PalMod - Paleo Modelling


(Isotope data for Greenland ice core)PalMod is funded by the Federal Ministry of Education and Science (BMBF) to understand climate system dynamics and variability during the last glacial cycle. Specific topics are:

  • to identify and quantify the relative contributions of the fundamental processes which determined the Earth’s climate trajectory and variability during the last glacial cycle,
  • to simulate with comprehensive Earth System Models (ESMs) the climate from the peak of the last interglacial (the Eemian warm period) up to the present, including the changes in the spectrum of variability, and
  • to assess possible future climate trajectories beyond this century during the next millennia with sophisticated ESMs tested in such a way.

The envisioned approach is innovative in three respects. First, the consortium aims at simulating a full glacial cycle in transient mode and with comprehensive ESMs which allow full interactions between the physical and biogeochemical components of the Earth system, including ice sheets. Second, we shall address climate variability during the last glacial cycle on a large range of time scales, from interannual to multi-millennial, and attempt to quantify the relative contributions of external forcing and processes internal to the Earth system to climate variability at different time scales. Third, in order to achieve a higher level of understanding of natural climate variability at time scales of millennia, its governing processes and implications for the future climate, we bring together three different research communities: the Earth system modeling community, the proxy data community and the computational science community.

The research is intended to be conducted over a period of 10 years, but with shorter funding cycles. 

Expected major outcomes of the first phase (8/2015-7/2019):

  1. Transient simulations of the last termination with ESMs.
  2. Transient simulations of biogeochemistry through the last deglaciation using ESMs including dust sources and transport models.
  3. Comprehensive data synthesis of paleoclimatic conditions during the last glacial cycle, associated with explicit estimates of uncertainty.
  4. Improved run-time performance of ESMs