Review comments on essd-2024-21

Abstract

<strong class="journal-contentHeaderColor">Abstract.</strong> Phytoplankton bloom phenology is an important indicator for the monitoring and management of marine resources and the assessment of climate change impacts on ocean ecosystems. Despite its relevance, there is no long-term and sustained observational phytoplankton phenological product available for global ocean implementation. The data product presented here addresses this need through the development of phenological detection algorithms (including among other seasonal metrics, the bloom initiation, termination, duration, and amplitude timing) using satellite derived chlorophyll-a data from the Ocean Colour Climate Change Initiative. This product provides the phenology output from three widely used bloom detection algorithms at three different spatial resolutions (4, 9 and 25 km) allowing for both regional and global-scale applications. In this study, the mean global phenology is characterised according to the three phenological detection methods and the different resolutions, which are compared to one another. In general, there is good agreement between the detection methods and between different resolutions on global scales. Regional differences are evident in coastal domains (particularly for resolution) and in regions with strong transitions between phytoplankton seasonal characteristics. This product can be used towards the development of national and global biodiversity assessments, pelagic ecosystem mapping and for monitoring change in climate sensitive regions relevant for ecosystem services. The dataset is published in the Zenodo repository under the following DOIs, 4 km: <a href="https://doi.org/10.5281/zenodo.8402932" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.8402932</a>. 9 km: <a href="https://doi.org/10.5281/zenodo.8402847" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.8402847</a> and 25 km: <a href="https://doi.org/10.5281/zenodo.8402823" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.8402823</a> (Nicholson et al., 2023a, b, c) and will be updated regularly.