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Session Proposal: Open Earth System Science Data and Artificial Intelligence (AI) / Machine Learning (ML) Advance Scientific Discovery (AGU25)

IN034
Open Earth System Science Data and Artificial Intelligence (AI) / Machine Learning (ML) Advance Scientific Discovery

Session ID#: 251103

Session Description:
The volume, velocity, variety, veracity, and value of Earth and environmental data are increasing rapidly. Data from observational networks, remote sensing and modeling platforms are expanding with ever increasing spatial resolution and temporal sampling. To realize the promise of new scientific discoveries in Earth system science, new analysis paradigms, novel hardware and software infrastructure, efficient and scalable data discovery, access, and management tools are required. This session solicits abstracts that describe high performance storage and computing infrastructure; data access and analytics platforms; strategies for fostering or ensuring FAIR (findability, accessibility, interoperability, and reusability) data principles; unique methods for data fusion, synthesis, and analysis of open data; standards for AI-ready training and benchmarking data; methods for building and using ML foundational models from Big Data archives; advances in research data platforms and technologies; and reports on scientific discoveries or research results employing large and/or complex Earth system science data.
Co-Sponsor(s):
  • A - Atmospheric Sciences
  • B - Biogeosciences
  • H - Hydrology
  • OS - Ocean Sciences
Index Terms:

1912 Data management, preservation, rescue [INFORMATICS]
1916 Data and information discovery [INFORMATICS]
1932 High-performance computing [INFORMATICS]
1942 Machine learning [INFORMATICS]
Primary Convener:  Forrest M. Hoffman, Oak Ridge National Laboratory, Computational Sciences & Engineering Division, Oak Ridge, TN, United States
Conveners:  Maxwell Grover, Argonne National Laboratory, Argonne, IL, United States, Charuleka Varadharajan, Lawrence Berkeley National Laboratory, Earth and Environmental Sciences Area, Berkeley, United States and Justin Jay Hnilo, U.S. Department of Energy, Germantown, MD, Washington, United States
Student/Early Career Convener:  Maxwell Grover, Argonne National Laboratory, Argonne, IL, United States
 
A novel workflow and reporting format for processing environmental sensor outputs into AI/ML-ready data and metadata (1848031)
Stephanie C Pennington, American Geophysical Union, Washington, DC, United States and Ben P Bond-Lamberty, Pacific Northwest National Laboratory, College Park, United States
 
Achieving AI-Readiness Through Modular Workflows for Data Generation, Management, and Publishing (1874239)
Vanessa Alessandra Garayburu-Caruso1, Amy E Goldman2, Brieanne K. Forbes3, Chris R Vernon4, Xingyuan Chen5, Yunxiang Chen5, Peter Regier3, Jie Bao3, Sundar Niroula3, Jianqiu Zheng3 and James Stegen3, (1)Pacific Northwest National Laboratory, Environmental Molecular Sciences Laboratory, Richland, United States, (2)Pacific Northwest National Laboratory, Biological Sciences, Richland, WA, United States, (3)Pacific Northwest National Laboratory, Richland, WA, United States, (4)Joint Global Change Research Institute, College Park, United States, (5)Pacific Northwest National Laboratory, Richland, United States
 
A Large-Scale Multi-modal Foundation Model for Fusing Complex Earth Observation Data (1884916)
Thomas Vandal, Zeus AI, Cambridge, United States and Kate Duffy
 
Revisiting Controls on Hyporheic Zone Respiration: Integrating Mechanistic and Deep-Learning Models with Continental-Scale Observations (1929138)
Jianqiu Zheng1, Vanessa Alessandra Garayburu-Caruso2, Timothy D Scheibe1 and James Stegen1, (1)Pacific Northwest National Laboratory, Richland, WA, United States, (2)Pacific Northwest National Laboratory, Environmental Molecular Sciences Laboratory, Richland, United States
 
Revealing the Butterfly Effect in Deep Learning Weather Prediction Model via Kinetic Energy Spectra Change (1931773)
Hisu Kim, GIST Gwangju Institute of Science and Technology, Department of Environment and Energy Engineering, Gwangju, South Korea and JinHo Yoon, Gwangju Institute of Science and Technology, Department of Environment and Energy Engineering, Gwangju, South Korea
 
A large-scale dataset for training deep learning segmentation and tracking of extreme weather (1950419)
Sol Kim1, Andre Graubner2, Lukas Kapp-Schwoerer2, Karthik Kashinath3 and Konrad Schindler4, (1)University of Chicago, Chicago, IL, United States, (2)ETH Zurich, Zurich, Switzerland, (3)NVIDIA Corporation, Santa Clara, CA, United States, (4)Institute of Geodesy and Photogrammetry, ETH Zurich, Zurich, Switzerland
 
Navigating ESGF with AI: Domain-Specific LLM for Earth System Data (1954131)
Daniel Saedi Nia1, Elias Massoud1, Bharat Sharma1, Forrest Hoffman1, Jitendra Kumar2, Nathan Collier1 and Sheryl Arya1,3, (1)Oak Ridge National Laboratory, Computational Sciences & Engineering Division, Oak Ridge, United States, (2)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, United States, (3)Arizona State University, Computational Sciences & Engineering Division, Tempe, United States
 
Data-driven Modelling of Global Belowground Productivity (1960293)
Bin Wang, Oak Ridge National Lab, Computational Sciences and Engineering Division, Oak Ridge, TN, United States, Min Xu, Oak Ridge National Laboratory, Climate Change Science Institute, Oak Ridge, United States, Elias Massoud, Oak Ridge National Laboratory, Computational Sciences & Engineering Division, Oak Ridge, United States, Zheng Shi, University of Oklahoma, Institute for Environmental Genomics, Department of Microbiology and Plant Biology, Norman, United States, Xi Zhang, Oak Ridge National Laboratory, Computer Science and Mathematics Division, Oak Ridge, United States and Forrest M Hoffman, Oak Ridge National Lab, Oak Ridge, United States
 
Revolutionizing Atmospheric Data Discovery and Access Through AI-Driven Innovations at the ARM Data Center (1963489)
Chirag Shah1, Wade Darnell1, Austin Aguilar1, Hannah Collier1, Eric Enright1, Dustin Rapp1, Vasile Garbulet1, Franklin Parry1, Zachary Medley1, Felipe Almeida2, Michael Giansiracusa1 and Giri Prakash1, (1)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, United States, (2)Universidade de São Paulo, São Paulo, Brazil
 
Accelerating AI development in environmental science through a community-driven learning journey approach (1966294)
Yuhan Rao, North Carolina State University, Cooperative Institute for Satellite and Earth System Studies, Asheville, United States, Robert J Redmon, NOAA National Centers for Environmental Information, Boulder, United States and Christopher Slocum, Center for Satellite Applications and Research, Fort Collins, United States
 
Bridging Earth System Modeling and Societal Impact: A Scalable SPEAR Data Delivery System for Informed Decision-Making (Invited) (1968543)
Aparna Radhakrishnan1, Soelem Aafnan Bhuiyan1, Aria Radick2, Jake Zappala3, Whit Anderson4, Daniel Barrie5, Kirsten Lynn Findell6, Matt Harrison4, Amanda McCarty7, Hiroyuki Murakami8, Haiyan Teng9, Russell S Vose10 and Chandin Wilson2, (1)Princeton University, Princeton, United States, (2)SAIC, Alexandria, United States, (3)SAIC, Princeton, United States, (4)Geophysical Fluid Dynamics Laboratory, Princeton, United States, (5)NOAA Climate Program Office, Silver Spring, MD, United States, (6)NOAA, Princeton, United States, (7)NOAA Washington DC, Washington, DC, United States, (8)NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, United States, (9)Pacific Northwest National Laboratory, Richland, United States, (10)National Climatic Data Center, Asheville, NC, United States
 
Towards Globally Harmonized Environmental Data: Data Harmonization Methodology and Lessons from GERI (1969502)
Krutika Deshpande1, Benjamin L Ruddell1, Cedric Hagen2, Hank W Loescher2,3, Michael SanClements2,3, Christine M Laney2, Thomas G Bornman4, Gregor T Feig4, Leo Chiloane4, Elisa Girola5, Guru Siddeswara6, Beryl Morris5, Paula Mabee2, Michael Mirtl7,8, Pamela L Sullivan9, Emmanual Salmon10, Melinda Dianne Smith11, Werner Leo Kutsch10, Steffen Zacharias12, Jaana K Back13, Tyson Lee Swetnam14, Nirav Merchant15 and Xiubo Yu16, (1)Northern Arizona University, School of Informatics, Computing, and Cyber Systems, Flagstaff, United States, (2)Battelle, National Ecological Observatory Network (NEON), Boulder, United States, (3)Institute of Alpine and Arctic Research, University of Colorado, Boulder, United States, (4)South African Environmental Observation Network (SAEON), Elwandle Coastal Node, Gqeberha, South Africa, (5)Terrestrial Ecosystem Research Network (TERN), The University of Queensland, Brisbane, Australia, (6)Terrestrial Ecosystem Research Network (TERN), The University of Queensland, Indooroopillay, Australia, (7)Helmholtz Centre for Environmental Research GmbH, Leipzig, Germany, (8)Umweltbundesamt GmbH, Environment Agency Austria, Vienna, Austria, (9)Oregon State University, College of Earth, Ocean, and Atmospheric Sciences, Corvallis, United States, (10)ICOS ERIC, Head Office, Helsinki, Finland, (11)Colorado State University, Department of Biology and Graduate Degree Program in Ecology, Fort Collins, CO, United States, (12)Helmholtz Centre for Environmental Research UFZ Leipzig, Department of Monitoring and Exploration Technologies, Leipzig, Germany, (13)Institute for Atmospheric and Earth System Research, University of Helsinki, Helsinki, Finland, (14)University of Arizona, CyVerse, Tucson, United States, (15)University of Arizona, Cyverse, Tuscon, United States, (16)Chinese Ecosystem Research Network, Chinese Academy of Sciences (CERN), Beijing, China
 
AMOVALIH: Hybrid Intelligence for Marine Biodiversity Assessment Integration with MINKA (1973259)
Ivan Rodero, Quanta Systems, S.L., Badalona, Spain, Andreu Fornós, Institut de Ciències del Mar - Spanish National Research Council,, Department of Physical and Technological Oceanography - EMBIMOS, Barcelona, Spain and Jaume Piera, Institut de Ciències del Mar - Spanish National Research Council, Department of Physical and Technological Oceanography - EMBIMOS, Barcelona, Spain
 
Leveraging AI Standards on Synthesized Data Gathered from Across the pan-Arctic (1985743)
Michele Thornton1, Terri Velliquette1, Natalie Griffiths2 and Jitendra Kumar1, (1)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, United States, (2)Oak Ridge National Laboratory, Oak Ridge, TN, United States
 
Guiding Responsible Use of Geoscience Data in AI/ML Contexts: Reducing Risks from Lack of Data Fitness-for-Purpose (1987962)
Monica Ainhorn Ainhorn Morrison, NSF National Center for Atmospheric Research, Boulder, United States
 
Democratizing Access to NSF NCAR’s Research Data (1988509)
Douglas Schuster1, Harsha Hampapura1, Riley Conroy1, Brian Bockelman2 and NSF NCAR, Computational and Information Systems Lab, Information Science and Services Section, (1)NSF National Center for Atmospheric Research, Boulder, United States, (2)Morgridge Institute for Research, Madison, United States
 
The Next Generation Earth System Grid Federation (ESGF) Distributed Data Infrastructure (1989584)
Forrest M. Hoffman, Oak Ridge National Laboratory, Computational Sciences & Engineering Division, Oak Ridge, TN, United States, Philip Kershaw, NCEO / Centre for Environmental Data Analysis, STFC, Rutherford Appleton Laboratory, Didcot, United Kingdom, Sasha Ames, Lawrence Livermore National Laboratory, Livermore, CA, United States, Rachana Ananthakrishnan, University of Chicago, Chicago, IL, United States, Laura Carriere, NCCS, NASA Goddard, Greenbelt, MD, United States, Stephan Kindermann, DKRZ German Climate Computing Centre, Data Management, Hamburg, Germany, Christian Page, CERFACS, Climate Modeling and Global Change, Toulouse, France, Aparna Radhakrishnan, Geophysical Fluid Dynamics Laboratory, Princeton, United States and Andrew Robinson, Australian National University National Computational Infrastructure, Canberra, Australia
 
GELOS: A Benchmark Dataset for Geospatial Exploration of Latent Observation Space (1990043)
Denys Godwin1, Rufai Balogun2, Sam Khallaghi2, Yao-Ting Yao2, Sujit Roy3, Rahul Ramachandran3 and Hamed Alemohammad, PhD2, (1)Clark University, Clark Center for Geospatial Analytics, Worcester, MA, United States, (2)Clark University, Clark Center for Geospatial Analytics, Worcester, United States, (3)NASA Marshall Space Flight Center, Huntsville, United States
 
Cloud to Community: Enabling Earth Science Through Open, FAIR Data (1994061)
Katie Baynes, NASA Headquarters, Earth Science Data Systems, Washington, DC, United States
 
AI for Research Infrastructures: Enhancing NEON Field Operations and Efficiency with Novel Safety Forward Tools (1994419)
Michael SanClements1, Tyler Karns2, Cedric Hagen1 and Connor Keating2, (1)Battelle, National Ecological Observatory Network (NEON), Boulder, United States, (2)Battelle, AS&T, Columbus, United States
 
Using AI/ML to Accelerate NASA Scientific Research and Discovery with the Science Explorer (1998693)
Mugdha Polimera1, Anna Kelbert2, Alberto Accomazzi3, Kelly Lockhart4, Felix Grezes4, Stephanie Jarmak5, Jean-Claude Paquin4, Taylor Jacovich4 and The SciX Team, (1)Center for Astrophysics | Harvard & Smithsonian, Cambridge, MA, UNITED STATES, (2)Harvard-Smithsonian Center for Astrophysics, Science Explorer (SciX), Cambridge, MA, United States, (3)Harvard-Smithsonian Center for Astrophysics, NASA Science Explorer (SciX), Cambridge, MA, United States, (4)Harvard-Smithsonian Center for Astrophysics, Cambridge, United States, (5)University of Central Florida, Orlando, United States
 
Bridging Big Earth Data and AI-integrated Workflows with the National Data Platform: A Case for FAIR, Composable, and Scalable Services (2004434)
Ilkay Altintas1, Manish Parashar2, Melissa Floca1, Jess Tate3, Saleem Alharir4, Charles Meertens5, Kate O'Laughlin6 and Amarnath Gupta7, (1)University of California San Diego, La Jolla, United States, (2)University of Utah, Scientific Computing and Imaging Institute, Salt Lake City, United States, (3)University of Utah, Salt Lake City, United States, (4)U Utah, SLC, United States, (5)UNAVCO, Inc., Boulder, CO, United States, (6)University of California San Diego, San Diego, United States, (7)University of California San Diego, La Jolla, CA, United States
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