Breakout Group A: What should the research questions and priorities in paleoscience be for the next 10 years?

How can we improve model-based estimates and predictions? How can we improve the production of paleo data? How can we better constrain past rates of change in the Earth system? These questions, among others, were identified as key priorities for future paleoscience during our breakout sessions at the YSM.

We identified that model-based climate sensitivity estimates and the ability to correctly capture climate feedbacks, abrupt transitions, and threshold behavior in models are key to predicting climate and associated changes. Integrated earth-system modeling with improved feedback interactions will be required to study whole-earth system dynamics.

Furthermore, assessing climate model performance requires better datasets of high-resolution proxy reconstructions: We need more high-quality data from under-represented regions. We also need new proxies for several climate variables. Also high on our wish list are solid constraints upon previously unresolved climate system components such as clouds and aerosols. We require better solar and volcanic forcing reconstructions, and we should strive to understand the underlying causes of discrepancies between the different forcing reconstructions available.

To improve the quality of our proxy networks we need to employ replication, high-resolution dating, statistical analysis and multi-proxy approaches in our research. Data uncertainty estimates should always be clearly stated. Process studies and controlled experiments must be used to establish regional calibrations and transfer functions to allow proxy-based reconstructions to capture not only high-frequency climate variability, but also a quantifiable climatic parameter such as temperature or precipitation.

Finally, we need to compile datasets and make them available in a quality-controlled, well-documented and easy-to-use form. Strict formats for “big data” should be employed in a globally acknowledged framework. The field could vastly benefit from larger collaboration with computer software engineers and informatics science to improve efficiency and manageability of earth science datasets.

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