Appendix 1: Source of base map
The base map data come from the public map service of ESRI (Environmental Systems Research Institute, Inc.). When you use the data, you must abide the terms of service (https://www.esri.com/zh-cn/legal/terms/full-master-agreement).
The SIO and ZJU shall not assume all responsibilities arising from the user’s release, copy, or modification of the data in violation of the provisions.
S5.1. Spherical coordinate system
SatCO2 platform uses the WGS84 coordinate system. The settings of the geographic coordinate system are as follows:
GEOGCS["WGS 84",
DATUM["WGS_1984",
SPHEROID["WGS 84",6378137,298.257223563,
AUTHORITY["EPSG","7030"]],
TOWGS84[0,0,0,0,0,0,0],
AUTHORITY["EPSG","6326"]],
PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],
UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9108"]],
AUTHORITY["EPSG","4326"]]
S5.2. Gridding method of in situ data
In general, a series of discrete points in the study area need to be mapped on regular grid for processing, or combined with other gridded data. Creating a raster grid from discrete in situ data points requires the process of interpolation of discrete data. Figure S1 is a schematic diagram of grid interpolation.
Figure S 1. Schematic diagram of gridding interpolation.The interpolation method in SatCO2 platform is the nearest interpolation method. It is to assign the corresponding in situ data, which are the closest of the space distance to the target raster. The advantage of this method is that the original in situ grid values will not be changed and the processing speed is fast.
S5.3. Spatial-temporal matching
The strategies of spatial-temporal matching processing of in situ data and satellite images in SatCO2 platform are as follows:
1) Take the latitude and longitude data of in situ sampling points, and match the longitude and latitude of satellite data. Due to the large spatial scale of satellite data, there will be multiple sampling points corresponding to the same satellite grid data (for example, within the same 4-km grid).
2) The time information of in situ sampling points corresponds to the time of satellite image. Since satellite data are daily, 10-day average, or monthly average data, there will be one satellite data value, corresponding to multiple sampling points (such as sampling within 10 days or continuous station sampling).
3) If the in situ sampling point cannot match the valid satellite data, the user can choose to match the climatological satellite data.
If multiple satellite images that meet the requirements are matched, a numerical average is taken as the matching result.
Appendix 6：Air-sea CO2 flux calculation
S7.1. The HAB algorithm in the East China Sea
S7.2. The RBD based HAB algorithm
S7.3. The RGCI based HAB algorithm
S7.4. The ABI based HAB algorithm
S7.5. The FLH based HAB algorithm
