Work

Specification and Verification for Climate Modeling: Formalization Leading to Impactful Tooling

Year: 2025

Type: article

Abstract: Earth System Models (ESMs) are critical for understanding past climates and projecting future scenarios.However, the complexity of these models, which include large code bases, a wide community of developers, and diverse computational platforms, poses significant challenges for software quality assurance.The increasing adoption of GPUs and heterogeneous architectures further complicates verification efforts.Traditional verification methods often rely on bitwise reproducibility, which is not always feasible, particularly under new compilers or hardware.Manual expert evaluation, on the other hand, is subjective and time-consuming.Formal methods offer a mathematically rigorous alternative, yet their application in ESM development has been limited due to the lack of climate model-specific representations and tools.Here, we advocate for the broader adoption of formal methods in climate modeling.In particular, we identify key aspects of ESMs that are well suited to formal specification and introduce abstraction approaches for a tailored framework.To demonstrate this approach, we present a case study using CIVL model checker to formally verify a bug fix in an ocean mixing parameterization scheme.Our goal is to develop accessible, domain-specific formal tools that enhance model confidence and support more efficient and reliable ESM development.

Source: Electronic Proceedings in Theoretical Computer Science

DOI: 10.4204/eptcs.432.8

Authors: Alper Altuntas, Allison H. Baker, John Baugh, Ganesh Gopalakrishnan, Stephen F. Siegel

Institutions: NSF National Center for Atmospheric Research, North Carolina State University, University of Utah, University of Delaware

Language: English

Topic: Formal Methods in Verification

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Climate action

Open Access status: diamond

Funders: National Science Foundation, U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research