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

Author:

Mansfield Laura A.1ORCID,Gupta Aman1ORCID,Burnett Adam C.1ORCID,Green Brian1ORCID,Wilka Catherine1ORCID,Sheshadri Aditi1ORCID

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

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