Tropical Pacific Chlorophyll Algorithm (TPCA): Reprocessing
收藏NIAID Data Ecosystem2026-03-12 收录
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https://zenodo.org/records/4922168
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资源简介:
The Tropical Pacific Chlorophyll Algorithm (TPCA) regional reprocessing includes Level 3 Mapped Daily 9km Chlorophyll data for the tropical Pacific (10°N to 10°S and 150°E to 90°W). These products are provided for the satellite sensors SeaWiFS (1997 - 2010), MODIS-Aqua (2002 - Present) and MERIS (2002-2012). SeaWiFS and MODIS-Aqua had the TPCA algorithm applied to them, however MERIS performs well as is for the tropical Pacific, and thus a snapshot of the NASA chlor_a product has been provided here.
The tropical Pacific Ocean is a globally significant region of climate-driven biogeochemical variability. Satellite ocean color algorithms have been used for over 20 years and provide a substantial historical record of global ocean chlorophyll-a variability. Current chlorophyll algorithms perform better in the tropical Pacific than for the globe. Nevertheless, improvements can be made to create a robust historical record of chlorophyll variability, which is essential to accurately identify ocean-atmosphere carbon fluxes and long-term trends in ocean productivity. We use a large in situ chlorophyll database to tune empirical ocean color algorithms to remove bias in the equatorial Pacific. Traditional band ratio chlorophyll algorithms (OCx) perform well, but exhibit errors at low chlorophyll concentrations. A new algorithm, the ocean Color Index (OCI; Hu et al., 2012), is effective at calculating low chlorophyll concentrations in the mesotrophic tropical Pacific Ocean. OCI effectiveness is limited to less than 0.2mg m-3, with OCx outperforming it above this limit. Here, we present optimized ocean color algorithms with modified polynomials and updated OCx to OCI blending windows in chlorophyll space. Existing ocean color algorithms underestimate tropical Pacific chlorophyll by 5.8%, 14% and 2% for SeaWiFS, MODIS-Aqua and MERIS. We develop regionally tuned sensor specific coefficients and blending windows to reduce systematic bias. We assess cross-sensor consistency to produce robust 21-year time series trends. These updated estimates increase chlorophyll concentrations in open water and decrease around island and warm-pool regions, with implications for our understanding of El Niño-Southern Oscillation driven carbon fluxes and net primary productivity.
The TPCA algorithm outlined in Pittman et al., 2019 (2019JC015498) has been applied to the relevant wavelengths for SeaWiFS and MODIS-Aqua. The Level 3 Mapped Daily ; 9km Rrs files for each sensor were obtained from https://oceandata.sci.gsfc.nasa.gov/. The MERIS Snapshot was provided directly from the NASA chlor_a product.
These files were then processed with the TPCA algorithm and are provided as yearly combined netcdf4 files.
5 wavelengths for SeaWiFS and 4 wavelengths for MODIS-Aqua were used in the creation of the TPCA reprocessing.
More details on the input data are provided in the readme file.
This dataset was produced by Nicholas Pittman for the ARC Centre of Excellence for Climate Extremes, as part of the Climate variability and teleconnections research program.
创建时间:
2021-06-18



