Correlation Analysis for Strongly Coupled Ocean-Atmosphere Data Assimilation for Future Versions of the Global Forecast System

Coupled models use various components (atmosphere, ocean, sea-ice, waves) together to produce a seamless prediction of the Earth system as a whole. The upcoming version of the National Oceanic and Atmospheric Administration’s (NOAA) Global Forecast System (GFS) is planned to be coupled with initializations performed individually for each model component. This is known as weak coupling; whereas with strong coupling, the model components data assimilation (DA) are initialized together. The Joint Effort for Data assimilation Integration (JEDI) framework aims to unify data assimilation (DA) programs across modeling systems. It allows for the use of weak or strong coupling with various models. Using the JEDI framework, this project aimed to determine the importance of atmosphere-ocean coupling strength for implementation in future versions of the GFS. This involved an analysis of the DA coupling between the Finite­-Volume Cubed-Sphere dynamical core atmospheric model (FV3) and the Modular Ocean Model 6 (MOM6). To evaluate this coupling, high resolution sea surface temperature (SST) from the MOM6 and 2 meter air temperature (T2m) from the FV3 were compared via difference and correlation analysis with daily data from eleven days in the summer and winter. Correlations are seen to change temporally and spatially. T2m–SST correlations over time showed the strongest relationships in the summer hemisphere and in certain specific locations, such as the El Nino Southern Oscillation (ENSO) region. Correlations were weakest towards the poles with increasing sea ice. Difference plots (SST-T2m) also demonstrated spatial differences between the two components and showed significant flow dependence.