstructed. The Palaeocene–Eocene Thermal Maximum (PETM) is known at present to have the highest carbon release rates of the past 66 million years, but robust estimates of the initial rate and onset duration are hindered by uncertainties in age models. Here we introduce a new method to extract rates of change from a sedimentary record based on the relative timing of climate and carbon cycle changes, without the need for an age model. We apply this method to stable carbon and oxygen isotope records from the New Jersey shelf using time-series analysis and carbon cycle–climate modelling. We calculate that the initial carbon release during the onset of the PETM occurred over at least 4,000 years. This constrains the maximum sustained PETM carbon release rate to less than 1.1Pg Cyr−1. We conclude that, given currently available records, the present anthropogenic carbon release rate is unprecedented during the past 66 million years. We suggest that such a ‘no-analogue state represents a fundamental challenge in constraining future climate projections. Also, future ecosystem disruptions are likely to exceed the relatively limited extinctions observed at the PETM.

At a glance

Figures

  1. Selected stable isotope records from New Jersey margin sections across the PETM onset.
    Figure 1: Selected stable isotope records from New Jersey margin sections across the PETM onset16, 20, 21, 23.

    a,b, Carbon (δ13C) (a) and oxygen (δ18O) (b) isotopes plotted versus position in core (the z = 0m alignment is arbitrary). Also, in the depth domain, the length of the onset interval cannot be compared between locations because of different sedimentation rates. Subb., species of Subbotina (planktonic foraminifer). Open (filled) diamonds indicate all (mean) Subb. values. Note that the Millville bulk isotope records are consistent with data from planktonic foraminifera at the same site22.

  2. Millville PETM records and time-series analysis.
    Figure 2: Millville PETM records and time-series analysis.

    a, Bulk stable carbon and oxygen isotopes (X,  δ13C; Y,  δ18O). Time runs to the right (oldest sample was assigned depth z = 0m). b, First-order differenced time series (x, y) and pre-whitened (filtered) series (x′, y′). See text for details. AR(6), autoregressive process of order six (see Supplementary Information). c, Leads/lags based on autocorrelation function (ACF) and cross-correlation function (CCF). Dashed horizontal lines, 95% confidence interval ( ; N, number of data points in the time series). After pre-whitening, CCFxy (grey squares) shows significant correlation only at Δk = 0 (contemporaneous) and at Δk = −6 (see text). d, Leads/lags between Millville δ13C (red) and δ18O (blue) at the start of the PETM onset. Arrows, apparent start based on superficial visual inspection; grey bars, range of pre-onset variability. Circles, first onset samples exceeding pre-onset variability; dashed lines, seven-point running means.

  3. Examples of model time lags ([tau]mod) as a function of model release time (tin).
    Figure 3: Examples of model time lags (τmod) as a function of model release time (tin).

    a,b, Lags are plotted for tin = 2,000yr (a) and tin = 4,000yr (b). indicates the maximum lead/lag allowed by the time-series analysis of the data records (see text). Note different time axes. All records and model output are normalized to % response. Simulated δ13C leads the model climate response at the onsets start because the models are forced by carbon input. In reality, temperature may have led carbon input initially5, 31, although the data do not support any significant δ18O lead at the start (Fig. 2d). Nevertheless, to avoid potential model bias during the initial onset phase, we determine τmod (arrows) as an average model lag, omitting the initial 40% of the normalized response (see Supplementary Information). The scenario shown in a is not feasible as τmod substantially exceeds τdat. Note that τdat is not to be determined from the raw (non-stationary) data records but from the first-order differenced and pre-whitened time series using cross-correlation (see text and Supplementary Information).

  4. Determining the minimum release time.
    Figure 4: Determining the minimum release time.

    Maximum lead/lag is based on data records (τdat) and model time lag (τmod) calculated using carbon cycle/climate models GENIE (ref. 12) and LOSCAR (refs 29,30), see text. The intercept of the shortest τmod and τdat yields the minimum onset interval consistent with the data (~4,000yr, black circle and arrow). The dashed purple lines illustrate potential uncertainties in τdat from variations in the onset length in the Millville core (zin ± 20%; however, see text and Supplementary Information). Standard model runs use 3,000Pg C carbon input and climate sensitivity S = 3K per CO2 doubling. Sensitivity of τmod was tested by varying the model release time (horizontal axis), total carbon input (open symbols: 2,000, 3,000, and 4,500Pg C), carbon release patterns (rate: up, down, noise), climate sensitivity (S), initial (pre-event) pCO2 (750–1,000ppmv), and atmospheric versus deep-ocean carbon injection (see Supplementary Information). NW Atl shelf represents GENIE grid-point output on the northwest Atlantic shelf corresponding to Millvilles palaeo-location (see Supplementary Information).

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Author information

Affiliations

  1. School of Ocean and Earth Science and Technology, University of Hawaii at Manoa, 1000 Pope Road, MSB 629, Honolulu, Hawaii 96822, USA

    • Richard E. Zeebe
  2. School of Geographical Sciences, University of Bristol, University Road, Bristol BS8 1SS, UK

    • Andy Ridgwell
  3. Department of Earth Sciences, University of California Riverside, 900 University Avenue, Riverside, California 92521, USA

    • Andy Ridgwell
  4. Earth and Planetary Sciences, University of California Santa Cruz, 1156 High Street, Santa Cruz, California 95064, USA

    • James C. Zachos

Contributions

R.E.Z. led the effort. All authors wrote the paper.

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The authors declare no competing financial interests.

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