This Week’s Discoveries | 14 November 2017
- Cornelia Pabst
- Leonard Smith
- dinsdag 14 november 2017
Niels Bohrweg 2
2333 CA Leiden
- De Sitterzaal
Why are we here: The interstellar medium according to SOFIA
Cornelia Pabst (Leiden Observatory)
Cornelia is a PhD student in the group of Xander Tielens at Leiden Observatory, studying the physics and chemistry of the interstellar medium.
The airborne Stratospheric Observatory For Infrared Astronomy (SOFIA) is a unique facility to study the infrared universe. We use SOFIA observations of the fine-structure line of ionized carbon (C+) to study the morphology and kinematics of the interstellar medium, gas and dust in the environment of stars. C+ emission is used as a tracer of the star-formation rate in distant galaxies, its origin, however, is poorly understood. Observations in the Orion Molecular Cloud challenge our understanding of the interplay between stars and gas, the morphology of the interstellar medium, and the origin of C+ emission.
Why the Weather Forecasts of the Future Forecast will Not Forecast the Future?
Leonard Smith ( London School of Economics and Political Science)
Leonard Smith is professor of Statistics at the Department of Statistics, The London School of Economics and Political Science (LSE) and Director of the Centre for the Analysis of Time Series (CATS). His original research interests focused on understanding the mathematics of nonlinear dynamical systems, the analysis of observational data, and the application of insights from those two areas to increase our understanding of actual phenomena. This core has broadened to include research questions on the communication of that understanding to the public, decision makers in industry and policy makers in government on one side, and to the philosophical foundations of uncertainty and mathematical modelling on the other. He is one of the organizers of the workshop “Uncertainty Guidances in Science and Public Policy” that is being held in the Lorentz Center from 13 Nov 2017 through 17 Nov 2017.
Poincare noted that "some hypotheses are dangerous" and went on to say that mathematical physics can render us the service of identifying dangerous assumptions we make without knowing we made them. Different notions of our aims in forecasting physical systems like the weather are discussed in this light. I argue that the insights of nonlinear dynamics, in particular structural model error and the loss of topological conjugacy in nonlinear systems, prevents our making accountable probability forecasts, in much the same way that "chaos" prevents our making accurate point forecasts. An alternative future for the weather forecasting enterprise is suggested.