Monthly mean dataset of global phytoplankton taxonomic group concentrations Part.2 (2013.1-2022.3)

Published: 10 November 2022| Version 2 | DOI: 10.17632/n39hktbt9r.2
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Description

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 Part.2 is from January 2013 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_PTG abbreviation_data production time.nc". Examples are as follows: MO_201301_chlor_data_20220520.nc where, 'MO' refers to MODIS-Aqua data. '201301' represents January 2013. 'Chlor_data' means chlorophytes' chlorophyll-a concentration (unit: mg m-3). The data production time is expressed as "month, month, day day, year". '.nc' is the suffix of the NetCDF data file.

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Steps to reproduce

This dataset of six PTGs' chlorophyll-a concentrations was produced based on MODIS-Aqua global monthly remote sensing reflectance data (Rrs) (2013.1-2022.3). 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 (https://oceancolor.gsfc.nasa.gov/). 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).

Institutions

Nanjing University of Information Science and Technology

Categories

Remote Sensing, Phytoplankton, Ocean

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