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The primary focus of PMIP efforts so far has been to look at changes in the mean climate and how these are modelled. However, GCMs also simulate internal variability about that mean state. Its study requires both high resolution proxy data and the storing of larger model datasets - which has been developing through the PMIP iterations.
The purpose of this working group is to encourage and facilitate the study of past climate variability: either amongst models or between models and data.
Historical footnote: group initiated at the PMIP3 2012 Crewe meeting.
Before identifying where the working group should focus its efforts, it was necessary to map the current research landscape. We therefore invited the leading PalaeoENSO researchers to contribute pieces to a collection. This collections appears in the August 2013 issue of the PAGES newsletter.
How should one combine and contrast the different sources of information on past ENSO variability? How should one marry simulations with observations across different periods?
Many people start their research by downloading lots of model data from ESFG and then computing the same diagnostics. This can be a particular hurdle for field/lab-based scientists, who are not so used to handling large model datasets. Chris has run NCAR's Climate Variability Diagnostics Package for all model simulations on the ESFG. The plots and data are available from the PMIPVarData website - along with some example codes to create some additional plots from the data files.
A great advantage of palaeoclimate observations has been the discovery of unforeseen climate transitions and variability. One example of this is the discovery of millennial scale variability in glacial conditions. Currently no systematic tool exists to look for new modes of variability across palaeoclimate simulations. How could we address this?