Abstract
Satellite salinity data from the Soil Moisture and Ocean Salinity (SMOS) mission was recently enhanced, increasing the spatial extent near the coast that eluded earlier versions. In a pilot attempt we assimilate this data into a coastal ocean model (ROMS) using variational assimilation and, for the first time, investigate the impact on the simulation of a major river plume (the Congo River). Four experiments were undertaken consisting of a control (without data assimilation) and the assimilation of either sea surface height (SSH), SMOS and the combination of both, SMOS SSH. Several metrics specific to the plume were utilised, including the area of the plume, distance to the centre of mass, orientation and average salinity. The assimilation of SMOS and combined SMOS SSH consistently produced the best results in the plume analysis. Argo float salinity profiles provided independent verification of the forecast. The SMOS or SMOS SSH forecast produced the closest agreement for Argo profiles over the whole domain (outside and inside the plume) for three of four months analysed, improving over the control and a persistence baseline. The number of samples of Argo floats determined to be inside the plume were limited. Nevertheless, for the limited plume-detected floats the largest improvements were found for the SMOS or SMOS SSH forecast for two of the four months.
Highlights
The ten largest rivers transport a combined 40% of the freshwater and particulate material into the oceans [1,2,3,4]
The latest version of Soil Moisture and Ocean Salinity (SMOS), a satellite salinity product, was recently (2017) processed with an updated technique to reduce errors near the coast. This allows more frequent coastal data, which could be employed in a Data assimilation (DA) system of the Congo River plume
IS4D-Var assimilated sea surface height (SSH), SMOS or SMOS SSH combined for four months
Summary
The ten largest rivers transport a combined 40% of the freshwater and particulate material into the oceans [1,2,3,4]. The accuracy of modelling these river plumes is valuable for fishing communities Terrestrial material, both suspended and dissolved, are transported via river plumes, affecting sediment and pollutant distributions and the biogeochemistry of carbon [3]. The second-largest river (in terms of the annual mean daily discharge) is the Congo in West Africa, discharging an average 39,866 m3 /s of freshwater per month into the Angola Basin. Such extensive outflow produces a plume as large as 800 km from the river mouth [4,5], influencing a substantial section of the basin. Denamiel et al [10] performed the first numerical simulation of the Congo River plume where they found the plume had a northward
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