Project goal: to identify sources of predictability for precipitation, temperature, and drought on sub seasonal to seasonal timescales, and to better understand and improve their representation in the…

Federal Cooperative Agreement Summary

George Mason University received a $1,048,807 cooperative agreement from the National Oceanic and Atmospheric Administration (NOAA) under the Weather and Air Quality Research program (CFDA 11.459), effective August 1, 2025 through July 31, 2028. The award supports research to identify sources of predictability for precipitation, temperature, and drought on subseasonal-to-seasonal (S2S) timescales and to improve their representation in the Seasonal Forecast System Version 1 (SFSv1). This research addresses the critical challenge of generating reliable S2S predictions, which present significant technical difficulties but would provide substantial societal value for drought and flood forecasting.

The primary deliverables include model output, analysis code, peer-reviewed manuscripts, and presentations that characterize SFSv1's climatological behavior and assess seasonal precipitation extremes. George Mason University will conduct two hierarchical suites of experiments: four 30-year ensembles to evaluate model climatology and El Niño-Southern Oscillation (ENSO) error impacts, and four sets of reforecasts focused on selected high-impact droughts and floods. The research outcomes will be communicated directly to the Seasonal Forecast System development team and will benefit the NOAA Environmental Modeling Center, Climate Prediction Center, and National Centers for Environmental Prediction. Additionally, the project includes developing training materials to expand participation in the Unified Forecast System community, particularly from underserved groups.

Project goal: to identify sources of predictability for precipitation, temperature, and drought on sub seasonal to seasonal timescales, and to better understand and improve their representation in the seasonal forecast system version 1. Problem/opportunity statement: S2S is a particularly challenging timescale on which to generate useful predictions, but reliable, accurate S2S forecasts would be of immense societal value. The development of the SFSV1 in a community framework allows the research community to directly contribute to a model that will significantly improve on the aging CFSV2. Methodology/activities to be performed: we will perform two hierarchical suites of experiments with SFSV1, in which the model evolution is increasingly constrained by observations: (1) four 30-year ensembles focused on characterizing the model climatology and the impact of enso errors, and (2) four sets of reforecasts of selected high-impact droughts and floods. Primary project product/outputs: products and outputs will consist of model output, analysis code, presentations, and peer-reviewed manuscripts. We will also generate training materials to help bring other scientists, particularly from underserved groups, into the UFS community. Expected results, outcomes, and benefits: we will provide a hypothesis-driven assessment of seasonal precipitation extremes, as well as better characterizing the climatological behavior of SFSV1. These outcomes and results will be communicated directly to the SFS development team through our ongoing collaboration. Intended beneficiaries and recipients: the proposed work will benefit the SFS development team and ultimately EMC, CPC and NCO. In addition, the UFS community will benefit from innovations, improved model performance, as well as improved portability of the seasonal forecast application for future research. Project_narrative