In an era of science that uses numerical models to better understand physical processes occurring on Earth, there is an increasing demand for robust empirical datasets to constrain these simulations. Generating robust datasets, especially data sets that express stratigraphic positions of sedimentary deposits as ages, often involves the use of multiple, independent geochronological techniques (e.g. different kinds of radioisotopic dating, magneto-, bio-, cyclostratigraphy and sedimentologic relationships along the succesion). The integration of these different kinds of geochronological information often poses challenges.

Age-depth models are the ultimate result of the integration of different geochronological techniques, and range from linear interpolation to more complex Bayesian techniques. We will introduce several modelling concepts and their application in a range of paleoenvironmental and paleoclimatic records. The Short Course will provide an introduction to the field of (Bayesian) age-depth models and will highlight the assumptions, benefits and limitations of different model approaches. It will prepare participants for independent application of suitable age-depth models to their data.