Monthly mean dataset of global phytoplankton taxonomic group concentrations (2002.7-2022.3)

Published: 14 February 2023| Version 1 | DOI: 10.17632/c9d852g8j9.1
Zhenghao Li,
Hailong Zhang,


This dataset is a satellite product of global monthly mean phytoplankton taxonomic group (PTG) chlorophyll-a concentrations, including chlorophytes (Chlor), diatoms (Diat), haptophytes (Hapt), cryptophytes (Crypt), and cyanobacteria (Cyan). The time coverage of the dataset is from July 2002 to March 2022. The data file includes PTG's chlorophyll-a concentration (unit: mg m-3), longitude, and latitude information, with a spatial resolution of 36 km. The values of non-water and invalid pixels are set to NaN. The data format is NetCDF (network common data form, nc). Naming rules: "data source identification_month and year_PTGs_data_production". Examples are as follows: where "MO" refers to MODIS-Aqua data. "200207" represents July 2002. The data production time is expressed as "month, month, day day, year". "nc" is the suffix of the NetCDF data file. Each nc file contains six PTGs Chla concentrations (unit: mg m-3).


Steps to reproduce

This dataset of six PTGs' chlorophyll-a concentrations was produced based on MODIS-Aqua global monthly remote sensing reflectance data (Rrs) (2002.7-2012.12). The production process is as follows: Step 1: MODIS-Aqua Rrs L3 monthly data (spatial resolution: 9 km) were obtained from NASA Goddard Space Flight Center ( In order to reduce the computational effort, its spatial resolution was resampled to 36 km. Step 2: Global phytoplankton absorption coefficients (412, 443, 469, 488, 531, 547, 555, 645, 667, 678 nm) were calculated from MODIS-Aqua Rrs data according to the quasi-analytical algorithm (QAA) developed by Lee et al. (2002). Step 3: Decompose the phytoplankton absorption coefficients using a Gaussian decomposition method and further establish the relationship between the measured PTG concentrations and the decomposition parameters to estimate PTG concentrations. Step 4: Combine steps 1-3, producing remote sensing products of six PTG concentrations in the global ocean. Refence Z. Lee, K. L. Carder, R. A. Arnone, Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters. Applied Optics 41, 5755-5772 (2002).


Nanjing University of Information Science and Technology


Oceanography, Remote Sensing, Phytoplankton


National Natural Science Foundation of China

42176179, 41876203, 42176181, 42106176

National Key Research and Development Program of China


Natural Science Foundation of Jiangsu Province

BK20211289, BK20210667

Open Fund of State Key Laboratory of Remote Sensing Science


Postgraduate Research & Practice Innovation Program of Jiangsu Province