Abstract. Retreat and advance of ice sheets perturb the gravitational field, solid surface and rotation of the Earth, leading to spatially variable sea-level changes over a range of timescales (~O100-6 years), which in turn feed back onto ice sheet dynamics. Coupled ice-sheet – sea-level models have been developed to capture the interactive processes between ice sheets, sea level and the solid Earth, but it is computationally challenging to capture short-term interactions (~O100-2 years) precisely within longer (~O103-6 years) simulations. The classic coupling algorithm assigns a uniform temporal resolution in the sea-level model, causing a quadratic increase in total CPU time with the total number of input ice history steps, which increases with either the length or temporal resolution of the simulation. In this study, we introduce a new “time window” algorithm for sea-level models that enables users to define the temporal resolution at which the ice loading history is captured during different time intervals before the current simulation time. Utilizing the time window, we assign a fine temporal resolution (~O100-2 years) for the period of ongoing and recent history of surface ice and ocean loading changes and a coarser temporal resolution (~O103-6 years) for earlier periods in the simulation. This reduces the total CPU time and memory required per model time step while maintaining the precision of the model results. We explore the sensitivity of sea-level model results to the model's temporal resolution and show how this sensitivity feeds back onto ice sheet dynamics in coupled modelling. We apply the new algorithm to simulate the sea-level changes in response to global ice-sheet evolution over two glacial cycles and the rapid collapse of marine sectors of the West Antarctic Ice Sheet in the coming centuries, providing appropriate time window profiles for each of these applications. The time window algorithm improves the total CPU time by ~50–% in each of these examples, and this improvement would increase with longer simulations than considered here. Our algorithm also allows coupling time intervals of annual temporal scale for coupled ice-sheet – sea-level modelling of regions such as the West Antarctic that are characterized by rapid solid Earth response to ice changes due to the thin lithosphere and low mantle viscosities.