PMIP Working Groups

· Past2K (Contacts: J. Jungclaus, johann.jungclaus@mpimet.mpg.de)

The WG aims at coordinating research activities using the past1000 and earlier millennium simulations, providing links to the reconstruction community, in particular to the PAGES2K network and to define new strategies both for upcoming analyses and the next generation of simulations.

· Quaternary Interglacials (Contacts: Bette Otto-Bliesner, ottobli@ucar.edu; Dan Lunt, d.j.lunt@bristol.ac.uk)

· PlioMIP2 (Contacts: Alan Haywood, A.M.Haywood@leeds.ac.uk; Harry Dowsett, hdowsett@usgs.gov)

·Deglaciations (Contacts: Ruža Ivanović, R.Ivanovic@leeds.ac.uk; Lauren Gregoire, L.J.Gregoire@leeds.ac.uk; Didier Roche, Didier.Roche@lsce.ipsl.fr)

This Working Group is coordinating efforts to carry out transient simulations of the last deglaciation (~21-9 ka). It is being implemented in close collaboration with the Last Glacial Maximum PMIP Working Group to maintain consistency across the experiments, and the simulations have been/will be specifically designed to include the full range of PMIP models.

·Pre-Pliocene climates (Contacts: Dan Lunt, d.j.lunt@bristol.ac.uk; Bette Otto-Bliesner, ottobli@ucar.edu)

It’s DeepMIP now. The objectives of DeepMIP group are:

To foster closer links between the palaeoclimate modelling and data communities.

To design experiments for the MIP, through discussion with both model and data communities.

To carry out such simulations with a wide range of state-of-the-art models.

To create and collate and synthesise datasets where appropriate to enable meaningful model-data comparisons.

To analyse the results with the aims of evaluating the models, understanding the reasons behind the model-model and model-data differences, and, where possible, providing suggestions for model improvements.

To carry out the above in such a way as to facilitate contribution to the IPCC.

DeepMIP is part of the Paleoclimate Modelling Intercomparison Project (PMIP), which itself is affiliated to CMIP6.

· P2FVAR (Past2Future: insights from a constantly varying past. Contacts: Julia Hargreaves, jules@blueskiesresearch.org.uk; Chris Brierley, c.brierley@ucl.ac.uk; Pascale Braconnot, pascale.braconnot@lsce.ipsl.fr)

This working group seeks to help climate scientists make the best use of the fact that CMIP6/PMIP4 includes so many models and time periods. This is a great source of information that represents a lot of effort by researchers from across the world - and then donated to the rest of the community. However it is such a large and complicated dataset that gleaning those insights can be a challenge. This working group exists to make analyses using multiple models, multiple time periods easier to undertake. The working group has put together a series of resources that provide easy access to some standard model fields, links to relevant paleo-observations, methdologies for performing analysis, examples of prior studies using them, and even some software for researchers to undertake initial analyses.

· PMIP-DATA (Contacts: Sandy P. Harrison, s.p.harrison@reading.ac.uk; Patrick (Bart) Bartlein, bartlein@uoregon.edu; Michel Crucifix, michel.crucifix@uclouvain.be; Andre Paul, apaul@marum.de; Allegra N. LeGrande, allegra.n.legrande@columbia.edu)

The purpose of the PMIP-DATA working group is to facilitate, support and coordinate model evaluation and benchmarking using palaeoenvironmental observations.

The working group will promote:

• data synthesis in both the terrestrial and marine realms
• the development of tools and new approaches for data analysis and data-model comparison
• the role of data assimilation in improving our understanding of past climate
• the exploration of new uses palaeoenvironmental data to address global change issues
• The working group will also be responsible for coordinating model evaluation and benchmarking exercises within CMIP6/PMIP4.

· PMIP infrastructure (Contacts: M. Kageyama, Masa.Kageyama@lsce.ipsl.fr; Jean-Yves Peterschmitt, Jean-Yves.Peterschmitt@lsce.ipsl.fr)

Everything related to the distribution and use of PMIP data.

Sessions and abstracts