The oceans are changing rapidly in response to climate change. In this period of rapid change, long-term trends are now emerging across ocean variables, while natural variability operates across a wide range of spatial and temporal scales, placing long-term observations at fixed locations in a unique position to be compared with models and reanalyses to investigate this variability and assess how well they represent changes in the ocean across timescales.

In this session, we invite contributions that bring together long-term ocean time series and numerical models and/or reanalyses and satellite data to examine the representation of ocean variability, from daily and seasonal cycles to subseasonal and interannual variability, and longer-term changes and trends. We encourage studies that go beyond model–observation validation and use the comparison to identify processes and timescales that are not adequately represented and investigate the physical causes of observed differences. Such approaches can improve the representation of ocean variability and the processes driving it in models and reanalyses and contribute to better estimates of long-term trends and their uncertainties, improved understanding of ocean–climate interactions, and enhanced skill in seasonal-to-decadal predictions.

Contributions are welcome at global, basin-wide and regional scales, and across ocean compartments, from the air–sea interface to the deep ocean and seafloor. Studies addressing ocean circulation and transports, biogeochemical or biological variables are encouraged. Contributions using CMIP models, ocean reanalyses, high-resolution regional models, process models, or other modelling and statistical approaches are all welcome. We particularly welcome contributions demonstrating the scientific value of sustained, high-frequency and long-term observations for improving models and reanalyses and advancing our understanding of a changing ocean.