Modeling the Near-Surface Diurnal Cycle of Sea Surface Temperature in the Mediterranean Sea

The diurnal cycle of sea surface temperature (SST) is an important component of the ocean-atmosphere system and is necessary for accurately computing air-sea heat fluxes. Ocean temperatures in the near-surface are highly sensitive to atmospheric conditions and can vary significantly depending on time of day. Ocean general circulation models are unable to fully capture the near-surface diurnal SST variability, because they do not possess the necessary vertical structure and resolution. Furthermore, SST observations come from a number of sources that represent the temperature at various near-surface depths. This presents difficulties when assimilating SST observations as well as constructing robust climate records of SST. In this study we model the fine-scale near-surface structure allowing SST comparisons between foundation SST, SST at depth, subskin SST, and skin SST. Hourly model results, forced and initialized using readily available reanalysis data, are from a 2-year period, 2013-2014, over the Mediterranean Sea. Various solar absorption parameterizations are examined, and the resulting SSTs are compared to Spinning Enhanced Visible and InfraRed Imager-derived observations of the skin temperature. Plain Language Summary The sea surface temperature (SST) is an important variable of the climate system. It governs the exchange of energy between the ocean and atmosphere. Accurate knowledge of SST is essential for weather and ocean forecasting. The vast majority of our observations of SST are remotely sensed and derived from satellite instruments that record the temperature within the top 1 mm. These observations are complemented by a mixture of ocean moorings and gliders that measure the temperature at various near-surface depths (similar to 20 cm to 1 m). SSTs are highly sensitive to atmospheric conditions and can vary significantly depending on time of day and near-surface depth. This presents difficulties when combining different observations to construct robust climate records of SST. In addition, large-scale computational models of the ocean typically resolve temperature in a surface layer similar to 1m thick and are unable to fully capture SST variability. It is therefore challenging to properly compare and/or merge modeled SSTs with observed SSTs. To address these challenges, we present a computational model of the fine-scale near-surface ocean structure. The model is tested in the Mediterranean Sea and used to produce a 2-year data set that makes possible SST comparisons at various near-surface depths at any hour of the day.