Parameter Uncertainty Quantification in an Idealized GCM With a Seasonal Cycle
Parameter Uncertainty Quantification in an Idealized GCM With a Seasonal Cycle
Climate models are generally calibrated manually by comparing selected climate statistics, such as the global top-of-atmosphere energy balance, to observations. The manual tuning only targets a limited subset of observational data and parameters. Bayesian calibration can estimate climate model parameters and their uncertainty using a larger fraction of the available …