Increasingly Sophisticated Climate Models Need the Out‐Of‐Sample Tests Paleoclimates Provide.

Climate models are becoming increasingly sophisticated as climate scientists continually work to improve the realism with which the processes influencing Earth's climate are represented. One example is the treatment of cloud microphysics: as complexity is added to cloud microphysical schemes, Earth's energy budget can respond to changes in climate forcings, such as carbon dioxide or aerosols, in new ways. This increase in degrees of freedom has illuminated larger spread in climate sensitivity across the latest generation of climate models participating Coupled Model Intercomparison Project, Phase 6, with more high climate sensitivity models (Zelinka et al., 2020, https://doi.org/10.1029/2019gl085782). Whilst the historical record gives us just over a century of data to apply toward climate sensitivity constraints (e.g., Nijsse et al., 2020, https://doi.org/10.5194/esd-11-737-2020), the ocean is still taking up much of the heat trapped by anthropogenic greenhouse gas emissions and the climate system is far from equilibrium which limits our understanding how climate sensitivity might change in response to long‐term forced climate change. Here we discuss the valuable tests that paleoclimate reconstructions can provide the latest generation of climate models, as demonstrated by the recent study of Zhu et al., 2022, https://doi.org/10.1029/2021ms002776. Their study provides an example of the benefits for climate model development when climate models are confronted with simulating climates very different from today. Ideally the climate model development stage under future iterations of CMIP will involve such tests as an effort to constrain global climate sensitivity and the regional patterns of climate, such as polar amplification and subtropical aridification. Plain Language Summary: In each successive generation of climate models the representation of climate processes becomes more realistic and more complex. The more sophisticated characterization of cloud processes has resulted in some models warming much more in response to increasing atmospheric carbon dioxide concentrations due to stronger cloud feedbacks; referred to as having a higher climate sensitivity. The Community Earth System Model version 2 (CESM2) is one such model. When used to simulate the Last Glacial Maximum (LGM), CESM2 has a global temperature around 5°C colder than surface temperature reconstructions and previous generations of this model. By investigating the updated cloud scheme, Zhu et al., 2022, https://doi.org/10.1029/2021ms002776 were able to identify and modify issues with the cloud microphysical scheme that were contributing to this problem. They subsequently produced a new version of CESM2 which can simulate the LGM more accurately without degrading the simulation of the 20th century climate. The Zhu et al., 2022, https://doi.org/10.1029/2021ms002776 study is an example of how a paleoclimate can be used to identify issues with cloud schemes not traditionally recognized in the model development and validation process. Incorporating paleoclimate simulations earlier in the model development and validation process may help constrain cloud feedbacks and subsequently climate sensitivity. Key Points: Paleoclimates provide valuable tests for the latest generation of climate modelsZhu et al., 2022, https://doi.org/10.1029/2021ms002776 provide an example of the paleoclimate benefits for climate model developmentFuture iterations of CMIP will ideally incorporate paleoclimate tests during model development [ABSTRACT FROM AUTHOR]