Towards Strongly Coupled Data Assimilation for Subseasonal-to-Seasonal (S2S) Prediction

Stephen Gregory Penny, NOAA Boulder, Boulder, MD, United States
A recent study by Penny et al. (2019) demonstrated the benefits of transitioning from weakly coupled data assimilation (WCDA), i.e. using a coupled forecast model but independent data assimilation for each separate component, to strongly coupled data assimilation (SCDA), i.e. analyzing the entire coupled system at once as one integrated system. This study used a simple coupled quasi-geostrophic model to demonstrate the properties of these CDA approaches, with a comprehensive assessment of many popular data assimilation methods. We will present the results from this study and then discuss the efforts being made to realize the benefits of SCDA using more realistic coupled models, such as NOAA’s Unified Forecast System (UFS).