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Abstract 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 mg Chl m−3) but might hinder the identification of subtle changes in chlorophyll at narrow local scales. Both model and float profiling data show good agreement with in situ data from station ALOHA, with model estimates showing a slight accuracy edge in inferring depth‐resolved observations. Uncertainties in float bio‐optical estimates impede their use as a reliable benchmark for validation, but the general qualitative agreement between model and float data provides confidence in the ability of model to replicate biogeochemical features below the surface, where data is not directly constrained by the assimilation of satellite ocean color.
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Depth‐Resolved Net Primary Production in the Northeast Pacific Ocean: A Comparison of Satellite and Profiling Float Estimates in the Context of Two Marine Heatwaves
Abstract Methods commonly used to estimate net primary production (NPP) from satellite observations are now being applied to biogeochemical (BGC) profiling float observations. Insights can be gained from regional differences in float and satellite NPP estimates that reveal gaps in our understanding and guide future NPP model development. We use 7 years of BGC profiling float data from the Northeast Pacific Ocean to quantify discrepancies between float and satellite NPP estimates and decompose them into contributions associated with the platform sensing method and depth resolution of observations. We find small, systematic seasonal discrepancies in the depth‐integrated NPP (iNPP) but much larger (>±100%) discrepancies in depth‐resolved NPP. Annual iNPP estimates from the two platforms are significantly, positively correlated, suggesting that they similarly track interannual variability in the study region. Using the long‐term satellite iNPP record, we identify elevated annual iNPP during two recent marine heatwaves and gain insights about ecosystem functionality.
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- Award ID(s):
- 2032754
- PAR ID:
- 10370325
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 48
- Issue:
- 19
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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