Based on the monthly precipitation data of 262 rain gauges, WRF and ERA5 precipitation data in the Yarlung Zangbo River basin, the daily precipitation data with a resolution of 10km from 1951 to 2020 in the Yarlung Zangbo River basin and seven sub basins are reconstructed using random forest learning algorithm. This data has been verified by the single point of the station and performs well in terms of annual and seasonal changes. And the data has been reverse evaluated by the hydrological model, which is used to drive the VIC hydrological model to simulate the runoff change of Yajiang River basin and each sub basin, and verified by the measured runoff, MODIS and glacier cataloging data. On the basis of the original first edition, this data has considered the spatial distribution characteristics of precipitation, which can better describe the precipitation characteristics in alpine regions.

File naming and required software

The data contains 3390 grid files. Each file has four columns, namely year, month, day and precipitation. The file is named data_ Latitude_ Longitude.

Data Citations Data citation guideline What's data citation?

Cite as:

Sun, H. (2022). Daily precipitation data with 10km resolution in the upper Brahmaputra (Yarlung Zangbo River) Basin-V2 (1951-2020). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Atmos.tpdc.272885. CSTR: 18406.11.Atmos.tpdc.272885. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Sun, H., Yao, T., & Su, F., et al. (2022). Corrected ERA5 precipitation by machine learning significantly improved flow simulations for the Third Pole basins. Journal of Hydrometeorology, 23(10). DOI:10.1175/JHM-D-22-0015.1( View Details | Bibtex)

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

Support Program

Second Tibetan Plateau Scientific Expedition Program

the National Natural Science Foundation of China (No:42201140)

Copyright & License

To respect the intellectual property rights, protect the rights of data authors, expand services of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.

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