4.7 Article

Atmospheric CO2 response to volcanic eruptions: The role of ENSO, season, and variability

Journal

GLOBAL BIOGEOCHEMICAL CYCLES
Volume 27, Issue 1, Pages 239-251

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/gbc.20028

Keywords

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Funding

  1. Carbon Mitigation Initiative project at Princeton University
  2. BP
  3. Swiss National Science Foundation
  4. National Centre of Competence in Research (NCCR) Climate
  5. European Project CARBOCHANGE [264879]

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Tropical explosive volcanism is one of the most important natural factors that significantly impact the climate system and the carbon cycle on annual to multi-decadal time scales. The three largest explosive eruptions in the last 50 years-Agung, El Chichon, and Pinatubo-occurred in spring/summer in conjunction with El Nino events and left distinct negative signals in the observational temperature and CO2 records. However, confounding factors such as seasonal variability and El Nino-Southern Oscillation (ENSO) may obscure the forcing-response relationship. We determine for the first time the extent to which initial conditions, i.e., season and phase of the ENSO, and internal variability influence the coupled climate and carbon cycle response to volcanic forcing and how this affects estimates of the terrestrial and oceanic carbon sinks. Ensemble simulations with the Earth System Model (Climate System Model 1.4-carbon) predict that the atmospheric CO2 response is (similar to)60% larger when a volcanic eruption occurs during El Nino and in winter than during La Nina conditions. Our simulations suggest that the Pinatubo eruption contributed 11 +/- 6% to the 25 Pg terrestrial carbon sink inferred over the decade 1990-1999 and -2 +/- 1% to the 22 Pg oceanic carbon sink. In contrast to recent claims, trends in the airborne fraction of anthropogenic carbon cannot be detected when accounting for the decadal-scale influence of explosive volcanism and related uncertainties. Our results highlight the importance of considering the role of natural variability in the carbon cycle for interpretation of observations and for data-model intercomparison.

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