Spatial-temporal Annual Precipitation Dataset in China-Mongolia-Russia Economic Corridor (1982-2018, 1-km/y)
LI Guangshuai1,2LIU Tingxiang2BUKun1YANG Jiuchun1JIAO Yue1,3YU Lingxue*1BAO Yulong4ZHANG Shuwen1
1 Remote Sensing and Geographic Information Research Center，Northeast Institute of Geography and Agroecology，Chinese Academy of Sciences，Changchun 130102，China2 School of Geography Science，Changchun Normal University，Changchun 130032，China3 School of Life Science，Liaoning Normal University，Dalian 116081，China4 School of Geography Science，Inner Mongolia Normal University，Hohhot 010022，China
DOI:10.3974/geodb.2022.02.07.V1
Published:Feb. 2022
Visitors：7260 Data Files Downloaded：229
Data Downloaded：123055.29 MB Citations：
Key Words：
China-Mongolia-Russia Economic Corridor,annual precipitation,ANUSPLIN,1-km,1982-2018,
Abstract：
The spatial-temporal annual precipitation dataset in China-Mongolia-Russia Economic Corridor (1982-2018, 1-km/y) was developed based on the integration between the precipitation records from 353 meteorological stations and the ANUSPLIN model with the longitude, latitude and altitude in the China-Mongolia-Russia Economic Corridor. The results show that R² was 0.9377, where R is the correlation coefficient between meteorological station data and interpolation results. The average Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) values were 4.5 mm and 2.3 mm respectively. The dataset is archived in .tif and .mdd data formats with a spatial resolution of 1 km. It is composed of 189 data files with data size of 5.43 GB (Compressed into three files with 1.53 GB).Browse
Foundation Item：
Chinese Academy of Sciences (XDA2003020301); National Natural Science Foundation of China (42071025); Ministry of Science and Technology of P. R. China (2017FY101301)
Data Citation：
LI Guangshuai, LIU Tingxiang, BUKun, YANG Jiuchun, JIAO Yue, YU Lingxue*, BAO Yulong, ZHANG Shuwen. Spatial-temporal Annual Precipitation Dataset in China-Mongolia-Russia Economic Corridor (1982-2018, 1-km/y)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2022. https://doi.org/10.3974/geodb.2022.02.07.V1.
LI Guangshuai, LIU Tingxiang, BUKun, et al. Spatial–temporal annual precipitation dataset in the China– Mongolia–Russia Economic Corridor (1982–2018, 1-km/y) [J]. Journal of Global Change Data & Discovery, 2022, 6(3): 425-432
References：
[1] Jiao, Y., Yang, J. C., Li, G. S., et al. Temporal and spatial data set of average temperature in China Mongolia Russia Economic Corridor (1982-2018, 1-km / y) [J /DB / OL] Electronic Journal of global change data warehousing (Chinese and English), 2022. https://doi.org/10.3974/geodb.2022.01.03.V1.
[2] Ge, X. R. Prospect analysis of energy cooperation between Russia and Northeast Asian countries [J]. Business Research. 2007(2): 153-155.
[3] Fu, J. Y. Triangular relations between China, Mongolia and Russia and China's strategic choice [J]. Learning Monthly, 2010(2): 43-45.
[4] Hijmans, R. J., Cameron, S. E., Parra, J. L., et al. Very high resolution interpolated climate surfaces for global land areas [J]. International Journal of the Royal Meteorological Society, 2005, 25(15): 1965-1978.
[5] Liu, Z. H., Yang, Q. K., Li, R. Special climate data spatial interpolation software ANUSPLIN and its application [J]. Meteorology, 2008, 34(2): 92-100.
[6] Tan, J. B., Li, A. N., Lei, G. B. Comparative analysis of spatial interpolation of meteorological elements ANUSPLIN and Cokriging in the southeast edge of Qinghai Xizang Plateau [J]. Plateau Meteorology, 2016, 35(4): 875-886.
[7] Liao, R. W., Cao, L. J., Zhang, D. B., et al. Accuracy comparison of gridded data of surface temperature and precipitation in China [J]. Meteorological Science and Technology, 2017, 45(2): 364-374.
[8] Qian, Y. L., Lv, H. Q., Zhang, Y. H. Application and evaluation of daily meteorological element interpolation method based on ANUSPLIN software [J]. Journal of Meteorology and Environment, 2010, 26 (2): 7-15.
[9] Hutchinson, M. F., Xu, T. B. Anusplin version 4.4 user guide [M]. Canberra: Fenner School of Environment and Society, Australian National University, 2013: 1-52.
[10] Liu, Z. H., McVicar, T. R., Li, L. T, et al. Spatial interpolation of meteorological elements in time series based on ANUSPLIN [J]. Journal of Northwest University of Agriculture and Forestry Science and Technology (Natural Science Edition), 2008, 10: 227-34.
[11] Hutchinson, M. F. The application of thin plate splines to continent-wide data assimilation. Data Assimilation Systems. BMRC Research Report No.27 [M]. Melbourne: Bureau of Meteorology, 1991: 104-113.
[12] Xu, X. Q., Zhu, M. X. Comparison of temperature spatial interpolation methods based on GIS in Jiangxi Province [J]. Journal of Green Science and Technology, 2021, 23(10): 21-24.
[13] Meng, Q. Spatial-temporal variation and acquisition of raster dataset of precipitation in the Qinling Mountains [D]. Xi’an: Northwest University, 2021.
[14] Bai, Y. Development of the Spatio-temporal variations dataset of NDVI in Qinling-Daba Mountains of China (2000-2019) [J]. Journal of Global Change Data and Discovery, 2020, 4(4): 346-353.
Data Product:
| ID |
Data Name |
Data Size |
Operation |
| 0 | Datapaper_CMREC_Prcp.pdf | 2559.00kb | DownLoad |
| 1 |
CMREC_Prcp_1982-1999_tif.rar |
624705.18KB |
|
| 2 |
CMREC_Prcp_2000-2018_tif.rar |
659770.82KB |
|
| 3 |
CMREC_Prcp_1982-2018_mdd.rar |
321805.54KB |
|