Meteorological indicators are very commonly used in daily research. Previously we shared with you the meteorological indicator raster data provided by the National Tibetan Plateau Scientific Data Center (you can check the previous articles for details):
- Raster data of monthly average air temperature at 1km resolution from 1901 to 2022
- Raster data of annual average air temperature at 1km resolution from 1901 to 2022
- 1km resolution monthly minimum temperature raster data from 1901 to 2022
- Raster data of annual minimum air temperature with 1km resolution from 1901 to 2022
- 1km resolution monthly maximum air temperature raster data from 1901 to 2022
- Raster data of annual maximum air temperature with 1km resolution from 1901 to 2022
This time we continue to share the high-precision meteorological indicator raster data released by the National Tibetan Plateau Scientific Data Center - monthly precipitation raster data with 1km resolution from 1901 to 2022! The unit of the monthly total precipitation data downloaded from the official website is 0.1mm, the data format is NETCDF, that is, .nc format, and the concept of the data is the monthly total precipitation . For your convenience, we have processed the original data, converted the unit to millimeter (mm), and converted the format to raster (.tif) format . In addition, the nationwide data is very large and inconvenient to use. We have divided the national data into provincial data!
The following is a detailed introduction of the data:
01Data preview
Nationwide data
First of all, let's take a look at the nationwide data. We will provide three kinds of data:
①Data in original nc format
② data in tif format with a spatial range larger than the national border of China
Let's take the national precipitation in July 2022 as an example to preview. The range of the .tif format data converted from the original .nc format data is a rectangular range and is larger than China's national border:
③Tif format data within China’s national boundaries
We extract the monthly total precipitation data within the national boundaries:
Data by province
For the data by province, we take the precipitation in Qinghai Province and Shandong Province in July 2022 as an example to preview:
02 Data details
Data Sources:
The data comes from data shared by scholar Peng Shouzhang on the National Tibetan Plateau Scientific Data Center platform, the website is: https://data.tpdc.ac.cn/zh-hans/data/faae7605-a0f2-4d18-b28f-5cee413766a2
the data shows:
The official website explains the data set. The data is generated in China through the Delta spatial downscaling scheme based on the global 0.5° climate data set released by CRU and the global high-resolution climate data set released by WorldClim. Moreover, the data of 496 independent meteorological observation points are used for verification, and the verification results are credible. The geographical spatial scope included in this dataset is the main land of the country (including Hong Kong, Macao and Taiwan), excluding areas such as South China Sea islands and reefs. It is recommended to use WGS84 as the data coordinate system.
Data Format:
Raster format (.tif) and NETCDF (.nc) format
Data unit:
Raster (.tif) format: Millimeters (mm)
NETCDF (.nc) format: 0.1mm
time limit:
1901-2022 (month by month)
Data coordinates:
for GCS_WGS_1984
Space range:
Nationwide/province
Spatial resolution:
0.0083333° (about 1km)
Data reference:
Peng Shouzhang. 1-km monthly precipitation dataset for China (1901-2022). A Big Earth Data Platform for Three Poles, 10.5281/zenodo.3185722]
Citation of the article publishing the data:
1.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. https://doi.org/10.1016/j.agrformet.2016.11.129
2.Ding, Y.X., & Peng, S.Z. (2020). Spatiotemporal trends and attribution of drought across China from 1901–2100. Sustainability, 12(2), 477.
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
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.
If you have data usage requirements, please quote according to the requirements of the official platform. For more data details, please check the official website!
At the bottom of the article is our official account business card. We will regularly introduce various types of urban data and data visualization and analysis technologies. Regarding the monthly precipitation raster data with 1km resolution from 1901 to 2022, everyone is welcome to pay more attention to us to learn more!