Abstract
Abstract. Net primary production of the oceans contributes approximately half of the total global net primary production, and long-term observational records are required to assess any climate-driven changes. The Ocean Colour Climate Change Initiative (OC-CCI) has proven to be robust whilst also being one of the longest records of ocean colour. However, to date, only one primary production algorithm has been applied to this data product, with other algorithms typically applied to single-sensor missions. The data product presented here addresses this issue by applying five algorithms to the OC-CCI data product, which allows the user to interrogate the range of distributions across multiple models and to identify consensus or outliers for their specific region of interest. Outputs are compared to single-sensor data missions, highlighting good overall global agreement, with some small regional discrepancies. Inter-model assessments address the source of these discrepancies, highlighting the choice of the mixed-layer data product as a vital component for accurate primary production estimates. The datasets are published in the Zenodo repository at https://doi.org/10.5281/zenodo.7849935, https://doi.org/10.5281/zenodo.7858590, https://doi.org/10.5281/zenodo.7860491 and https://doi.org/10.5281/zenodo.7861158 (Ryan-Keogh et al., 2023a, b, c, d).
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