TM2 | The Pliocene Model Intercomparison Project Phase 3 (PlioMIP3)
The Pliocene Model Intercomparison Project Phase 3 (PlioMIP3)
Convener: Alan Haywood | Co-convener: Julia Tindall
Tue, 29 Apr, 19:00–20:00 (CEST)
 
Room 0.49/50
Tue, 19:00
The Pliocene Model Intercomparison Project Phase 3 (PlioMIP3) aims to improve our understanding of Earth System behaviour in the Pliocene – a warm climate of the past where CO2 levels were similar to today. This townhall will bring together scientists from a number of institutions to discuss progress on PlioMIP3. Since PlioMIP3 is an international collaboration it can be difficult for the community to meet in person, and this townhall will be a valuable opportunity to complement online meetings that are already taking place.

Modelling groups will be able to update the community on their progress and to discuss problems and potential solutions. The best way of coordinating the scientific outcomes will be discussed, in order to ensure maximum impact of the project. The townhall will also provide an opportunity for Early Career Researchers and PhD students, who have recently started working on the Pliocene, to meet the community.

The target audience is mainly scientists who are running the PlioMIP3 experiments and analysing the model output. However, it will also be of interest to the wider Pliocene community and scientists who model other time periods. For example, there are numerous opportunities for Pliocene data-model comparison – which will be discussed. Also, it is useful for all model intercomparison projects to work together for maximum scientific impact, and the townhall will provide a space where we can discuss how this will be achieved. It will benefit the project to get feedback on expected scientific outcomes from the wider audience that will be attending EGU.

We anticipate that the townhall will advance the PlioMIP3 project, by providing project updates, sharing ideas, and making decisions about the best way forward. Ultimately the project will provide an increased understanding of warm climates, including physical processes, uncertainties, and the synergies between models and data.