Meetings: Documents

Seasonal and Interannual Variability of Freshwater Transport at River-Dominated Ocean Margin Systems from 1992-2018: Results from the Global ECCO2 with Real-time Discharge
[18-Feb-20] Feng, Y., Menemenlis, D., Xue, H., Liu, Z., and Xiu, P.
Presented at the 2020 Ocean Sciences Meeting
River plume dynamics generated considerable research interests for the past decade due to the important role in coastal ecology, biogeochemistry, shoreline morphology and climate. Previous investigators have utilized satellite ocean color or configured regional models in studying the dispersal of river plumes, with focusing on a certain continental shelf. In this study, we improved a globally configured 18-km resolution, eddy permitting model (ECCO2) from non-point river discharge input to point input. We used the model to investigate seasonal variability of river plumes at three continental shelves, namely the Northern Brazilian (NB) Shelf, the Northern Angola (NA) Basin, and the Texas-Louisiana (TL) Shelf. A comparison with World Ocean Database (WOD) showed that SMAP SSS Anomaly (SSSA) field showed small RMSE. Common river plume dispersal patterns were all well identified from the three products, including (1) the eastward transport of the Amazon River plume in July - November; (2) the southward dispersal of the Congo River plume in February-March; and (3) the July - September reversal of the Mississippi River plume. We also found that the plume area responded to freshwater discharge differently for these three regions. The response time is about 2 month for the NB shelf, 4 month for the NA Basin and 3 month for the TL shelf. About 50-70% variability can be explained by freshwater discharge at the NB shelf and the NA Basin. In contrast, only about 20% can be explained at the TL shelf. The response time reflected the lag between the maximum river discharge and external forcing, primarily wind and ambient currents. The lower explained variance at the TL shelf is because the shelf located at higher latitude, resulting in the more bottom-advected river plume rather than the surface-advected. Our study highlights mechanisms controlling river plume variability from the global model and data assimilation products.