Model calibration using ESEm v1.1.0 – an open, scalable Earth system emulator

Watson-Parris, Duncan; Williams, Andrew; Deaconu, Lucia; Stier, Philip

doi:https://doi.org/10.5194/gmd-14-7659-2021

Articles | Volume 14, issue 12

https://doi.org/10.5194/gmd-14-7659-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Benchmark datasets and machine learning algorithms for Earth...

https://doi.org/10.5194/gmd-14-7659-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 12

Model description paper

|

20 Dec 2021

Model description paper |

| 20 Dec 2021

Model calibration using ESEm v1.1.0 – an open, scalable Earth system emulator

Duncan Watson-Parris, Andrew Williams, Lucia Deaconu, and Philip Stier

Data sets

Example Perturbed Parameter Ensemble (Black Carbon) Duncan Watson-Parris and Lucia Deaconu https://doi.org/10.5281/zenodo.3856645

duncanwp/ESEm: v1.1.0 (v1.1.0) Duncan Watson-Parris, Andrew Williams, and Pietro Monticone https://doi.org/10.5281/zenodo.5466563

Data of the paper: Ensemble daily simulations for elucidating cloud–aerosol interactions under a large spread of realistic environmental conditions Guy Dagan and Philip Stier https://doi.org/10.5281/zenodo.3785603

Model code and software

ESEm v1.1.0 Duncan Watson-Parris and Andrew Williams https://doi.org/10.5281/zenodo.5196632

Short summary

The Earth System Emulator (ESEm) provides a fast and flexible framework for emulating a wide variety of Earth science datasets and tools for constraining (or tuning) models of any complexity. Three distinct use cases are presented that demonstrate the utility of ESEm and provide some insight into the use of machine learning for emulation in these different settings. The open-source Python package is freely available so that it might become a valuable tool for the community.