Regional multimodal fusion of surface soil moisture data in China (1850-2100)- A Big Earth Data Platform for Three Poles

Monthly data of 7cm soil moisture in the surface layer of China. The time range includes the historical period 1850-2014 and the future period 2015-2100 (the future period includes four different shared socio-economic paths: ssp1-2.6, ssp2-4.5, ssp3-7.0 and ssp5-8.5). The spatial resolution is 0.25 °.

This data is based on the deep learning method, taking the 7cm surface soil moisture data of era5 land as a reference, and integrating the surface soil moisture data of 25 scaled down cmip6 models. In the context of climate change, data can be used for drought and vegetation correlation analysis.

File naming and required software

File name: the surface soil moisture data is stored in NetCDF format. The name of the file is "ssm_mon_sspxxx_yyyy-yyyy.nc", where XXX represents different shared socio-economic paths (except historical period), and yyyy-yyyy represents the time range.

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Cite as:

Feng, D. (2022). Regional multimodal fusion of surface soil moisture data in China (1850-2100). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Terre.tpdc.272699. CSTR: 18406.11.Terre.tpdc.272699. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Feng, D.H., Wang, G.J., Wei, X.K., Amankwah, S.O.Y., Hu, Y.F., Luo, Z.C., Hagan, D.F.T., & Ullah, W. (2022). Merging and Downscaling Soil Moisture Data From CMIP6 Projections Using Deep Learning Method. Frontiers in Environmental Science, 10.( View Details | Bibtex)

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

Copyright & License

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License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)