Model calibration using ESEm v1.0.0 -- an open, scalable Earth System Emulator

TL;DR

ESEm is an open-source, scalable Earth System Emulator framework that facilitates model emulation, validation, and uncertainty quantification across diverse earth science models, enabling efficient exploration of model sensitivities and uncertainties.

Contribution

It introduces ESEm, a versatile tool with a general workflow for emulating and validating earth system models, supporting uncertainty quantification and calibration.

Findings

Successfully reduced parametric uncertainty in a general circulation model.

Explored precipitation sensitivity in a cloud resolving model.

Assessed scenario uncertainty in the CMIP6 multi-model ensemble.

Abstract

Large computer models are ubiquitous in the earth sciences. These models often have tens or hundreds of tuneable parameters and can take thousands of core-hours to run to completion while generating terabytes of output. It is becoming common practice to develop emulators as fast approximations, or surrogates, of these models in order to explore the relationships between these inputs and outputs, understand uncertainties and generate large ensembles datasets. While the purpose of these surrogates may differ, their development is often very similar. Here we introduce ESEm: an open-source tool providing a general workflow for emulating and validating a wide variety of models and outputs. It includes efficient routines for sampling these emulators for the purpose of uncertainty quantification and model calibration. It is built on well-established, high-performance libraries to ensure robustness, extensibility and scalability. We demonstrate the flexibility of ESEm through three case-studies using ESEm to reduce parametric uncertainty in a general circulation model, explore precipitation sensitivity in a cloud resolving model and scenario uncertainty in the CMIP6 multi-model ensemble.