Intrinsic Ocean Variability Partly Randomizes the Mean Seasonal Cycle of Sea Level

Oceanic nonlinearities generate random intrinsic sea level variations across the global ocean, which locally compete with forced sea level variations paced by atmospheric and astronomical drivers. This study utilizes a global ocean/sea‐ice 50‐member ensemble simulation to characterize the sea level mean seasonal cycle (computed over 1993–2015) and partition its forced and intrinsic components. The model faithfully reproduces many features of the observed sea level mean seasonal cycle. Ensemble diagnostics show that the mean seasonal cycle is most stochastic in energetic regions of the ocean, such as the Southern Ocean and western boundary currents, and remains partly random up to 10° × 10° () scales in these regions. Both forced and intrinsic components mostly have a steric origin, but with deeper steric signals involved in the intrinsic term. Our study thus demonstrates that ocean nonlinearities impart a marked stochastic flavor to the sea level seasonal cycle averaged over 23 years and illustrates the usefulness of eddying ocean ensemble simulations for adequately interpreting observations.