Subseasonal to Seasonal Research Improves Extended-Range Weather Prediction

Global and regional weather patterns give researchers clues to predict weather from 2 weeks to 2 months in the future.

Subseasonal to Seasonal Research (S2S) significantly aids decision support across industries and also provides the knowledge necessary for forecasters and emergency managers to keep the public informed and prepared for weather phenomena.

Improving Skill and Enhancing Value

S2S Supports Forecast Innovation

Subseasonal to Seasonal Research (S2S) is a priority area for NOAA and the US congress due to its ability to fill emerging forecast needs in various economic sectors. This is reflected in two primary goals identified by NOAA and in the Weather Research and Forecasting Innovation Act of 2017 (the Weather Act). The S2S program works to:

Improve the skill of S2S forecasts
Enhance the value of S2S products for stakeholders.

With new advances in forecasting, traditional weather models are pushed to predict further and further into the future. Global climate models are implemented at broader spatial and temporal resolution. This leaves a gap for prediction timescales of two weeks to two years, commonly referred to as the Subseasonal to Seasonal timescale.

The S2S program works to improve forecasts models by funding projects that:

Advance the scientific development of earth system models
Improve model representation of processes within and between model domains, including coupled data assimilation
Develop coupled prediction systems related to weather pattern modulations associated with air-ocean-land-ice interactions
Reduce systematic model error
Focus on error and bias reduction of weather models (such as the UFS) using postprocessing, reanalysis/ reforecasts and other statistical tools

The S2S program additionally funds and coordinates aspects of the ongoing North American Multi-Model Ensemble (NMME), an interagency/intergovernmental ensemble of coupled models from centers in the US and Canada, providing data for global, 12-month forecasts of 13 key variables. NMME data is used for multiple forecast needs.

What’s Happening Now

Updates & Events

Image ID: wea04701, NOAA's National Weather Service (NWS) Collection Photo Date: 2010 July 12 Photographer: CST Tami Beduhn Image Credit: Crew and Officers of NOAA Ship FAIRWEATHER

NCEP Introduces Operational Reanalysis for Climate Monitoring (CORe)

June 17, 2026

The National Centers for Environmental Prediction (NCEP) has launched the Conventional Observation Reanalysis (CORe), a new operational dataset designed to support monitoring of the Earth…

Person using a laptop to view a two-column scientific research paper featuring a data table and results section.

NOAA Launches SFS Beta Near-Real-Time Capability

June 17, 2026

NOAA has reached an important milestone in the development of the Seasonal Forecast System (SFS) Project with the March 2026 launch of the SFS Beta…

A wooden desk holds an open laptop, a white coffee mug, a notepad with a pen, and a smartphone near a window.

2026 S2S Land–Atmosphere Interactions Workshop

June 17, 2026

Registration is now open and abstracts are being accepted for the 2026 Subseasonal to Seasonal (S2S) Land–Atmosphere Interactions Workshop, co-hosted by NOAA and NSF NCAR.…

Image Credit: NOAA Looking over the deep green moss-covered slopes of Unalaska Island, over Captains Bay, to the cloud enshrouded Makushin Volcano. Image ID: amer0268, NOAA's Small World Collection Location: Alaska, Amaknak Island, Dutch Harbor Photographer: Mr. Tom Ward NOAA Teacher at Sea Program

Advancing Understanding of Land–Atmosphere Interactions and Processes for S2S Predictability

June 17, 2026

Please save the date for the upcoming workshop, Advancing Understanding of Land–Atmosphere Interactions and Processes for S2S Predictability, to be held August 4–6, 2026 at…

Precipitation

We support improvements to precipitation prediction within the UFS’s Seasonal Forecast System (SFS). Projects are solicited through the regular program calls, and may improve data assimilation, process modeling within the SFS, diagnostics, and post-processing techniques. The goal is to demonstrate improvements in precipitation prediction.

Western States Hydrology

We focus on hydroclimatological changes in major western US river basins, via assessments of snow cover, temperature, and precipitation changes that impact river flow. We seek to improve model representation of physical interactions (MJO, QBO, ENSO) that modulate baroclinic waves and drive atmospheric rivers, major storm events, and influence floods and drought.

Support for ICAMS

We provide scientific staffing support for several Implementation Teams (ITs) within the Committee on Research and Innovation and participate in the Subcommittee on Earth System Modeling and Prediction for the Interagency Council for Advancing Meteorological Services (ICAMS). Assisting these ITs supports the interagency structure, as well as connecting the S2S program with interagency efforts.

Model Development and Data Assimilation

We focus on innovative data assimilation (DA), especially coupled DA, which is integral to improving models and integrating new observation technologies. We also support development, improvement, and evaluation of model components and coupled modeling; and work to improve ensembles within S2S timescales.

High-resolution Ocean Modeling

We partnered with ONR in the NOPP 2022 Broad Area Announcement, selecting a project on improving high-resolution tide modeling within MOM6. The project will improve boundary conditions provided to coastal models, as well as improve Arctic ice flexure modeling.

Artificial Intelligence and Machine Learning

We explore and integrate cutting-edge Artificial Intelligence (AI) and Machine Learning (ML) techniques to enhance S2S prediction capabilities. Our efforts focus on developing AI/ML-driven approaches for improved data assimilation, bias correction, and the identification of complex patterns within models and the Earth system. We also support projects that leverage AI/ML for advanced diagnostics and post-processing of forecast outputs, aiming to refine predictions and provide more actionable insights for various environmental phenomena.

PROJECT VIGNETTES

Research and Modeling
to Improve S2S Timescale Predictions

PROJECT VIGNETTES

Research and Modeling
to Improve S2S Timescale Predictions

A ship’s bow plows through turbulent blue water as large white waves crash over the deck under a dark, stormy sky.

New Marine Hazards product gives mariners a longer outlook

March 28, 2025

The Ocean Prediction Center (OPC) rolled out its experimental Week 2 Marine Hazards Outlook in mid-March, providing guidance about the chance of certain wave heights and wind speeds at longer lead times. Because of the demand for information about wind and wave hazards beyond the upcoming week, OPC meteorologists researched…

Image Credit- Authors: Greg Greg Jennrich, David Straus, Muthuvel Chelliah, and Cory Baggett

Ensemble Prediction and Predictability of Extreme Weather via Circulation Regimes

August 12, 2022

A presentation given at NOAA’s 46th Annual Climate Diagnostics and Prediction Workshop used cluster analysis methods to investigate and forecast circulation regimes impact on weeks 3/4 predictions. This study demonstrates that the dominant circulation regimes over North America are combinations of teleconnections where the clusters are related to temperature and…

Photo Credit: NOAA This lone thunderhead quickly blew up just at sunset after a day of monsoonal showers near Williamson Valley, Az. Thunderhead over Table Mountain. Image ID: con00020, NOAA's National Weather Service (NWS) Collection Location: Arizona, Williamson valley Photographer: Jeff Stillman Credit: NOAA Weather in Focus Photo Contest 2015

Advances in the Prediction of MJO Teleconnections in the S2S Forecast Systems

August 12, 2022

A recent study uses novel diagnostics to evaluate the ability of 11 state-of-the-art Subseasonal to Seasonal (S2S) forecast systems to represent the teleconnections of the Madden-Julian Oscillation (MJO) and the impact on mid-latitude weather systems and prediction. Several S2S program funded projects contributed to this work. While highlighting where model…

Read about all FY24 Funded Projects >

Taking on Operational Challenges

Currently Funded Projects

Read about all FY24 Funded Projects >

Resource Library

Integrate Subseasonal to Seasonal Research into Your Projects

Reports From the NOAA Institutional Repository

From the NOAA Institutional Repository

S2S Community Workshop: Toward Minimizing Early Model Biases and Errors in S2S Predictions Workshop Summary

Report Author(s): Bassett, Christine and Olsen, Mark.

Published Date: 2025

DOI: https://doi.org/10.25923/m6ja-bb22

NMME: Meeting Future Needs Workshop Report June 21-22, 2023

Report Author(s): Bassett, Christine; Carman, Jessie; Kang, DK; and Olsen, Mark.

Published Date: 2023

DOI: https://doi.org/10.25923/f86r-b662

Report to Congress. Subseasonal and seasonal forecasting innovation: plans for the twenty-first century

Corporate Author(s):National Weather Service (U.S.)

Published Date: 2020

DOI : https://doi.org/10.25923/mesd-8b58

SubX Current and Potential Users Forum Report

Personal Author(s): Bassett, Christine; Carman, Jessie; Olsen, Mark; Smith, Jonathan.

Corporate Author(s): Weather Program Office (U.S.)

Conference Author(s): SubX Current and Potential Users Forum, August 24 – 26, 2021

Published Date: 2022

DOI: https://doi.org/10.25923/a7kd-c322

Community-Supported Research Initiatives For Improvement of Subseasonal to Seasonal (S2S) Prediction

Personal Author(s): Brooks, Maureen; Carman, Jessie; Olsen, Mark; Brown, Bonnie;Sandgathe, Scott; McCarren, David; James, C. Sim;

Corporate Authors(s): The National Earth System Prediction Capability (National ESPC)

Published Date: 2021

DOI: https://doi.org/10.25923/a4ca-p882

NOAA’s Subseasonal Experiment

Corporate Authors(s): United States. National Oceanic and Atmospheric Administration. Office of Oceanic and Atmospheric Research

Published Date: 2019

DOI: https://doi.org/10.25923/azn6-ff23

Building an Interannual to Decadal Prediction and Projection Capability for Decision Support

Corporate Authors(s): United States. National Weather Service; National Centers for Environmental Prediction (U.S.);

Conference Author(s): National Earth System Prediction Capability (sponsor)

Published Date: 2019

DOI: https://doi.org/10.25923/n9p9-q979

Metrics, Post-Processing, and Products for Subseasonal to Seasonal Workshop: Fostering discussion of user needs; agency capabilities and products; gaps; and potential operational and technological solutions

Corporate Authors(s): United States. National Weather Service.; United States. National Oceanic and Atmospheric Administration. Office of Oceanic and Atmospheric Research;

Conference Author(s): Metrics, Post-processing, and Products for Subseasonal to Seasonal Workshop

Published Date: 2018

URL: https://repository.library.noaa.gov/view/noaa/20613

Position paper on high performance computing needs in Earth system prediction

Personal Author(s): Carman, Jessie C.; Clune, Thomas; Giraldo, Francis; Govett, Mark; Kamrath, Anke; Lee, Tsengdar; McCarren, David; Michalakes, John; Sandgathe, Scott; Whitcomb, Tim;

Corporate Authors(s): National Earth System Prediction Capability (U.S.)

Published Date: 2017

DOI: http://doi.org/10.7289/V5862DH3

Journal Articles

Exploring the Need for Reliable Decadal Prediction

Sandgathe, S., Brown, B. R., Carman, J. C., Infanti, J. M., Johnson, B., McCarren, D., & McIlvain, E. (2020). Exploring the Need for Reliable Decadal Prediction, Bulletin of the American Meteorological Society, 101(2), E141-E145. Retrieved Aug 24, 2022, from https://journals.ametsoc.org/view/journals/bams/101/2/bams-d-19-0248.1.xml

Bridging the Gap between Climate and Weather

Sandgathe, S., Carman, J., Johnson, B., & McIlvain, E. (2018). Bridging the Gap between Climate and Weather, Bulletin of the American Meteorological Society, 99(11), ES191-ES193. Retrieved Aug 24, 2022, from https://journals.ametsoc.org/view/journals/bams/99/11/bams-d-18-0154.1.xml

Six Priorities for Investment in Snow Research and Product Development

Hurwitz, M. M., Baxter, S., Brown, B., Carman, J., Dale, J., Draper, C., Horsfall, F., Hughes, M., Gerth, J., Kapnick, S., Olheiser, C., Olsen, M., Stachelski, C., Vincent, M., Webb, R., & Zdrojewski, J. (2020). Six Priorities for Investment in Snow Research and Product Development, Bulletin of the American Meteorological Society (published online ahead of print 2020). Retrieved Aug 24, 2022, from https://journals.ametsoc.org/view/journals/bams/aop/bamsD200218/bamsD200218.xml

The National Earth System Prediction Capability: Coordinating the Giant

Carman, J. C., Eleuterio, D. P., Gallaudet, T. C., Geernaert, G. L., Harr, P. A., Kaye, J. A., McCarren, D. H., McLean, C. N., Sandgathe, S. A., Toepfer, F., & Uccellini, L. W. (2017). The National Earth System Prediction Capability: Coordinating the Giant, Bulletin of the American Meteorological Society, 98(2), 239-252. Retrieved Aug 24, 2022, from https://journals.ametsoc.org/view/journals/bams/98/2/bams-d-16-0002.1.xml