Reprocessing Data
Reprocessing Data
• Special data sets of the seas around China
• GOCI data sets
• Western Pacific-Indian Ocean data sets
• Global data sets
• NASA public data sets
• Public data sets by other institutions
The SatCO2 V1.03 platform (released in May 2021) contains satellite and model data products related to marine ecosystems and carbon cycles in seas around China, western Pacific-Indian Ocean regions, and global oceans over the past 20 years. Data processing characteristics have been divided into six categories.
Note:Please click "Parameter" if you want to detailed datasets information.
1. Special datasets of seas around China
These datasets include level-1 products from the GF-4 and HY-1B satellites provided by the National Satellite Ocean Application Service of China, remote sensing reflectance products provided by NASA, and atmospheric products provided by NOAA. Based on the level-1 products mentioned above, SOED has produced normalized water-leaving radiance and primary water quality products, including seawater transparency, surface water salinity, suspended matter concentration, and partial pressure of seawater CO2 (pCO2), using self-developed atmospheric correction and water constituent inversion algorithms.
2. Geostationary Ocean-Color Imager (GOCI) datasets
These datasets include GOCI L1B, i.e., geostationary ocean color satellite remote sensing data provided by the Korea Ocean Satellite Center. Based on this, SOED has produced normalized water-leaving radiance and surface suspended matter concentration products in two coastal regions, i.e., the Bohai Sea and Yangtze River Estuary, with high spatial and temporal resolution using self-developed atmospheric correction and inversion algorithms.
3. Western Pacific-Indian Ocean datasets
These datasets are based on the remote sensing reflectance data and products provided by NASA. SOED has produced surface suspended matter concentration, chlorophyll concentration, and seawater transparency products for the eastern Indian Ocean, western Pacific Ocean, and the South China Sea using self-developed inversion algorithms.
4. Global datasets
These datasets include remote sensing reflectance, total absorption coefficients, and particulate backscattering coefficients retrieved by SeaWiFS, MODIS/Aqua, and VIIRS from NASA. SOED has produced global sea surface CDOM absorption coefficients, backscattering coefficients, and seawater transparency products using self-developed inversion algorithms.
5. NASA public datasets
These datasets are provided by NASA and include remote sensing reflectance, surface chlorophyll concentration, photosynthetic available radiation, concentrations of organic and inorganic particulate carbon from the SeaWiFS, MODIS/Aqua, and VIIRS sensors, and sea surface salinity from the Aquarius sensor.
6. Public datasets by other institutions
These datasets are from institutions such as RRS, CMEMS, OSU, ESA, NOAA, and ECMWF and include ocean environmental parameters, such as sea surface temperature, salinity, sea level, mixing layer depth, wind, and rainfall capacity; ecological parameters, such as net primary productivity and multiple-satellite-merged chlorophyll concentration; and atmospheric parameters, such as mole fraction of atmospheric CO2, relative humidity, and sea surface atmospheric pressure.
References for SOED self-developed algorithms:
Please visit www.SatCO2.com for more information.
• GOCI data sets
• Western Pacific-Indian Ocean data sets
• Global data sets
• NASA public data sets
• Public data sets by other institutions
The SatCO2 V1.03 platform (released in May 2021) contains satellite and model data products related to marine ecosystems and carbon cycles in seas around China, western Pacific-Indian Ocean regions, and global oceans over the past 20 years. Data processing characteristics have been divided into six categories.
Note:Please click "Parameter" if you want to detailed datasets information.
At present, the remote sensing data set of marine ecological environment has been open for download. The data can be downloaded through the National Earth System Science Data Center. The download link is as follows:
http://www.geodata.cn/data/index.html?publisherGuid=126744287495931&categoryId=67
http://www.geodata.cn/data/index.html?publisherGuid=126744287495931&categoryId=67
1. Special datasets of seas around China
These datasets include level-1 products from the GF-4 and HY-1B satellites provided by the National Satellite Ocean Application Service of China, remote sensing reflectance products provided by NASA, and atmospheric products provided by NOAA. Based on the level-1 products mentioned above, SOED has produced normalized water-leaving radiance and primary water quality products, including seawater transparency, surface water salinity, suspended matter concentration, and partial pressure of seawater CO2 (pCO2), using self-developed atmospheric correction and water constituent inversion algorithms.
Names Of data sets | Parameters | Spatial range/resolution | Temporal range/resolution |
GF-4 data sets SIO_GF4_CCD_NODEF |
normalized water-leaving radiance (491, 561, 653, 809 nm), suspended particle matter concentration | Single orbit; 50m | November 2017 - present; single orbit |
HY-1B data sets SIO_HY1B_COCTS_NODEF |
normalized water-leaving radiance ( 412nm,443nm, 490nm, 520nm, 565nm,670nm), surface chlorophyll concentration, surface suspended matter concentration, 865-nm aerosol optical thickness, sea water transparency, sea surface temperature, attenuation coefficient, atmosphere visibility, CDOM absorption coefficient (including the detritus absorption) | Single orbit; 1.6 km | April 2007 - January 2016; single orbit |
China sea CO2 data sets SIO_AQUA_MODIS_EAMS SIO_MERGE_MERGE_EAMS |
surface water salinity, aquatic pCO2 | (100°-130°E, 0°-41°N); 1.6 km |
2003-2018; monthly average |
2. Geostationary Ocean-Color Imager (GOCI) datasets
These datasets include GOCI L1B, i.e., geostationary ocean color satellite remote sensing data provided by the Korea Ocean Satellite Center. Based on this, SOED has produced normalized water-leaving radiance and surface suspended matter concentration products in two coastal regions, i.e., the Bohai Sea and Yangtze River Estuary, with high spatial and temporal resolution using self-developed atmospheric correction and inversion algorithms.
Names Of data sets | Parameters | Spatial range/resolution | Temporal range/resolution |
Yangtze River Estuary SIO_COMS_GOCI_CJE |
normalized water-leaving radiance (412nm,443nm, 490nm, 555nm,660nm, 680nm, 745nm,865nm), surface suspended matter concentration |
(119°-126°E, 27°-35°N); 500 m |
2011 – 2018.6, monthly average;
2011-2019.8, every hour; (CJE) |
Bohai Sea SIO_COMS_GOCI_BOH |
(117°-123°E, 37°-41°N); 500 m | ||
North Yellow Sea SIO_COMS_GOCI_NYS |
(123°E-126°,37°N-40°N); 500m | ||
Zhejiang Coast SIO_COMS_GOCI_ZJC |
(120°E-124°E,27°N-31°N); 500m | ||
Taiwan Strait SIO_COMS_GOCI_TWS |
(117°E-122°E,24N-27°N); 500m | ||
South Korea Coast SIO_COMS_GOCI_SKC |
(125°E-130°E,33.8°N-35°N); 500m |
3. Western Pacific-Indian Ocean datasets
These datasets are based on the remote sensing reflectance data and products provided by NASA. SOED has produced surface suspended matter concentration, chlorophyll concentration, and seawater transparency products for the eastern Indian Ocean, western Pacific Ocean, and the South China Sea using self-developed inversion algorithms.
Names Of data sets | Parameters | Spatial range/resolution | Temporal range/resolution |
South China Sea SIO_SAT_SENSOR_SCS |
surface suspended matter concentration, surface chlorophyll concentration, sea water transparency | (98°-127°E, 0°-25°N); 1.8 km |
May 2010 – December 2020; monthly average;
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Western Pacific Ocean SIO_SAT_SENSOR_WPO |
(121°-160°E, 2°S-46°N); 1.8 km |
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Eastern Indian Ocean SIO_SAT_SENSOR_EIO |
(80°-118°E, 10°S-21°N); 1.8 km |
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One Belt and One Road region SIO_SAT_SENSOR_AER |
surface chlorophyll concentration, sea surface temperature, photosynthetic effective radiation, sea water transparency, primary productivity | (12°W-150°E, 40°S-80°N); 9 km |
2003 – 2018; monthly average |
Disastrous wave product SIO_MERGE_MERGE_GLOBAL |
count of disastrous wave | (20°-160°W, 60°S-85°N); 9 km |
2006 – 2018; Climatological monthly mean data |
significant wave height | 2006 – 2018; daily average |
These datasets include remote sensing reflectance, total absorption coefficients, and particulate backscattering coefficients retrieved by SeaWiFS, MODIS/Aqua, and VIIRS from NASA. SOED has produced global sea surface CDOM absorption coefficients, backscattering coefficients, and seawater transparency products using self-developed inversion algorithms.
Names Of data sets | Parameters | Spatial range/resolution | Temporal range/resolution |
SeaWiFS SIO_SeaWiFS_SeaWiFS_GLOBAL |
355-nm CDOM absorption coefficient, seawater transparency, non-algal particle absorption coefficient, 660-nm particle attenuation coefficient, 660-nm organic particle attenuation coefficient, sea surface salinity | Global, 9 km |
September 1997- December 2010; daily average, monthly average |
MODIS/Aqua SIO_MODIS_MODIS_GLOBAL |
July 2002 – present; daily average, monthly average |
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VIIRS SIO_SNPP_VIIRS_GLOBAL |
January 2012 – present; daily average, monthly average |
5. NASA public datasets
These datasets are provided by NASA and include remote sensing reflectance, surface chlorophyll concentration, photosynthetic available radiation, concentrations of organic and inorganic particulate carbon from the SeaWiFS, MODIS/Aqua, and VIIRS sensors, and sea surface salinity from the Aquarius sensor.
Names Of data sets | Parameters | Spatial range/resolution | Temporal range/resolution |
Aquarius OBPG_AQUARIUS_AQUARIUS _GLOBAL |
Sea surface salinity | Global, 100 km |
2011-2015; monthly average |
SeaWiFS NASA_SeaWiFS_SeaWiFS_GLOBAL |
Remote sensing reflectance (412nm, 443nm, 490nm,510nm, 555nm, 670nm),surface chlorophyll concentration, photosynthetic available radiation at sea surface, particulate organic carbon, surface particulate inorganic carbon |
Global, 9 km |
September 1997 -December 2010; daily average, monthly average
|
MODIS/Aqua NASA_MODIS_MODIS_GLOBAL |
Remote sensing reflectance (412nm, 443nm, 469nm,488nm, 531nm, 547nm, 555nm, 645nm,667nm),surface chlorophyll concentration, photosynthetic available radiation at sea surface, particulate organic carbon, surface particulate inorganic carbon |
Global, 9 km |
July 2002 – present; daily average, monthly average |
VIIRS NASA_SNPP_VIIRS_GLOBAL |
Remote sensing reflectance (410nm, 443nm, 486nm, 551nm, 671nm),surface chlorophyll concentration, photosynthetic available radiation at sea surface, surface particulate organic carbon, surface particulate inorganic carbon |
Global, 9 km |
January 2012 –January 2021; daily average, monthly average
|
6. Public datasets by other institutions
These datasets are from institutions such as RRS, CMEMS, OSU, ESA, NOAA, and ECMWF and include ocean environmental parameters, such as sea surface temperature, salinity, sea level, mixing layer depth, wind, and rainfall capacity; ecological parameters, such as net primary productivity and multiple-satellite-merged chlorophyll concentration; and atmospheric parameters, such as mole fraction of atmospheric CO2, relative humidity, and sea surface atmospheric pressure.
Names Of data sets | Institution | Parameters | Spatial range/resolution | Temporal range/resolution |
CCMP NASA_MERGE_MERGE_GLOBAL |
Remote Sensing Systems (RRS) | sea surface wind | Global, 25 km |
1987 - 2017; daily average, monthly average |
SMAP NASA_SMAP_MERGE_GLOBAL |
Sea surface salinity |
April 2015 -November 2019; monthly average
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Sea level anomaly CEMES_SAT_MERGE_GLOBAL |
Copernicus Marine environmental monitoring service (CMEMS) | Sea level anomaly | Global, 25 km |
1993 – January 2019;
daily average, monthly average |
Geostrophic flow CEMES_MODEL_MERGE_GLOBAL |
Geostrophic flow |
January 1993 – June 2018; daily average, monthly average
|
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Mixing layer depth CEMES_MODEL_MERGE_GLOBAL |
Mixing layer depth | 1993 – 2017; daily average, monthly average |
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SeaWiFS OSU_SeaWiFS_SeaWiFS_GLOBAL |
Oregon State University (OSU) | Net primary productivity (VGPM,EppleyVGPM, CbPM) |
Global, 9 km |
September 1997 – December 2010; monthly average |
MODIS OSU_MODIS_MODIS_GLOBAL |
July 2002 -August 2019; monthly average
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VIIRS OSU_SNPP_VIIRS_GLOBAL |
2012 - July 2019; monthly average
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SMOS BEC_SMOS_MERGE_GLOBAL |
European Space Agency (ESA) | Sea surface salinity | Global, 100km |
July 2009- April 2017; monthly average
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CCI ESACCI_SAT_MERGE_GLOBAL |
Multiple-satellite-merged chlorophyll concentration | Global, 4 km |
1997 – December 2018; daily average, monthly average |
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CarbonTracker NOAA_MERGE_MERGE_GLOBAL |
National Oceanic and Atmospheric Administration (NOAA) | Atmospheric pCO2 (after correction of the air pressure, water vapour, and spatial interpolation) |
Global, 25 km |
2000-2016; daily average, monthly average |
Relative Humidity NOAA_NCEP_MERGE_GLOBAL |
Relative humidity | Global, 100 km |
2000-2016; daily average | |
AVHRR_OI NOAA__NOAA_AVHRR_GLOBAL |
Sea surface temperature | Global, 25 km |
1981 –April 2020; daily average, monthly average
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SIC NSIDC_DMSP_SSMIS_ARCTIC NSIDC_MERGE_MERGE_ARCTIC |
National Snow and Ice Data Center(NSIDC) | Sea Ice Concentration | Arctic;25km |
October 1978 –December 2017;
Daily average,monthly average |
Landsat Dataset USGS_Landsat_TM/ETM/OLI _ROW/PATH |
U.S. Geological Survey (USGS) | Remote sensing reflectance(Landsat8 443nm, 482nm, 562nm, 655nm, 865nm, 1610nm, 2200nm)(Landsat4,5 483nm, 560nm, 662nm, 835nm, 1648nm, 2206nm)(Landsat7 483nm, 560nm, 662nm, 835nm, 1648nm, 2206nm) |
China Sea, Yangtze River DaTong Station;Zhejiang River;30M | 1989-April 2019; single orbit |
TRMM Precipitation dataset NASA_TRMM_MERGE_GLOBAL |
National Aeronautics and Space Administration (NASA) | 3B42 Daily accumulated(mm) 3B43 Monthly average(m/hr) |
50°S~50°N; 25KM |
1998-December 2019; Daily average, Monthly average |
Underway pCO2 CDIDC-Uderway |
Carbon Dioxide Information Analysis Center (CDIAC) at the U.S. Department of Energy's Oak Ridge National Laboratory | Sea surface pCO2, temperature, salinity | underway | 1992-2015; underway |
References for SOED self-developed algorithms:
Please visit www.SatCO2.com for more information.