Abstract/Summary

Five upper ocean mixed layer models driven by ERA-Interim surface forcing are compared with a year of hydrographic observations of the upper 1000 m, taken at the Porcupine Abyssal Plain observatory site using profiling gliders. All the models reproduce sea surface temperature (SST) fairly well, with annual mean warm biases of 0.11  ° C (PWP model), 0.24  ° C (GLS), 0.31  ° C (TKE), 0.91  ° C (KPP) and 0.36  ° C (OSMOSIS). The main exception is that the KPP model has summer SSTs which are higher than the observations by nearly 3 ° . Mixed layer salinity (MLS) is not reproduced well by the models and the biases are large enough to produce a non-trivial density bias in the Eastern North Atlantic Central Water which forms in this region in winter. All the models develop mixed layers which are too deep in winter, with average winter mixed layer depth (MLD) biases between 160 and 228 m. The high variability in winter MLD is reproduced more successfully by model estimates of the depth of active mixing and/or boundary layer depth than by model MLD based on water column properties. After the spring restratification event, biases in MLD are small and do not appear to be related to the preceding winter biases. There is a very clear relationship between MLD and local wind stress in all models and in the observations during spring and summer, with increased wind speeds leading to deepening mixed layers, but this relationship is not present during autumn and winter. We hypothesize that the deepening of the MLD in autumn is so strongly driven by the annual cycle in surface heat flux that the winds are less significant in the autumn. The surface heat flux drives a diurnal cycle in MLD and SST from March onwards, though this effect is much more significant in the models than in the observations. We are unable to identify one model as definitely better than the others. The only clear differences between the models are KPP’s inability to accurately reproduce summer SSTs, and the OSMOSIS model’s more accurate reproduction of MLS.