Modelling Complexity: the case of Climate Science

TL;DR

This paper reviews scientific and epistemological challenges in climate science, emphasizing the complexity of modeling, uncertainties, and limitations of geo-engineering, proposing a thermodynamics-based framework and critiquing reliance on supercomputing and centralized planning.

Contribution

It introduces a non-equilibrium thermodynamics framework for climate modeling and critically examines current computational and planning approaches in climate science.

Findings

Climate models face significant uncertainties and scale challenges.

Geo-engineering solutions have intrinsic limitations.

Critique of reliance on supercomputing and centralized scientific planning.

Abstract

We briefly review some of the scientific challenges and epistemological issues related to climate science. We discuss the formulation and testing of theories and numerical models, which, given the presence of unavoidable uncertainties in observational data, the non-repeatability of world-experiments, and the fact that relevant processes occur in a large variety of spatial and temporal scales, require a rather different approach than in other scientific contexts. A brief discussion of the intrinsic limitations of geo-engineering solutions to global warming is presented, and a framework of investigation based upon non-equilibrium thermodynamics is proposed. We also critically discuss recently proposed perspectives of development of climate science based purely upon massive use of supercomputer and centralized planning of scientific priorities.