Climate information plays a key role in driving models of agricultural, hydrological, energy, and economic systems. While process-based Earth system models (ESMs) are the goal standard for providing such information, they are computationally expensive to run. Reduced complexity models and emulators are a common solution for providing novel scenarios and realizations of climate information at reduced computational expense. In addition, reduced complexity models and emulators have an important role in exploring uncertainties in forcing and temperature response, and are being used to answer questions relevant to mitigation policies and warming targets.

We welcome submissions identifying new developments in reduced complexity climate models, the emulation of Earth system model behaviors across multiple variables and/or considering variability, and novel applications of such information in impacts modeling.