Coupled circulation (NEMO) and wave model (WAM) system was used to study the effects of surface ocean waves on water temperature distribution and heat exchange at regional scale (the Baltic Sea). Four scenarios-including Stokes-Coriolis force, sea-state dependent energy flux (additional turbulent kinetic energy due to breaking waves), seastate dependent momentum flux and the combination these forcings-were simulated to test the impact of different terms on simulated temperature distribution. The scenario simulations were compared to a control simulation, which included a constant wave-breaking coefficient, but otherwise was without any wave effects. The results indicate a pronounced effect of waves on surface temperature, on the distribution of vertical temperature and on upwelling's. Overall, when all three wave effects were accounted for, did the estimates of temperature improve compared to control simulation. During the summer, the wave-induced water temperature changes were up to 1°C. In northern parts of the Baltic Sea, a warming of the surface layer occurs in the wave included simulations in summer months. This in turn reduces the cold bias between simulated and measured data, e.g. the control simulation was too cold compared to measurements. The warming is related to seastate dependent energy flux. This implies that a spatiotemporally varying wave-breaking coefficient is necessary, because it depends on actual sea state. Wave-induced cooling is mostly observed in near-coastal areas and is the result of intensified upwelling in the scenario, when Stokes-Coriolis forcing is accounted for. Accounting for sea-state dependent momentum flux results in modified heat exchange at the water-air boundary which consequently leads to warming of surface water compared to control simulation.
We present ice-free and ice-included statistics for the Baltic Sea using a wave hindcast validated against data from 13 wave measurement sites. In the hindcast 84% of wave events with a significant wave height over 7 m occurred between November and January. The effect of the ice cover is largest in the Bay of Bothnia, where the mean significant wave height is reduced by 30% when the ice time is included in the statistics. The difference between these two statistics are less than 0.05 m below a latitude of 59.5°. The seasonal ice cover also causes measurement gaps by forcing an early recovery of the instruments. Including the time not captured by the wave buoy can affect the estimates for the significant wave height by roughly 20%. The impact below the 99 th percentiles are still under 5%. The significant wave height is modelled accurately even close to the shore, but the highest peak periods are underestimated in a narrow bay. Sensitivity test show that this underestimation is most likely caused by an excessive refraction towards the shore. Reconsidering the role of the spatial resolution and the physical processes affecting the low-frequency waves is suggested as a possible solution.
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