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Today's "Freiburger Horizonte" Lecture: Hans von Storch on Climate Models

In our lecture series "Freiburger Horizonte", Professor em. Dr. Hans von Storch, meteorologist and head of the institute for coastal research (Helmholtz Centre Geesthacht) talks tonight about climate models. He will concentrate on different types of models and their application as well as their intentions. His main aim is to discuss what kind of knowledge each model generates and for what reason.
Today's "Freiburger Horizonte" Lecture: Hans von Storch on Climate Models

(c) J. Xu

Popularizing scientific knowledge can be risky. The best example is the research on climate change. Only a few other topics seem to polarize the public as strongly as climate change. Professor emeritus Dr. Hans von Storch, meteorologist, and climate researcher, warns against a "hype of climate-anxiety". Instead, he pleas for sustainable research on climate true to the motto of "creating knowledge".

This is also the topic of Von Storch's lecture in the series "Freiburger Horizonte". Taking account of different models for different purposes and contexts, he differentiates conceptual models that simplify to a high degree and aim at facilitating understanding, and numeric, quasi-realistic models which have a high level of complexity and are used when future developments of climate systems are to be evaluated, for instance, while considering regulations for the emission of greenhouse gases. On this foundation, von Storch will discuss what kind of knowledge different models create.

Freiburger Horizonte - Hans von Storch

The speaker

Hans von Storch is a professor emeritus for meteorology at the University of Hamburg. From 2008 until 2015, he directed the "Institut für Küstenforschung" of Helmholtz Centre Geesthacht. He is also author of the book "Die Klimafalle: Die gefährliche Nähe von Politik und Klimaforschung“ (2013).

The lecture is thematically linked to this year's research focus "Environmental Forecasting". Its researchers analyze a variety of models from different disciplines (including meteorology), intending to deduce a best practice for reliable environmental prognoses.