Dataset for Global drivers of phytoplankton phenology trends
Authors/Creators
Description
This dataset accompanies the study Global drivers of phytoplankton phenology trends and provides the environmental and biological fields required to reproduce the full analysis workflow. The dataset is structured specifically for use with the analysis code provided in the repository. All datasets are provided on a 1° × 1° global grid with consistent temporal coverage for phenology trend analysis from 1998–2020.
All climatology files are named according to the corresponding variable; however, the data within each file are stored under the internal variable name DAILYCLIM.
Model data (PlankTOM12.2)
The dataset includes processed output from the PlankTOM12.2 global marine biogeochemical model. The following variables are provided as daily climatologies on a 1° × 1° global grid for 1998–2020:
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Chlorophyll-a concentration (TCHL)
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Sea surface Temperature (tos)
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Sea surface salinity (sos)
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Mixed Layer Depth (somxl030): depth where potential density exceeds surface density (rho(jk=1)) by + 0.03 kg m⁻³
Native chlorophyll-a units in PlankTOM12.2 are g L⁻¹. These are converted to mg m⁻³ within the analysis workflow, consistent with OC-CCI. All model variables are provided in a consistent NetCDF structure with standard naming conventions required by the phenology analysis scripts.
Model Version Publication: Guest, J. K. (2023). Plankton seasonal dynamics and carbon export in a warming ocean (Doctoral thesis, University of East Anglia).
ARMOR3D reanalysis data
Physical driver fields used in the study are derived from the ARMOR3D global ocean reanalysis product. These include:
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Sea surface temperature (to)
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Sea Surface Salinity (so)
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Mixed layer depth (mlotst)
ARMOR3D provides 3D fields constructed by combining satellite altimetry, sea surface temperature, and in-situ hydrographic observations through statistical interpolation methods. Full preprocessing steps applied to ARMOR3D fields for this dataset are documented in the file: /observations/ARMOR3D/README_ARMOR3D_processing.txt
Users should cite both of the following foundational references when using ARMOR3D-derived products:
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Guinehut, S., Dhomps, A.-L., Larnicol, G., & Le Traon, P.-Y. (2012). High resolution 3D temperature and salinity fields derived from in situ and satellite observations. Ocean Science, 8(5), 845–857.
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Mulet, S., Rio, M.-H., Mignot, A., Guinehut, S., & Morrow, R. (2012). A new estimate of the global 3D geostrophic ocean circulation based on satellite data and in-situ measurements. Deep Sea Research Part II, 77–80, 70–81.
OC-CCI chlorophyll processing workflow
A reproducible pipeline is provided for generating chlorophyll-a climatologies from ESA’s Ocean Colour Climate Change Initiative (OC-CCI) v5.0 dataset used in the analysis.
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Users must download OC-CCI v5 chlorophyll-a data and associated bias metrics.
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Full preprocessing instructions (bias correction, 1° × 1° aggregation, FILLXY gap-filling, and 21-day smoothing) are provided in: /observations/OC-CCIv5/README.txt
Files
data.zip
Files
(11.5 GB)
| Name | Size | Download all |
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md5:f25934b2e3869913a3c1a8e179ae0549
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11.5 GB | Preview Download |
Additional details
Related works
- Cites
- Software: 10.5281/zenodo.8388158 (DOI)
Funding
- Royal Society
- Royal Society Research Professorship (awarded to Corinne Le Quéré) RP\R1\19106
- Natural Environment Research Council
- UK NERC Marine Frontiers (awarded to Marie-Fanny Racault) NE/V011103/1
- Schmidt Sciences
- CALIPSO Project
Software
- Repository URL
- https://github.com/joe-kguest/global-phytoplankton-phenology
- Programming language
- Python
References
- Buitenhuis, E. T., Guest, J. K., Rebecca Wright, Philip Townsend, & Le Quéré, C. (2023). Description of the PlankTOM Equations (PlankTOM12.2). Zenodo. https://doi.org/10.5281/zenodo.8388158
- Guinehut, S., Dhomps, A.-L., Larnicol, G., & Le Traon, P.-Y. (2012). High resolution 3D temperature and salinity fields derived from in situ and satellite observations. Ocean Science, 8(5), 845–857.
- Guinehut, S., Dhomps, A.-L., Larnicol, G., & Le Traon, P.-Y. (2012). High resolution 3D temperature and salinity fields derived from in situ and satellite observations. Ocean Science, 8(5), 845–857.