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Due to their abundance and their observational advantages, M dwarfs offer the best chance of finding habitable planets through sheer numbers. Therefore, in the race to detect signs of life beyond the Solar System, rocky M-dwarf planets offer exciting prospects. While the habitable zone serves as a preliminary indicator of the potential habitability of a planet, planetary climate studies are necessary in order to better assess a planets ability to host life. Climate is affected by numerous factors that are not considered in the classic habitable zone formulation, but can be included in climate models of varying complexity.Oceans have a dominant impact on planetary climate, so understanding their effects is a necessary part of modelling terrestrial exoplanets in order to understand future observations. We have conducted studies with an intermediate complexity coupled atmosphere-ocean general circulation model (FORTE2.0). Using a coupled dynamic ocean enables us to include effects of ocean circulation. Strong tidal interactions are tightly linked to the ocean vertical diffusivity and thus ocean temperature structure (including surface temperature). Taking into account the impact of ocean tides can therefore lead to significant effects on planetary climate.We investigated the case of non synchronous terrestrial planets in close orbits in the habitable zone of their M host star. In this scenario, we have parameterised the effect of propagating tides, and analysed their impact on ocean circulation and minimum and maximum values of surface temperature. We found that ocean tides are particularly important in setting latitudinal gradients in temperature, with subsequent effects on climate and habitability.By considering scenarios in which the magnitude of tidal forcings varies over a range of values, we were able to determine that key surface quantities (such as winds, heat flux and water flux) are subjected to change.The repercussions that ocean vertical diffusion can have on surface quantities is noteworthy from the observational point of view, as observable features - such as cloud patterns are shaped differently in each scenario.
Paolo et al. (Sat,) studied this question.