The variability caused by external forcing and internal forcing in the marginal sea, Bohai and Yellow Sea

We analyze the tidal forcing effects on the internal variability in two marginal seas, the Bohai and Yellow Seas, and interpretate such effects from stochastic climate model and physical process (for instance, baroclinic instability) aspects. Ensemble simulations of the numerical module (Finite-volume Coastal Ocean Model) with and without tidal forcings are used to analyze the tidal forcing effects on the internal variability. EOF analysis is used to separate the variability into different spatial scales. The results show that the internal variability is significantly decreased especially in large (100 Km) and medium (60 km) scales, less so in small scales (23 km), when the tidal forcing is turned off. This result is well explained by Hasselmann's theory. Ocean memory, represented by the temporal autocorrelation function, is a critical element in this theory. Ocean memory is enhanced when the tidal forcing is excluded in all spatial scales, more obvious in large and medium scales; correspondingly, the internal variability increased significantly in the large and medium scales, compared with small scales in no-tide simulation. Physically, it can be explained as when the tidal forcing is turned off, once an anomaly appears in the system, it can survive for a longer time and easier to grow into large-scale variability. From the physical process aspect, we demonstrated that internal variability level and baroclinic instability variation co-vary consistently when comparing summer and winter seasons, and with and without tides. Our interpretation is that a stronger baroclinic instability causes more potential energy to be transformed into kinetic energy, allowing the unforced disturbances to grow.