Underestimating Internal Variability Leads to Narrow Estimates of Climate System Properties

Alex G. Libardoni, Chris E. Forest, Andrei P. Sokolov, Erwan Monier

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Probabilistic estimates of climate system properties often rely on the comparison of model simulations to observed temperature records and an estimate of the internal climate variability. In this study, we investigate the sensitivity of probability distributions for climate system properties in the Massachusetts Institute of Technology Earth System Model to the internal variability estimate. In particular, we derive probability distributions using the internal variability extracted from 25 different Coupled Model Intercomparison Project Phase 5 models. We further test the sensitivity by pooling variability estimates from models with similar characteristics. We find the distributions to be highly sensitive when estimating the internal variability from a single model. When merging the variability estimates across multiple models, the distributions tend to converge to a wider distribution for all properties. This suggests that using a single model to approximate the internal climate variability produces distributions that are too narrow and do not fully represent the uncertainty in the climate system property estimates.

Original languageEnglish (US)
Pages (from-to)10000-10007
Number of pages8
JournalGeophysical Research Letters
Volume46
Issue number16
DOIs
StatePublished - Aug 28 2019

All Science Journal Classification (ASJC) codes

  • Geophysics
  • Earth and Planetary Sciences(all)

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