Evaluation of Vertical Patterns in Chlorophyll-A Derived From a Data Assimilating Model of Satellite-Based Ocean Color ...
Satellite-based sensors of ocean color have become the primary tool to infer changes in surface chlorophyll, while BGC-Argo floats are now filling the information gap at depth. Here we use BGC-Argo data to assess depth-resolved information on chlorophyll-a derived from an ocean biogeochemical model...
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| Format: | Text |
| Language: | English |
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AGU
2024
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.13016/m2h4ge-grac https://mdsoar.org/handle/11603/35187 |
| Summary: | Satellite-based sensors of ocean color have become the primary tool to infer changes in surface chlorophyll, while BGC-Argo floats are now filling the information gap at depth. Here we use BGC-Argo data to assess depth-resolved information on chlorophyll-a derived from an ocean biogeochemical model constrained by the assimilation of surface ocean color remote sensing. The data-assimilating model replicates well the general seasonality and meridional gradients in surface and depth-resolved chlorophyll-a inferred from the float array in the Southern Ocean. On average, the model tends to overestimate float-based chlorophyll, particularly at times and locations of high productivity such as the beginning of the spring bloom, subtropical deep chlorophyll maxima, and non-iron limited regions of the Southern Ocean. The highest model RMSE in the upper 50 m with respect to the float array is of 0.6 mg Chl m?3, which should allow the detection of seasonal changes in float-based biomass (varying between 0.01 and >1 ... |
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