Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations

Tapio Schneider; Shiwei Lan; Andrew Stuart; João Teixeira

doi:10.1002/2017gl076101

journal article Dec 28, 2017

Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations

Tapio Schneider

Shiwei Lan

Andrew Stuart João Teixeira

Geophysical Research Letters Vol. 44 No. 24 · American Geophysical Union (AGU)

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Abstract

AbstractClimate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high‐resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high‐resolution simulations, for example, of clouds and convection, through matching low‐order statistics between ESMs, observations, and high‐resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.

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Metrics

262

Citations

196

References

Details

Published: Dec 28, 2017
Vol/Issue: 44(24)
License: View

Authors

T

Tapio Schneider

California Institute of Technology Pasadena CA USA; Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

S

Shiwei Lan

California Institute of Technology Pasadena CA USA

A

Andrew Stuart

California Institute of Technology Pasadena CA USA

J

João Teixeira

Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

Funding

Office of Naval Research Award: N00014-17-1-2079

Cite This Article

Tapio Schneider, Shiwei Lan, Andrew Stuart, et al. (2017). Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations. Geophysical Research Letters, 44(24). https://doi.org/10.1002/2017gl076101

Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations

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