ITS1.6/CL0.3 | Integrating Earth System Reconstructions and Climate Modeling: Forcing, Uncertainties, and Next-Generation Digital Twins
EDI
Integrating Earth System Reconstructions and Climate Modeling: Forcing, Uncertainties, and Next-Generation Digital Twins
AGU and WMO
Convener: Lina TeckentrupECSECS | Co-conveners: Haipeng LiECSECS, Jarmo KikstraECSECS, Guillaume Dupont-Nivet, Camilla MathisonECSECS, Christopher Smith, Alexander J. WinklerECSECS

Earth System Models (ESMs), climate forcing, and Earth system reconstructions are crucial for understanding climate dynamics. However, disparities in responses to forcing agents, system coupling - particularly across CMIP - as well as the integration of reconstructions, present significant challenges. This session combines insights from deep-time Earth system reconstructions with cutting-edge climate modeling to enhance our understanding of past, present, and future climate change. We highlight the role of anthropogenic and natural forcings, the importance of addressing model uncertainties in CMIP and beyond, opportunities to develop next-generation digital twins of our planet, and present CMIP7 forcings. This session features contributions that span the following themes:

1. Earth System Reconstructions and Digital Twins
- Integrating paleogeographic data and advanced modeling (e.g., machine learning) to reveal past environmental changes and major Earth system transitions.
- Building digital twins of the planet by fusing diverse datasets and numerical models, emphasizing open, community-driven approaches.

2. Anthropogenic and Natural Forcing for CMIP6, CMIP7, and beyond
- Developing and evaluating historical and future time series of climate drivers (e.g., greenhouse gases, aerosols, land-use changes).
- Investigating how changes in forcing propagate through the climate system, using both observational data and idealized or multi-model experiments (CMIP6, CMIP7, etc.).

3. Model Disparities and Uncertainty
- Identifying the causes of divergent outcomes within CMIP ensembles, including internal variability, parameterization, external forcings, and ESM architectures.
- Employing reduced-complexity models and emulators to capture underexplored regions of uncertainty and guide more robust climate projections.

4. Critical Model Development and Impact Research
- Refining ESMs to reduce uncertainties and improve model performance, with emphasis on interdisciplinary approaches.
- Addressing regional-scale challenges in using CMIP outputs for impact studies, ensuring that policymakers and non-experts can effectively interpret climate projections.

We encourage submissions that bridge these topics, highlight open research and interdisciplinary collaboration, and showcase the work of early career researchers.