We’re excited to share that the Subseasonal-to-Seasonal (S2S) Predictions community will host dedicated sessions at the upcoming AGU and AMS conferences!
We welcome abstract submissions from researchers, practitioners, and experts across meteorology, climate science, hydrology, and related fields. These sessions are an opportunity to explore innovative research, spark collaboration, and advance the science and application of S2S prediction.
Submit your abstract and be part of the conversation driving the future of S2S prediction!
AGU 2025 Annual Meeting
- Date: December 15-19, 2025
- Location: New Orleans, LA
- Abstract Submission Deadline: July 30, 2025
- For more information and to submit your abstract, visit AGU 2025 Annual Meeting Website
Session 1:
A016 Advancing Skill in Subseasonal-to-Seasonal (S2S) Prediction
Session ID: 252208
Chairs: Christine Bassett (NOAA WPO); Mark Olsen (NOAA WPO); Margaret Orr (NOAA WPO); Yaga Richter (NCAR); Yan Xue (NOAA NWS)
Session Description: Reliable subseasonal-to-seasonal (S2S) forecasts are essential for managing economic risk and informing planning in sectors such as energy, agriculture, water resources, and transportation. Land-atmosphere interactions, along with processes like the Madden-Julian Oscillation (MJO), El Niño-Southern Oscillation (ENSO), and stratospheric variability, are central to predictability at this time scale. This session invites contributions that improve understanding and predictive skill by identifying, diagnosing, and addressing model errors across components of the Earth system. Submissions may also include process-oriented diagnostics, improved initialization and data assimilation strategies, bias corrections, statistical post-processing tools, and refinements to physical parameterizations. We particularly welcome studies that leverage observational constraints, develop process- and operation-oriented metrics, or contribute to model evaluation frameworks that support operational use. The session will also include highlights from the June 2025 Land-Atmosphere S2S Workshop, with a focus on strengthening coordination across modeling, observational, and application communities to advance forecast performance.
Session 2:
A012 Advancing AI and Machine Learning for Improved Subseasonal-to-Seasonal (S2S) Forecast Skill
Session ID: 252232
Chairs: Christine Bassett (NOAA WPO); Mark Olsen (NOAA WPO); Margaret Orr (NOAA WPO) Nachiketa Acharya (Spire Global, Inc.); Johnna Infanti (NOAA NWS); Marybeth Arcodia (Colorado State University)
Session Description: Timely and skillful subseasonal-to-seasonal (S2S) predictions are a critical tool for reducing economic risk and improving decision making across sectors such as energy, agriculture and food security, and transportation. Additionally, industries rely on dependable S2S guidance to make informed decisions on supply chains, logistics, and resource allocation. Artificial intelligence (AI) and machine learning (ML) are increasingly being explored to improve forecast skill by correcting systematic biases, enhancing model calibration, and sharpening representations of key drivers like the Madden-Julian Oscillation (MJO) and El Niño-Southern Oscillation (ENSO). This session invites contributions that apply AI/ML to bias correction, hybrid modeling, and process diagnostics—especially where methods demonstrate operational potential or measurable gains in skill. We also welcome work that integrates AI tools with traditional modeling frameworks to improve efficiency and decision support. We particularly encourage submissions that show how AI-driven innovations can strengthen model reliability, reduce costs, and support the delivery of actionable forecasts across public and private sectors.
AMS 2026 Annual Meeting
- Date: January 25-29, 2026
- Location: Houston, TX
- Abstract Submission Deadline: August 14, 2025
- For more details and abstract submission, visit AMS 2026 Annual Meeting Website
Session Title: Strengthening Subseasonal-to-Seasonal (S2S) Forecasts through Model Advancements and Ensemble Innovations
Conference: 14th Symposium on the Weather, Water, and Climate Enterprise OR 39th Conference on Hydrology
Chairs: Christine Bassett (NOAA WPO), Mark Olsen (NOAA WPO), Margaret Orr (NOAA WPO)
Session Description: Subseasonal-to-seasonal (S2S) forecasts provide essential support for decision-making across agriculture, water management, energy, and disaster risk reduction. However, persistent model errors and uncertainties remain a major barrier to skillful S2S prediction. This session will highlight advances in model development and ensemble strategies that address early bias growth and systematic errors across components of the Earth system. Contributions are invited on reducing forecast drift, refining physical parameterizations, strengthening initialization methods, and improving ensemble design. Submissions focusing on key drivers of predictability — such as the Madden-Julian Oscillation (MJO), El Niño–Southern Oscillation (ENSO), stratosphere-troposphere coupling, and earth system component interactions — are encouraged. Studies that apply observational constraints, advance process-based diagnostics, implement bias correction techniques, or translate improvements into operational systems are particularly welcomed. Special attention will be given to approaches that deliver measurable gains in forecast reliability, reduce uncertainty, and strengthen operational decision-making for sectors sensitive to weather and environmental conditions.
