Marine aquaculture is well positioned to help meet global seafood demand, but the reliance of most production on the ambient environment suggests inherent vulnerability to climate change effects. Climate change vulnerability and risk assessments can help determine targeted adaptation needs. Some salmon culture sectors are now adopting variants of these assessments to support sustainability reporting. Many existing monitoring and modelling methods are already well suited to flag deleterious influences of climate change on marine aquaculture with potential application through digital twins. These may include intensive monitoring approaches like precision aquaculture, and application of ecophysiology and energetic models which aim to predict outcomes that can scale from individual animals to the farm level. Though not without limitations. Digital twin approaches incorporating components of climate change projections are apt to be predictive (a digital twin category) stand-alone applications unconnected to an asset (or ‘Digital siblings’). There are important data input considerations for the monitoring of climate change stressors and application of climate data to models, irrespective of digital twin type. Data streams are crucial for most digital twins, and the effort of maintaining monitoring equipment in the marine environment is not trivial. The present spatial and temporal scale of ocean model climate projections is still too coarse for application at the farm scale. Significant in situ data collection is required to correct for projection biases, and this data collection must be long term. There is great opportunity for industry collection of ocean data to contribute to long-term ocean data sets across entire regions.