Primary Convener:
Tong Qiu, Duke University

Convener:
Michael Dietze, Boston University
Nivedita Dubey, Washington State University
Tejasvi Chauhan, Max Planck Institute for Biogeochemistry

Early Career Convener:
Abigail Lewis, Virginia Tech

Chair:
Tong Qiu, Duke University
Michael Dietze, Boston University

Advances in data, models, and decision support enable rapid progress in making biogeoscience more predictive at all time-scales. Forecasting accelerates science and boosts societal relevance, especially when involving multidisciplinary collaborators, social scientists, and end users. This session highlights methodological and application-based research on forecasting biogeochemistry, biogeophysics, hydrology, agriculture, and ecology across terrestrial and aquatic systems. In particular, we emphasize the emerging opportunities of sub-seasonal to seasonal (S2S) forecasting to support decision-making in agriculture, water resource management, and ecosystem planning. We welcome contributions on: (1) innovations in forecasting tools, climate services, and ecological applications; (2) advances in artificial intelligence, machine learning, and data assimilation for forecasting, with an emphasis on explainability and uncertainty quantification; (3) case studies that evaluate the economic and societal value of forecasts in specific decision-making contexts; and (4) fundamental advances in theories, models, and data streams that improve the predictability of ecological and Earth system processes.

Index Terms
0414 Biogeochemical cycles, processes, and modeling
0430 Computational methods and data processing
0480 Remote sensing
0485 Science policy

Suggested Itineraries:
Climate Change and Global Policy
Machine Learning and AI
Open Science and Open Data

Cross-Listed:
SY - Science and Society
H - Hydrology
GC - Global Environmental Change

Neighborhoods:
3. Earth Covering