Estimates of volcanic-induced cooling in the Northern Hemisphere over the past 1,500 years

Journal name:
Nature Geoscience
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Published online

Explosive volcanism can alter global climate, and hence trigger economic, political and demographic change1, 2. The climatic impact of the largest volcanic events has been assessed in numerous modelling studies and tree-ring-based hemispheric temperature reconstructions3, 4, 5, 6. However, volcanic surface cooling derived from climate model simulations is systematically much stronger than the cooling seen in tree-ring-based proxies, suggesting that the proxies underestimate cooling7, 8; and/or the modelled forcing is unrealistically high9. Here, we present summer temperature reconstructions for the Northern Hemisphere from tree-ring width and maximum latewood density over the past 1,500 years. We also simulate the climate effects of two large eruptions, in AD 1257 and 1815, using a climate model that accounts explicitly for self-limiting aerosol microphysical processes3, 10. Our tree-ring reconstructions show greater cooling than reconstructions with lower spatial coverage and based on tree-ring width alone, whereas our simulations show less cooling than previous simulations relying on poorly constrained eruption seasons and excluding nonlinear aerosol microphysics. Our tree-ring reconstructions and climate simulations are in agreement, with a mean Northern Hemisphere extra-tropical summer cooling over land of 0.8 to 1.3°C for these eruptions. This reconciliation of proxy and model evidence paves the way to improved assessment of the role of both past and future volcanism in climate forcing.

At a glance


  1. New tree-ring reconstructions of NH extra-tropical land (40[deg]-90[deg] N) summer temperature anomalies (with respect to 1961-1990) since AD 500.
    Figure 1: New tree-ring reconstructions of NH extra-tropical land (40°–90° N) summer temperature anomalies (with respect to 1961–1990) since AD 500.

    a, Number of clusters. b, Calibration/verification (C/V) statistics of the NH1 reconstruction. c, NH1 (dark blue, mean value; pale blue envelope, 95% confidence interval calculated with a 1,000 iteration bootstrap approach) based on 30 clusters, 32 nested models calibrated against NH average instrumental JJA temperatures. d, NH2 (black) represents the mean of 22 regional reconstructions of instrumental JJA temperatures over the areas corresponding to its 22 chronology clusters. Red curves show 30-yr smoothing. For details see text and Methods.

  2. Summer cooling following Samalas and Tambora eruptions.
    Figure 2: Summer cooling following Samalas and Tambora eruptions.

    a,b, JJA cooling induced by Samalas reconstructed (NH1, NH2, and ref. 5), simulated in PMIP3 and (b) IPSL ensemble (SC2 scenario, 95.5 Tg SO2) for an eruption in May, July 1257 and January 1258 (note different y-axis scale). c,d, JJA cooling induced by Tambora reconstructed (NH1, NH2, and ref. 5) and simulated in PMIP3 (c) and IPSL ensemble (SC5 scenario, 56.8 Tg SO2) for an eruption in April 1815 (d). Temperature anomalies are deviations from a 30-yr running mean. White dots highlight cooling below the fifth percentile of NH1, NH2 and pre-industrial IPSL control simulation. Black dots stress anomalies below the fifth percentile of the IPSL last millennium forced simulation. The ensemble mean response to LS and US injection height scenarios is shown as dashed and solid lines, respectively, with their shaded 90% confidence spread.


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Author information


  1. Climatic Change and Climate Impacts, Institute for Environmental Sciences, University of Geneva, Boulevard Carl-Vogt 66 CH-1205 Geneva, Switzerland

    • Markus Stoffel &
    • Martin Beniston
  2. Section of Earth and Environmental Sciences, University of Geneva, rue des Maraîchers 13 CH-1205 Geneva, Switzerland

    • Markus Stoffel
  3., Institute of Geological Sciences, University of Berne, Baltzerstrasse 1+3 CH-3012 Berne, Switzerland

    • Markus Stoffel &
    • Sébastien Guillet
  4. Laboratoire d’Océanographie et du Climat: Expérimentations et approches numériques, Sorbonne Universités, UPMC Université Paris 06, IPSL, UMR CNRS/IRD/MNHN, F-75005 Paris, France

    • Myriam Khodri,
    • Virginie Poulain &
    • Nicolas Lebas
  5. Geolab, Université Blaise Pascal, 4 rue Ledru F-63057 Clermont-Ferrand, France

    • Christophe Corona
  6. Laboratoire Atmosphères, Milieux, Observations Spatiales, Sorbonne Universités, UPMC Université Paris 06, IPSL, UMR CNRS/UVSQ, F-75005 Paris, France

    • Slimane Bekki
  7. Centre Européen de Recherche et d’Enseignement des Géosciences de l’Environnement, Avenue Louis Philibert F-13545 Aix en Provence, France

    • Joël Guiot
  8. Department of Geography, University of Western Ontario, 1151 Richmond Street London, Ontario N6A 5C2, Canada

    • Brian H. Luckman
  9. Department of Geography, University of Cambridge, Downing Place Cambridge CB2 3EN, UK

    • Clive Oppenheimer
  10. Laboratoire des Sciences du Climat et de l’Environnement, Institut Pierre Simon Laplace/CEA-CNRS-UVSQ UMR 8212, L’Orme des Merisiers, F-91191 Gif-sur-Yvette, France

    • Valérie Masson-Delmotte


M.S., M.K., C.C. and S.G. designed the study with input from V.P., S.B., J.G., B.H.L., C.O., M.B. and V.M.-D. S.G. and C.C. performed climate reconstructions; M.K., S.B., V.P. and N.L. compiled ice-core data for SO2 yields estimation, designed the experiments and ran the microphysical and GCM models. All authors contributed to discussion and writing.

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