Robust Multiyear Climate Impacts of Volcanic Eruptions in Decadal Prediction Systems

Leon Hermanson, Roberto Bilbao, Nick Dunstone, Martin Ménégoz, Pablo Ortega, Holger Pohlmann, Jon I. Robson, Doug M. Smith, Gary Strand, Claudia Timmreck, Steve Yeager, Gokhan Danabasoglu

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Major tropical volcanic eruptions have a large impact on climate, but there have only been three major eruptions during the recent relatively well-observed period. Models are therefore an important tool to understand and predict the impacts of an eruption. This study uses five state-of-the-art decadal prediction systems that have been initialized with the observed state before volcanic aerosols are introduced. The impact of the volcanic aerosols is found by subtracting the results of a reference experiment where the volcanic aerosols are omitted. We look for the robust impact across models and volcanoes by combining all the experiments, which helps reveal a signal even if it is weak in the models. The models used in this study simulate realistic levels of warming in the stratosphere, but zonal winds are weaker than the observations. As a consequence, models can produce a pattern similar to the North Atlantic Oscillation in the first winter following the eruption, but the response and impact on surface temperatures are weaker than in observations. Reproducing the pattern, but not the amplitude, may be related to a known model error. There are also impacts in the Pacific and Atlantic Oceans. This work contributes toward improving the interpretation of decadal predictions in the case of a future large tropical volcanic eruption.

Original languageEnglish
Article numbere2019JD031739
JournalJournal of Geophysical Research: Atmospheres
Volume125
Issue number9
DOIs
StatePublished - May 16 2020

Keywords

  • ENSO
  • NAO
  • climate
  • coupled model
  • volcano

Fingerprint

Dive into the research topics of 'Robust Multiyear Climate Impacts of Volcanic Eruptions in Decadal Prediction Systems'. Together they form a unique fingerprint.

Cite this