Spatial and Temporal Resolution in Ocean Models

You’ve seen how a model is built. Now Emanuela Clementi turns to one of the most important choices of all: resolution – how finely the model divides space and time, and what that decides about the ocean it can “see.”

The lecture covers both dimensions:

• Spatial resolution – the size of the grid cells, which sets the smallest feature a model can capture. It ranges from around 100 km for global models down to around 100 m for coastal ones. Different goals need very different resolutions: global models prioritise long, stable, multi-decadal runs, while coastal models must resolve complex bathymetry and fast local processes
• Why resolution matters so much – it controls how much detail a model shows, and which processes it can resolve at all. Anything smaller than a grid cell – the sub-grid processes – is lost and must be handled another way (the subject of the next lecture). Higher resolution means more realism, but at a steep price in computational cost
• Temporal resolution – the ocean varies across an enormous range of timescales, from minutes to millennia. A model must step forward in time finely enough to capture the processes that matter, and its outputs are shared as averages at chosen frequencies – hourly, daily, or monthly being the most common
• How space and time are linked – the two cannot be chosen independently. The CFL condition ties them together: if the grid is fine, the time step must be short, because information in the model cannot travel faster than one grid cell per step. Finer grids therefore demand shorter time steps – and much more computing

The thread to carry forward: choosing resolution is a key modelling decision, and space and time resolution are interconnected. There is no single “best” resolution – only the right one for the job, balanced against what a computer can afford. The reading and exercise that follow let you explore these trade-offs directly.