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Understanding the unknowns: recognition, quantification, influence and minimisation of uncertainty in the geosciences (co-organized)
Convener: Lucia Perez-Diaz  | Co-Conveners: Juan Alcalde , Clare Bond , Susanne Buiter , Flora Boekhout , Nick Roberts 
 / Thu, 12 Apr, 10:30–12:00 / Room -2.31
 / Attendance Thu, 12 Apr, 17:30–19:00 / Hall X2
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With ever-more powerful computers and sophisticated laboratory techniques it comes as no surprise that many aspects of geology now rely on models and simulations. These are extremely powerful tools for testing hypothesis, integrating data and visualizing processes acting over multiple spatial or temporal geological scales. Often these processes are not observable together, or at all, in the field. They are however, based on interpretations and assumptions. In order to assess the relevance and applicability of the results, and crucially their suitability as boundary conditions for multidisciplinary studies, the errors (e.g. uncertainities in interpretations to build a model) and any assumptions made throughout the modelling or experimental process need to be carefully considered so that their influences can be quantified. Despite the importance of understanding uncertainty, it is often neglected by interpreters, geomodellers and experimentalists, perhaps driven by the societal expectation for a single (flawless) deterministic model and outputs.

This session aims to bring together geoscientists from a variety of fields interested in developing a more integrated understanding of how quantifying and recognizing uncertainty in geological interpretation, models and experiments broadens their applicability and increases their value. We would like this session to be a platform to bring together end-users of geological data with geoscientists interested in better representing and quantifying uncertainty. Abstract submissions for this session can include, but are not limited to, the following topics: interpretational uncertainty, uncertainty quantification, strategies and methods for uncertainty reduction in model creation and experiments.

Participation of early career geoscientists and researchers from both academic and industry backgrounds is encouraged.