Climate science, in particular climate prediction and projection, are heavily dependent on the use of Earth system models (ESMs), which are nonlinear, complex, and chaotic representations of the Earth’s spheres. As such, ESMs are susceptible to various sources of uncertainty. These include uncertainty in the initial state, parameter values, model formulation, structure, and external forcing. Ensembles have become a key tool to quantify these uncertainties and improve predictions. However, challenging questions remain regarding how to design and interpret such ensembles within the constraints of limited computational power and the lack of a rigorous framework for their design. Therefore, this special issue will be a valuable resource to climate scientists working on both theoretical and practical aspects of prediction ahead of Phase 7 of the Coupled Model Intercomparison Project (CMIP7) and future assessments.
This issue arises from the minisymposium
Theoretical and Computational Aspects of Ensemble Design and Interpretation in Climate Science and Modelling hosted during the SIAM Conference on Mathematical & Computational Issues in Geosciences in Bergen, Norway (19–22 June 2023). It will feature works by participants as well as external contributions.