An EOF-Based Emulator of Means and Covariances of Monthly Climate Fields

Abstract. Fast emulators of comprehensive climate models are often used to explore the impact of anthropogenic emissions on future climate. A new approach to emulators is introduced that predicts means and covariances of monthly averaged climate variables. The emulator is trained with output from a state-of-the-art climate model and serves as a good first-order representation for the evolution of spatially resolved climate variables and their variability. For illustrative purposes, the emulator is applied to predict changes in the mean and variability of monthly values of both temperature and relative humidity as a function of global mean temperature changes. However, the approach can be applied to any other variable of interest.