Internal Climate Variability in Ensemble Climate Models

Internal climate variability refers to the natural fluctuations arising from the chaotic interactions within the atmosphere, ocean, cryosphere and land surface. Ensemble climate models exploit this variability by running multiple simulations with slightly different initial conditions to sample the full range of possible trajectories. By comparing ensemble members, researchers can distinguish the climate system’s internal ‘noise’ from the externally forced signal driven by greenhouse gases, aerosols and solar variability. This separation is essential for evaluating model fidelity, attributing observed changes, estimating projection uncertainty and informing adaptation strategies. Large ensembles—typically tens to hundreds of members—allow for robust estimation of statistics such as mean trends, extremes and teleconnections at global and regional scales. Ensemble means provide a clearer view of the forced response by averaging out internal fluctuations, while the spread among members quantifies irreducible uncertainty. As model resolution and complexity increase, ensembles remain indispensable for interpreting near-term forecasts, assessing the likelihood of extreme events and guiding policy decisions under a changing climate.

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Internal Climate Variability in Ensemble Climate Models publication trend

The graph below shows the total number of articles in internal climate variability in ensemble climate models across all publications each year (not limited to Nature Index journals).

Technical terms

Internal climate variability: Fluctuations in climate parameters arising from the climate system’s natural chaotic dynamics rather than external forcings.

Forced response: The component of climate change directly attributable to external drivers such as greenhouse gas increases, solar variability or aerosol emissions.

Initial-condition large ensemble: A set of climate model simulations that share the same external forcings but differ only in their initial states, used to sample internal variability.

Ensemble mean: The average of all members in an ensemble, which emphasises the forced response by smoothing out individual internal fluctuations.

References

1. Importance of internal variability for climate model assessment. npj Climate and Atmospheric Science (2023).
2. MIROC6 Large Ensemble (MIROC6-LE): experimental design and initial analyses. Earth System Dynamics (2023).
3. The New Max Planck Institute Grand Ensemble With CMIP6 Forcing and High‐Frequency Model Output. Journal of Advances in Modeling Earth Systems (2023).