2020-12-27, 20:00–21:30 (Europe/Berlin), hacc München / about:future
Models, as well as the explanations and predictions they produce, are on everyone's minds these days, due to the climate crisis and the Corona pandemic. But how do these models work? How do they relate to experiments and data? Why and how can we trust them and what are their limitations? As part of the omega tau podcast, I have asked these questions of dozens of scientists and engineers. Using examples from medicine, meteorology and climate science, experimental physics and engineering, this talk explains important properties of scientific models, as well as approaches to assess their relevance, correctness and limitations.
For more than twelve years I have been interviewing scientists and engineers for my podcast omega tau. In many of the conversations, the pivotal importance of models for science and engineering becomes clear. Due to the pandemic and the climate crisis, the meaningfulness, correctness and reliability of models and their predictions is ever present in the media. And because most of us don't have a lot of experience with building and using models, all we can do is to "believe". This is unsatisfactory. I think that, in the same way as we must become media literate to cope with the flood of (fake) news, we must also acquire a certain degree of "model literacy": we should at least understand the basics how such models are developed, what they can do, and what their limitations are.
With this talk my goal is to teach a degree of model literacy. I discuss validity ranges, analytical versus numerical models, degrees of precision, parametric abstraction, hierarchical integration of models, prediction versus explanation, validation and testing of models, parameter space exploration and sensitivity analysis, backcasting, black swans as well as agents and emergent behavior. The examples are taker from meteorology and climate science, from epidemiology, particle physics, fusion research and socio-technical systems, but also from engineering sciences, for example the control of airplanes or the or the construction of cranes.