1-km monthly precipitation dataset for China (1901-2017)


This dataset includes the monthly precipitation data with 0.0083333 arc degree (~1km) for China from Jan 1901 to Dec 2017. The data form belongs to NETCDF, namely .nc file. The unit of the data is 0.1 mm. The dataset was spatially downscaled from CRU TS v4.02 with WorldClim datasets based on Delta downscaling method. The dataset was evaluated by 496 national weather stations across China, and the evaluation indicated that the downscaled dataset is reliable for the investigations related to climate change across China. The dataset covers the main land area of China, including Hong Kong, Macao and Taiwan regions, and excluding islands and reefs in South China Sea.


Data file naming and use method

2019qzkk0603-zgyjsl: in which, 2019QZKK is the project number, 06 represents task 6,03 represents topic 3, and zgyjsl is the initial letter of Chinese pinyin;The data format is NETCDF, nc data can be opened by ArcMAP software;Matlab can be used for extraction and processing, Matlab released the function to read and store the nc file, the reading function is ncread, switch to the nc file storage folder, the statement is expressed as: ncread (' XXX. Nc ', 'var', [I j t], [leni lenj lenj]), where XXX.Var is the name of the variable read from XXX. Nc.I, j and t are respectively the beginning row, column and time of data reading, while leni, lenj and lent I are respectively the length of data reading in the dimension of row, column and time.Thus, this function can be used to read any region and any time period in the study area.


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Citations

1. Ding, Y.X., & Peng, S.Z. (2020). Spatiotemporal trends and attribution of drought across China from 1901–2100. Sustainability, 12(2), 477.( View Details | Bibtex)

2. Peng, S.Z., Ding, Y.X., Wen, Z.M., Chen, Y.M., Cao, Y., & Ren, J.Y. (2017). Spatiotemporal change and trend analysis of potential evapotranspiration over the Loess Plateau of China during 2011–2100. Agricultural and Forest Meteorology, 233, 183–194.( View Details | Bibtex)

3. Peng, S.Z., Ding, Y.X., Liu, W.Z., & Li, Z. (2019). 1 km monthly temperature and precipitation dataset for China from 1901 to 2017. Earth System Science Data, 11, 1931–1946. https://doi.org/10.5194/essd-11-1931-2019( View Details | Bibtex)

4. Peng, S. , Gang, C. , Cao, Y. , & Chen, Y. . (2017). Assessment of climate change trends over the loess plateau in china from 1901 to 2100. International Journal of Climatology.( View Details | Bibtex)

Cite the data

PENG Shouzhang. 1-km monthly precipitation dataset for China (1901-2017). National Tibetan Plateau Data Center, 2020. doi: 10.5281/zenodo.3185722. (Download the reference: RIS | Bibtex )

Using this data, you must reference article references listed in the Required Data Citation and reference data


Support Program

Second Tibetan Plateau Scientific Expedition Program

User Limit

To respect the intellectual property rights, protect the rights of data authors,expand servglacials 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.

Example of acknowledgement statement is included below: The data set is provided by National Tibetan Plateau Data Center (http://data.tpdc.ac.cn).


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


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Keywords
Geographic coverage
Spatial coverage

East: 136.20

South: 16.25

West: 72.20

North: 55.56

Detail
  • Temporal resolution: Monthly
  • Spatial resolution: 1km - 10km
  • File size: 9,922 MB
  • Browse count: 248 Times
  • Apply count: 27 Times
  • Share mode: online
  • Temporal coverage: 1901-01-01 To 2017-12-31
  • Updated time: 2020-03-15
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Contact Information
: PENG Shouzhang  

Distributor: National Tibetan Plateau Data Center

Email: data@itpcas.ac.cn

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