Global satellite observations of marine phytoplankton pigments over the past two decades
Abstract Documenting the variations of phytoplankton pigments is essential for understanding phytoplankton assemblages' dynamics and physiological characteristics in the global oceans. Advanced chlorophyll a satellite product has provided an overview of global phytoplankton biomass, yet deeper taxonomic biomass monitoring demands more detailed pigment information. In this study, we have collected 1562 in situ measured sea surface samples (depth < 10 m) from 1997 to 2017 covering the global ocean, where the in situ dataset consists of pigment concentration and phytoplankton absorption coefficient ( a ph ). A global semi‐analytical pigment model was developed using the Gaussian decomposition method and was evaluated by the leave‐one‐out cross validation method. Model accuracy verification based on in situ measurement (e.g., mean absolute percentage errors below ~ 67% for most pigments) and satellite synchronization dataset (e.g., most pigments have mean absolute percentage errors below ~ 70%) showed the reliable performance of the pigment model in the global oceans. We reconstructed the global hyperspectral phytoplankton absorption by the three‐component absorption model of the phytoplankton size class, enabling satellite application of the pigment model and obtaining the nearly 20‐yr spatiotemporal variations of 14 phytoplankton pigments. Global pigment concentrations exhibited a generally relatively unchanging pattern at the beginning of the 21 st century, as evidenced by stable geographic distribution and temporal trends, while local environmental disturbances created anomalies in 1‐yr period. Our findings provide an effective model to detect global pigment concentration and essential satellite products for further analysis of phytoplankton assemblages.
Authors
- Yu Huan (ORCID: https://orcid.org/0000-0003-2703-4430)
- Yuhang Chen (ORCID: https://orcid.org/0000-0001-6066-1626)
- Shengqiang Wang (ORCID: https://orcid.org/0000-0003-4725-1635)
- Deyong Sun (ORCID: https://orcid.org/0000-0001-9599-2732)
- Zhenghao Li (ORCID: https://orcid.org/0009-0003-6889-2519)
- Peng Chen (ORCID: https://orcid.org/0000-0002-0635-9220)
Institutions
- Nanjing University of Information Science and Technology (CN)
- Ministry of Natural Resources (CN)
- Zhejiang Ocean University (CN)
- Second Institute of Oceanography (CN)
- Ningbo Putian Information Industry (China) (CN)
- State Key Laboratory of Remote Sensing Science (CN)
Publication Details
- Journal
- Limnology and Oceanography
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1002/lno.70017
- Citations
- 1
- Primary Topic
- Marine and coastal ecosystems
- Type
- article
- Field-Weighted Citation Impact
- 1.79
Funders
- National Natural Science Foundation of China