Variability in a mixed layer ocean model driven by Stochastic atmospheric forcing

A stochastic model of atmospheric surface conditions, developed from 30 years of data at Ocean Weather Station P in the northeast Pacific, is used to drive a mixed layer model of the upper ocean. The spectral characteristics of anomalies in the four atmospheric variables; air and dewpoint temperature, wind speed and solar radiation, and many ocean features, including the seasonal cycle are reasonably well reproduced in a 500-year model simulation. However, the ocean model slightly underestimates the range of the mean and standard deviation of both temperature and mixed layer depth over the course of the year. The spectrum of the monthly SST anomalies from the model simulation are in close agreement with observations, especially when atmospheric forcing associated with El Nino is included. The spectral characteristics of the midlatitude SST anomalies is consistent with stochastic climate theory proposed by Frankignoul and Hasselmann (1977) for periods up to similar to 6 months. Lead/lag correlations and composites indicate a clear connection between the observed SST anomalies in spring and the following fall, as anomalous warm or cold water created in the deep mixed layer during winter/spring remain below the shallow mixed layer in summer and is then reentrained into the surface layer in the following fall and winter. This re-emergence mechanism also occurs in the model but the temperature anomaly pattern is more diffuse and influences the surface layer over a longer period compared with observations. A detailed analysis of the simulated mixed layer temperature tendency indicates that the anomalous net surface heat flux plays an important role in the growth of SST anomalies throughout the year and is the dominant term during winter. Entrainment of water into the mixed layer from below strongly influences SST anomalies in fall when the mixed layer is relatively shallow and thus has little thermal inertia. Mixed layer depth anomalies are highly correlated with the anomalous surface mechanical mixing in summer and surface buoyancy forcing in winter.