In my master's project, I developed a conceptual model of the upper ocean to simulate the daily variation of sea surface temperature. The main goal was to come up with a simple improvement over previously used slab ocean models by accurately capturing how surface warming depends on wind.

The sea surface of the tropical ocean typically warms under the sun during daytime and cools at night. This daily temperature cycle depends on the amount of sunlight, wind speed, and other factors such as air temperature, humidity, and water clarity. Model simulations of the tropical atmosphere demonstrate that the daily change of sea surface temperature (SST) can affect if and how clouds cluster above the ocean.

However, many studies investigating cloud organization neglect this atmosphere-ocean interaction or represent it unrealistically. To address this, we propose a simple numerical model that adds one step of realism by including the effect of water mixing in the upper ocean caused by wind. Comparing predictions of this model with the observed sea temperature evolution during a research cruise, we show that the model reproduces the observed SST dynamics, accurately capturing the relationship between wind speed and the strength of daily SST warming.

Our model can be plugged into high-resolution atmosphere models to improve the representation of air-sea heat exchange when simulating clouds. Understanding the complex processes behind cloud clustering is important for the prediction of rainfall extremes, hurricanes, and global warming estimates.

Related publications

• R. Börner, J. O. Haerter & R. Fiévet, A conceptual model of the diurnal warm layer for idealized atmospheric simulations with interactive SST (2024). arXiv:2205.07933

Read more in my master's thesis on this topic.

Further resources

The source code of the diurnal warming models are available on Github.