This short course, which extends the course on emulation in managing uncertainty in geophysical models, discusses the issue of the calibration of geophysical simulators using emulator technology. The course will focus on calibration (simulator parameter estimation), addressing the issue of how to model the discrepancy between the simulator and reality. Appropriate specification of the discrepancy is a critical step in Bayesian approaches to calibration. We will also describe multistage approaches to calibration based on the use of an implausibility score to progressively refine both the emulator and the parameter estimates. Using examples from the MUCM project (http://www.mucm.ac.uk) we will describe the practical implementation of Bayesian calibration methods, linking to the MUCM Toolkit. By the end of the session we anticipate that attendees would know the potential and limitations of emulation for calibration, and have sufficient knowledge to attempt calibration for their simulators, using the freely available MUCM Toolkit for guidance. Note that it is not essential to have attended our earlier course on “The Role of Emulation in Managing Uncertainty in Complex Geophysical Models”, but this would be of benefit if you are not familiar with the emulation concepts.