Enter Note Done
Go to previous page in this tab
Session
  • Poster
  • Bookmark Icon
  • H23W: Advancing Prediction, Theory, and Causal Understanding in Geosciences through AI and Big Data GeoBurst Session IV Poster
  • Schedule
    Notes
  • NOLA CC
    Set Timezone
  •  
    View Map

Generic 'disconnected' Message
Primary Convener:
Yalan Song, Pennsylvania State University Main Campus

Convener:
Frederick Cheng, University of Virginia
Mohammed Ombadi, University of Michigan Ann Arbor
Allison Goodwell, Prairie Research Institute at University of Illinois at Urbana-Champaign
Jasper Vrugt, UC-Irvine
Peishi Jiang, University of Alabama
Leila Hernandez Rodriguez, Lawrence Berkeley National Laboratory
Zach Perzan, Middlebury College
Rebecca Herman, Columbia University of New York

Early Career Convener:
Tadd Bindas, ERT

Chair:
Jasper Vrugt, UC-Irvine
Peishi Jiang, University of Alabama
Zach Perzan, Middlebury College
Allison Goodwell, Prairie Research Institute at University of Illinois at Urbana-Champaign

This session explores the integration of big data and machine learning with physics in geosciences, addressing both the challenges and opportunities of applying AI/ML in the field. While the proliferation of 'Big Data' offers unprecedented opportunities, the hydrology community faces the challenge of developing and refining physical theories that complement and keep pace with the predictive capabilities of AI/ML (Nearing et al., 2021). We focus on: (1) development and harmonization of large-scale datasets, (2) reconciling observations with theory, (3) integrating/discovering theory through AI/ML, (4) diagnosing or detecting model misspecification/errors, (5) causal methods developments, applications, or counterfactual approaches that study environmental systems and how they respond to climate change or perturbations, and (6) physically-based or machine learning model studies with a focus on causality, explainability, functional performance, or process representations. We highlight the submissions from early-career researchers at all stages to foster collaboration, innovation, and in-depth discussions within the community.

Index Terms
0555 Neural networks, fuzzy logic, machine learning
1847 Modeling
1873 Uncertainty assessment
4475 Scaling: spatial and temporal

Cross-Listed:
NG - Nonlinear Geophysics
B - Biogeosciences

GeoBurst Sessions:
Yes

Neighborhoods:
3. Earth Covering

Scientific Discipline
Neighborhood
Type
Where to Watch
Presentations
Discussion