Affiliation:
1. Department of Earth System Science Stanford Doerr School of Sustainability Stanford University Stanford CA USA
Abstract
AbstractThe 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.
Funder
National Science Foundation
Google
Publisher
American Geophysical Union (AGU)
Subject
General Earth and Planetary Sciences,Environmental Chemistry,Global and Planetary Change