Course goals
Gain comprehensive knowledge about the astronomical influence on climate and the development of high-resolution integrated geological time-scales and their applications in paleoclimatic and other Earth science studies. Training in how to carry out individual / teams assignments by means of computer-practicals and presentation (written/oral) of results.
Content
Paleoclimatic research dedicated to unravel natural climate variability is becoming increasingly important in view of current global warming. Astronomical forced climate change related to the Earth’s orbital parameters represent a crucial and integral part of the natural behavior of the climate system in the past on millennial to million year time scales. Paleoclimate studies has solved the problem of the Ice Ages and focused on the orbital theory of the Monsoon. In this course we will focus on climate forcing by the Earth’s orbital parameters computed by means of astronomical solutions for the Solar System. In addition, we will focus on the use of (Milankovitch) cycles to construct geological time scales with an unprecedented resolution and accuracy that are necessary for climate studies of the past and on mathematical methods to statistically detect cyclic variability in paleoclimate records. The course is divided in two parts that are intricately linked:
Astronomical time scales and their applications: Introduction and astronomical solutions; Time scale development and spectral analysis; Ar/Ar dating and geodynamic linkages; Cyclostratigraphy and link to sequence stratigraphy.
Astronomical forcing of climate: Astronomical climate forcing and phase relations; Climate modelling of orbital variations; Sub-Milankovitch cyclicity.
During the computer practicals students will operate in teams of 2 and learn how to use statistical methods (spectral, wavelet) to detect astronomical climate forcing in paleoclimatic archives and determine phase relations between cyclic climate changes and insolation forcing. In addition results of climate modeling experiments will be statistically analysed using the same methods.
Students (in teams of 2) will further have to write an essay on a topic related to the contents of the course and based on scientific publications. They will also have to give a powerpoint presentation of 15-20 minutes that will be marked by fellow students as well.
