Abstract
In 1976, Klaus Hasselmann initiated a groundbreaking shift in climate science when he introduced the Stochastic Climate Model (SCM) to the field, a conceptual framework aimed at elucidating the origins of red spectra observed in the dynamics of both the atmosphere and the oceans. While this concept had somewhat faded from the limelight as climate science increasingly morphed into climate change science, it regained prominence within the climate science community when Klaus Hasselmann was awarded the Nobel Prize in Physics in 2021. Historically, the primary use of the SCM centered on explaining why the spectra of atmospheric and oceanic dynamics were continuous and ''red'' rather than a series of peaks. Our present paper has expanded the scope of the SCM's applicability, when we used it as a valuable tool for understanding the generation of intrinsic variability (often referred to as ''noise'') within the hydrodynamics of a marginal sea. Our analysis of multiple simulation ensembles using a regional ocean model has uncovered a relationship between the generation of intrinsic variability tied to the annual cycle and the activation of tides. This relationship can be attributed to a single parameter, and notably, this parameter corresponds to the central element in the SCM—referred to as the "memory."
