A General Strategy for Physics-Based Model Validation Illustrated with Earthquake Phenomenology, Atmospheric Radiative Transfer, and Computational Fluid Dynamics
Didier Sornette, Anthony B. Davis, James R. Kamm, and Kayo Ide

TL;DR
This paper proposes a formal, iterative approach to model validation that emphasizes building trust through progressive, constructive approximation, illustrated with examples from physics and computational models.
Contribution
It introduces a new methodology for model validation that accounts for redundancy, novelty, and predictive accuracy, applicable across various scientific domains.
Findings
Validated the approach with quantum mechanics as a benchmark
Applied the methodology to earthquake, atmospheric, and fluid dynamics models
Demonstrated the adaptive process improves trust in complex models
Abstract
Validation is often defined as the process of determining the degree to which a model is an accurate representation of the real world from the perspective of its intended uses. Validation is crucial as industries and governments depend increasingly on predictions by computer models to justify their decisions. In this article, we survey the model validation literature and propose to formulate validation as an iterative construction process that mimics the process occurring implicitly in the minds of scientists. We thus offer a formal representation of the progressive build-up of trust in the model, and thereby replace incapacitating claims on the impossibility of validating a given model by an adaptive process of constructive approximation. This approach is better adapted to the fuzzy, coarse-grained nature of validation. Our procedure factors in the degree of redundancy versus novelty…
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Taxonomy
TopicsMeteorological Phenomena and Simulations · Climate variability and models · Scientific Computing and Data Management
