This preprint introduces stochastic emulators designed to capture spatially resolved extreme temperature events in Earth System Models. The emulators aim to improve the representation of extreme events, which are often challenging to model accurately in traditional Earth System Models due to their computational complexity. By leveraging stochastic methods, this work provides an efficient tool for analyzing and predicting extreme temperature behavior in climate systems.