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Title: Formalizing the use of expert judgement in uncertainty quantification of computer models Authors:  Leanna House - Virginia Tech (United States) [presenting]
Abstract: Deterministic computer models or simulators are used regularly to assist researchers in understanding the behavior of complex physical systems when real-world observations are limited. However, simulators are often imperfect representations of physical systems and may introduce layers of uncertainty into model-based inferences that are hard to quantify. To formalize the use of expert judgement in assessing simulator uncertainty, a method, called reification, has been previously proposed that decomposes the discrepancy between simulator predictions and reality by an improved, hypothetical computer model known as a reified simulator. One criticism of reification is that validation is, at best, challenging; only expert critiques can validate the subjective judgements used to specify a reified simulator. We develop a procedure to quantify the advantages of reification for fast, modular simulators. The procedure is explained and implemented within the context of a rainfall-runoff. We show that reification leads to informed judgements of simulator uncertainty.