Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 4
Articles | Volume 18, issue 4
https://doi.org/10.5194/gmd-18-1041-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-18-1041-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 4
Development and technical paper
 | 
24 Feb 2025
Development and technical paper |  | 24 Feb 2025

Using feature importance as an exploratory data analysis tool on Earth system models

Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman

Related authors

Prescribing the aerosol effective radiative forcing in the Simple Cloud-Resolving E3SM Atmosphere Model v1
Naser Mahfouz, Hassan Beydoun, Johannes Mülmenstädt, Noel Keen, Adam C. Varble, Luca Bertagna, Peter Bogenschutz, Andrew Bradley, Matthew W. Christensen, T. Conrad Clevenger, Aaron Donahue, Jerome Fast, James Foucar, Jean-Christophe Golaz, Oksana Guba, Walter Hannah, Benjamin Hillman, Robert Jacob, Wuyin Lin, Po-Lun Ma, Yun Qian, Balwinder Singh, Christopher Terai, Hailong Wang, Mingxuan Wu, Kai Zhang, Andrew Gettelman, Mark Taylor, L. Ruby Leung, Peter Caldwell, and Susannah Burrows
EGUsphere, https://doi.org/10.5194/egusphere-2025-1868,https://doi.org/10.5194/egusphere-2025-1868, 2025
Short summary
Volcanic Aerosol Modification of the Stratospheric Circulation in E3SMv2 Part I: Wave-Mean Flow Interaction
Joseph Hollowed, Christiane Jablonowski, Thomas Ehrmann, Diana Bull, Benjamin Wagman, and Benjamin Hillman
EGUsphere, https://doi.org/10.5194/egusphere-2025-1756,https://doi.org/10.5194/egusphere-2025-1756, 2025
Short summary
HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024,https://doi.org/10.5194/gmd-17-5913-2024, 2024
Short summary
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024,https://doi.org/10.5194/gmd-17-5087-2024, 2024
Short summary
The fully coupled regionally refined model of E3SM version 2: overview of the atmosphere, land, and river results
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023,https://doi.org/10.5194/gmd-16-3953-2023, 2023
Short summary
More articles (1)

Cited articles

Alao, O., Lu, P. Y., and Soljačić, M.: Discovering Dynamical Parameters by Interpreting Echo State Networks, in: NeurIPS 2021 AI for Science Workshop, https://openreview.net/forum?id=coaSxusdBLX (last access: 10 July 2023), 2021. a
Ancona, M., Ceolini, E., Öztireli, C., and Gross, M.: Towards better understanding of gradient-based attribution methods for deep neural networks, arXiv [preprint], https://doi.org/10.48550/arXiv.1711.06104, 7 March 2018. a
Armour, K. C., Bitz, C. M., and Roe, G. H.: Time-varying climate sensitivity from regional feedbacks, J. Climate, 26, 4518–4534, 2013. a
Baker, A. H., Hu, Y., Hammerling, D. M., Tseng, Y.-H., Xu, H., Huang, X., Bryan, F. O., and Yang, G.: Evaluating statistical consistency in the ocean model component of the Community Earth System Model (pyCECT v2.0), Geosci. Model Dev., 9, 2391–2406, https://doi.org/10.5194/gmd-9-2391-2016, 2016. a
Banerjee, A., Butler, A. H., Polvani, L. M., Robock, A., Simpson, I. R., and Sun, L.: Robust winter warming over Eurasia under stratospheric sulfate geoengineering – the role of stratospheric dynamics, Atmos. Chem. Phys., 21, 6985–6997, https://doi.org/10.5194/acp-21-6985-2021, 2021. a
More articles (52)
Download
Short summary
Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.

Read more
Share
Special issue
Theoretical and computational aspects of ensemble design,...