Updates on Model Hierarchies for Understanding and Simulating the Climate System: A Focus on Data‐Informed Methods and Climate Change Impacts

The climate model hierarchy encompasses models of varying complexity along different axes, ranging from idealized models that elegantly describe isolated mechanisms to fully coupled Earth system models that aspire to provide useable climate projections. Based on the second Model Hierarchies Workshop, which took place in 2022, we present perspectives on how this field has evolved since the first Model Hierarchies Workshop in 2016. In this period, we have witnessed a dramatic increase in the use of (a) machine learning in climate modeling and (b) climate models to estimate risks and influence decision making under climate change. Here, we discuss the implications of these growing areas of research and how we expect them to become integrated into the model hierarchies framework. The climate modeling community often describes the variety of models used to understand and simulate climate processes as a hierarchy in complexity. Simple idealized models exist at the bottom of the hierarchy and are useful for explaining underlying physics, while fully coupled Earth system models exist at the top of the hierarchy and aim to provide useable climate projections. We present perspectives on how the model hierarchy field is evolving, focusing on two noticeable changes in recent years. Firstly, models are increasingly using machine learning, and secondly, there has been a growing interest in the usability of climate models, for instance, for estimating risks associated with climate change. Here, we discuss the implications of these growing areas of interest and how we expect them to become integrated into the model hierarchies framework. Inspired by the 2022 Model Hierarchies workshop, we present perspectives on how the field is evolving Firstly, we note the growing interest in the use of machine learning which presents another way to ascend or descend the model hierarchy Secondly, we discuss the role of the model hierarchy for actionable climate science and decision‐making