CMIP at AGU24
9 December @ 08:00 – 13 December @ 17:00 US/East Coast
This December, AGU24 returns to Washington, D.C. with the theme “What’s Next for Science”.
On this page:
- Call for abstract submissions
- CMIP events
Call for Abstract Submissions
Submit your abstract to AGU24 by Wednesday, 31 July 23:59 EDT/03:59 +1 GMT.
Abstracts should focus on scientific results, enabling Earth and space science or its application, and/or the contribution of Earth and space science to society.
The session viewer, approved sessions, and submitted abstracts can be viewed here. Please note, this is not the final meeting schedule, the scientific program will be published in October.
Submission Fees
The abstract submission fee is:
- a required and non-refundable processing fee.
- separate from membership dues and meeting registration fees.
- not based on approval of your abstract submission or attendance at the meeting.
- payable by credit card only; wire payments or purchase orders cannot be accommodated.
2024 Abstract Submission Fees
Regular Fee – $70 USD
Student Fee – $40 USD
Low Income/Lower-Middle Income* – No Fee
*Please see 2024 fiscal year World Bank country classifications by income level table for more information.
CMIP events
Addressing and Understanding Uncertainties in CMIP: Key Insights and Future Directions (B001)
Conveners: Lina Teckentrup, Barcelona Supercomputing Center, Barcelona, Spain, Indrani Roy, UCL Institute for Risk and Disaster Reduction, London, United Kingdom, Alexander J. Winkler, Max Planck Institute for Biogeochemistry, Department of Biogeochemical Integration, Jena, Germany, Wandi Yu, Lawrence Livermore National Laboratory, Livermore, United States and Camilla Mathison, Met Office, Exeter, United Kingdom
Abstract: The Coupled Model Intercomparison Project (CMIP) is instrumental in advancing our understanding of the Earth’s climate system and its future projections. However, Earth system models (ESM) exhibit disparities in critical aspects, particularly in their responses to anthropogenic forcings and the intricate coupling of physical and biogeochemical systems. Given that the Earth system science community, and notably the IPCC, relies on CMIP outputs to inform policy and mitigation strategies, it becomes imperative to address these inherent uncertainties through a multidisciplinary approach that unites atmospheric, oceanic, cryospheric and terrestrial modeling analyses. In this session, we invite studies that investigate uncertainties and model disagreements across all facets associated with CMIP projections. These may include contributions, but are not limited to:
- Identification of processes and key entities with significant disparities across CMIP models
- Critical scientific priorities for future CMIP/Earth system model development
- Opportunities, challenges, and constraints in using CMIP output for impact research
Systematic Benchmarking and Evaluation of Climate and Earth System Models (GC142)
Conveners: Jiwoo Lee, Lawrence Livermore National Laboratory, PCMDI, Livermore, CA, United States, Paul Ullrich, Lawrence Livermore National Laboratory, Livermore, United States, Elizabeth Maroon, University of Wisconsin Madison, Madison, WI, United States and Fiaz Ahmed, University of California, Los Angeles, Dept. of Atmospheric and Oceanic Sciences, Los Angeles, United States
Abstract: Having credible Earth System Models (ESMs) is essential for climate change research. Systematic and routine evaluation of multiple ESMs in a collective manner is important for not only expediting the evaluation cycle but also for ensuring comprehensive documentation of data quality. This importance has grown as the data burden of ESMs push from the petabyte to exabyte scale through projects such as the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the forthcoming CMIP7. The evaluation of ESMs has become more challenging with higher resolution and enhanced complexity of models. To advance the integration of benchmarking and evaluation into routine simulation or model development workflows, this session invites studies that explore benchmarking of ESMs, new and informative diagnostics (including process-oriented diagnostics), science performance metrics, development of evaluation tools or database, and model versus observational uncertainties. We also welcome presentations on strategies to efficiently deploy diagnostics during model development.
Climate forcing: quantifying the roles and responses of anthropogenic and natural climate drivers (GC046)
Conveners: Paul James Durack, Lawrence Livermore National Laboratory, Program for Climate Model Diagnosis and Intercomparison, Livermore, CA, United States and Dr. Vaishali Naik, Ph.D., NOAA/ Geophysical Fluid Dynamics Laboratory, Princeton, United States
Abstract: Climate change results from atmosphere constituent modulation affecting the top-of-atmosphere energy balance, or land use changes at the Earth’s surface, altering surface albedo, amongst other “forced” changes. These natural or anthropogenic climate drivers are termed “climate forcing” agents. This session highlights research assessing and quantifying uncertainties in forcing agent evolution and their climate influence using Earth System Model simulations, or Earth observations. We invite contributions on all climate forcing research aspects, including the development of historical and future forcing time-series, analyses that use idealized, single- or multi-model approaches, or observational methods to evaluate the climate change impacts. We are especially interested in studies that examine the responses to forcing changes through time, using next-generation (CMIP7), current (CMIP6, CMIP6Plus), or previous CMIP phases. Research considering multiple components of the climate system (the ocean, atmosphere, cryosphere, land surface/subsurface, and biology) and provides evidence for linkages and coherent forced responses is highly encouraged.
Exploring Coupled Earth System Interactions: Bridging Knowledge Gaps and Model Representation (A080)
Conveners: Chayan Roychoudhury, University of Arizona, Department of Hydrology and Atmospheric Sciences, Tucson, AZ, United States, Benjamin Gaubert, National Center for Atmospheric Research (NCAR), Atmospheric Chemistry Observations & Modeling Laboratory (ACOM), Boulder,CO, United States, Rajesh Kumar, National Center for Atmospheric Research, Research Applications Laboratory, Boulder, CO, United States, Duncan Watson-Parris, University of California San Diego, La Jolla, United States and Benjamin Gaubert
Abstract: Representation of the coupled interactions within Earth System Models (ESMs) is crucial for predicting medium-range and high-impact weather and ensuring reliable climate projections. This session invites submissions that explore these complex interactions within the Earth system, spanning the atmosphere, land, and biosphere. From atmospheric composition to meteorology and land feedbacks, we seek contributions that elucidate the complexity of different Earth system processes and explore them through both Darwinian (highlighting specific components of this complexity) and Newtonian (evaluating system-wide complexity) paradigms. We welcome studies utilizing observational data, traditional modeling approaches (i.e. data-denial experiments and perturbed parameter ensembles), data assimilation in coupled ESMs, model inter-comparisons like CMIP, as well as explainable/interpretable artificial intelligence techniques to investigate these interactions across different spatio-temporal scales. Emphasis will be placed on identifying key variables and their joint sensitivity driving non-linear phenomena, benchmarking coupling in climate models, and exploring the climate impact of these coupled processes.
Open and FAIR Data in Climate Change Assessments and Research (IN037)
Conveners: Xiaoshi Xing1,2, Martina Stockhause3,4, April Lamb5,6, David Milward7,8 and Yasmine Daouk2,9, (1)IPCC TG-Data (DDC); NASA SEDAC, Palisades, United States(2)Columbia University in New York, Palisades, United States(3)IPCC TG-Data (DDC), Hamburg, Germany(4)German Climate Computing Centre (DKRZ), Hamburg, Germany(5)NOAA’s Assessments Technical Support Unit (TSU); IPCC AR7 WGIII Technical Support Unit (TSU) – Asheville, Asheville, United States(6)North Carolina State University, North Carolina Institute for Climate Studies, Asheville, United States(7)IPCC Data Distribution Centre, Warwick, United Kingdom(8)MetadataWorks, UK, Warwick, United Kingdom(9)NASA SEDAC, Palisades, United States
Abstract: Global assessments on climate change (e.g. IPCC Assessment Reports) and national climate assessments (e.g. U.S. National Climate Assessments) are based on peer-reviewed literature and data. Climate change research in general is also data driven. Open and FAIR (findable, accessible, interoperable, and reusable) data and transparent data usage are essential for robust processes and the key elements of Open Science.
In this session, we showcase and explore:
- Open and FAIR data provided for or created during assessments or research.
- Open and FAIR tools facilitating processes, like figure creation, data dissemination, including metadata schemas, catalogs, and interactive components.
- Best practices like licensing, citations, provenance, and interlinking/knowledge graphs.
- New approaches supporting future assessments and research, like AI/ML tools.
We invite institutions, agencies, and individuals to present their data, tools, best practices, experiences, lessons learned, and plans to enhance Open Science practices for the benefit of the scientific community, policy makers, and our society.
Advances in Emulating Earth System Models (GC012)
Conveners: Björn Lütjens, Massachusetts Institute of Technology, Kalyn Dorheim, Pacific Northwest National Laboratory/Joint Global Change Research Institute, Claudia Tebaldi, Pacific Northwest National Laboratory/Joint Climate Change Research Institute, Duncan Watson-Parris, University of California San Diego
Abstract: Earth system models can only be run for a small selection of possible emission scenarios due to their computational complexity. Approximations of Earth system models, such as reduced complexity climate models or emulators, then leverage their generated data and scenario forcings to interpolate to new emission scenarios. However, existing emulators can break down for emulating overshoot scenarios, irreversible changes, (compound) extreme events, or aerosol forcings. Further, demands to produce high spatiotemporal output that captures the internal variability of the Earth System remains challenging.
We welcome submissions from the machine learning, as well as, the reduced complexity climate modeling communities to encourage an interdisciplinary exchange including, but not limited to:
– Benchmarking and validation protocols including scenario requirements
– Applications of emulators
– Theoretical insights
– Reduced-complexity climate models
– Probabilistic emulation techniques, such as Weather generators, diffusion, GPs, EVT
– (Hybrid) deep learning approaches including neural operators, SSMs, foundation models
The global water cycle: coupling and exchanges of mass and energy between the ocean, land, cryosphere, and atmosphere (GC049)
Conveners: Paul James Durack, Lawrence Livermore National Laboratory, John T Reager, NASA Jet Propulsion Laboratory, Nadya Vinogradova Shiffer, NASA Headquarters, Francis H Lambert, University of Exeter
Abstract: This session highlights water cycle research emphasizing the Earth as a connected system, describing linkages between the ocean, atmosphere, cryosphere, and land surface and subsurface processes. Contributions are invited on all aspects of water cycle research, including analyses undertaken using in situ and space-borne observations from current (e.g., GO-SHIP, Argo, SMAP, SMOS, GRACE-FO, GPM, GCOM-W, SWOT), past (e.g., Aquarius, TRMM, GRACE), and future (e.g., CIMR) satellite missions, estimates based on numerical models, data assimilation products, as well as climate model projections, links to the global energy cycle, and theoretical contributions. We particularly welcome studies that consider multiple realms (the ocean, atmosphere, cryosphere, land surface, and subsurface) and provide compelling evidence for linkages, describing coherent water cycle variability and change. We welcome global and regional assessments across these interfaces and contributions that demonstrate what needs to be observed to ensure that long-term changes in the water cycle are accurately quantified.
