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Climate variability is variation in climate statistics across time or space, including fluctuations in means, seasonal behavior and extremes. It can arise internally from interacting atmospheric and oceanic dynamics or from changing external influences. The averaging interval and variable being measured must be specified.

A climate system can fluctuate even under steady forcing. A nonlinear convection model can produce nonperiodic behavior without a random external input, illustrating one mechanism for internally generated variability. This does not identify the cause of a particular observed climate trend: attribution requires comparing mechanisms, timescales and independent observations.^[ref]

Klaus Hasselmann explained how rapid, irregular weather fluctuations can generate slow climate variability. His 1976 Hasselmann stochastic climate model separates fast atmospheric variables from more slowly responding components such as the ocean and cryosphere, retaining the fluctuating forcing that simple time averaging would discard. Slow components integrate that forcing; stabilizing climate feedbacks prevent the variance from growing without bound. This supplies a mechanism for internally generated variability even when the external conditions do not vary.^[ref]

A physicist who developed stochastic climate models and founded the Max Planck Institute for Meteorology in 1975.^[ref]