An important part of natural carbon-climate variability is caused by volcanic eruptions both during recent decades and during the preindustrial period. While the direct radiative and dynamical effects of sulfate aerosols from volcanic eruptions on the physical climate system are relatively well known, less emphasis has been placed on investigating the impact of volcanic eruptions on the global carbon cycle and variability in the atmospheric CO2 record.
(a) Prescribed zonal averaged stratospheric optical depth in the mid-visible wavelength for the Pin.1x case. (b–f) Global mean responses of the carbon cycle-climate system to different strengths of volcanic eruptions: time series of monthly (b) net surface solar flux, (c) atmospheric surface temperature, (d) atmospheric CO2 concentration, (e) land carbon inventory and (f) ocean carbon inventory (sum of dissolved inorganic and organic carbon). In all plots in (b–f) and for all cases, the mean annual cycle from the control simulation has been removed. The volcanic eruptions start after half a year.
We assessed the impact of volcanic eruptions on the coupled climate-biogeochemical system by forcing a comprehensive, fully coupled carbon cycle-climate model with pulse-like stratospheric optical depth changes. The model simulates a decrease of global and regional atmospheric surface temperature, regionally distinct changes in precipitation, and a decrease in atmospheric CO2 after volcanic eruptions. The volcanic-induced cooling reduces overturning rates in tropical soils, which dominates over reduced litter input due to soil moisture decrease, resulting in higher land carbon inventories for several decades. The perturbation in the ocean carbon inventory changes sign from an initially weak carbon sink to a carbon source. Positive carbon and negative temperature anomalies in subsurface waters last up to several decades. The multi-decadal decrease in atmospheric CO2 yields an additional radiative forcing that amplifies the cooling and perturbs the Earth System on much longer time scales than the atmospheric residence time of volcanic aerosols.
Simulated global mean changes after the Pinatubo eruption. Temporal evolution of global ensemble monthly mean differences in (a) atmospheric surface temperature and (b) atmospheric CO2 between six simulations with and without volcanic eruptions is shown. The eruptions started in El Niño winter (black), La Niña winter (red), El Niño summer (green), and La Niña summer (blue) conditions. Shadings indicate one standard deviation confidence interval of the ensemble simulations. Dashed black lines indicate observation-derived temperature and atmospheric CO2 changes after the Mount Pinatubo eruption.
The three largest explosive volcanic eruptions in the last 50 years – Agung, El Chichón, and Pinatubo – occurred in spring-summer in conjunction with El Niño events and left distinct negative signals in the observational temperature and CO2 records. However, confounding factors such as seasonal variability and El Niño-Southern Oscillation (ENSO) may obscure the forcing-response relationship.
We determined 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 ocean carbon sinks. Ensemble simulations with the Earth System Model CSM1.4-carbon predict that the atmospheric response is ~60% larger when a volcanic eruption occurs during El Niño and in winter than during La Niña conditions. The simulations suggest that the Pinatubo eruptions 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. The results highlight the importance of considering the role of natural variability in the carbon cycle for interpretation of observations and for data-model intercomparison.