Dataset List

Vol.|Area

Data Details

30-year Average Monthly/1-km Climate Variables Dataset of China (1951-1980, 1981-2010)


CHENG Qi1WU Xingqi1WEI Linfeng1HU Xiaofei1NI Jian*1,2
1 College of Chemistry and Life Sciences,Zhejiang Normal University,Jinhua 321004,China2 Jinhua Mountain Observation and Research Station for Subtropical Forest Ecosystems,Jinhua 321004,China

DOI:10.3974/geodb.2022.06.03.V1

Published:Jun. 2022

Visitors:7858       Data Files Downloaded:1358      
Data Downloaded:574860.21 MB      Citations:

Key Words:

China,temperature,precipitation,percentage of sunshine,interpolation,1-km

Abstract:

The 30-year Average Monthly/1-km Climate Variables Dataset of China (1951-1980, 1981-2010) was developed using thin plate smoothing spline technique and ANUSPLIN (4.4) tool based on 30-year average meteorological records of national weather stations in China from 1951-1980 and from 1980-2010, re-spectively. The three climatic variables are temperature, precipitation and percentage of sunshine. The error statistics of both station data and interpolated data were performed using the Generalized Cross Validation (GCV), mean absolute errors (MAE) and root mean squared errors (RMSE), as well as the linear regression between the observed and interpolated data. The dataset is archived in .asc, .grd and .tif data formats, and consists of 216 data files with data size of 29.7 GB (Compressed into 8 files with 3.35 GB).Browse

Foundation Item:

Ministry of Science and Technology of P.R. China (2019QZKK0402)

Data Citation:

CHENG Qi, WU Xingqi, WEI Linfeng, HU Xiaofei, NI Jian*. 30-year Average Monthly/1-km Climate Variables Dataset of China (1951-1980, 1981-2010)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2022. https://doi.org/10.3974/geodb.2022.06.03.V1.

CHENG Qi, WU Xingqi, WEI Linfeng, et al. 30-year average monthly/1-km climate variables dataset of China (1951-1980, 1981-2010) [J]. Journal of Global Change Data & Discovery, 2022, 6(4): 533–544.

References:

[1] Fang, J. Y. Ecoclimatological analysis of the forest zones in China [J]. Acta Ecologica Sinica, 1991, 11(4): 377-387.
     [2] Zhang, X S. A vegetation-climate classification system for global change studies in China [J]. Quaternary Sciences, 1993, 13(2): 157-169, 193.
     [3] Ni, J. An introduction to bioclimatic factors in global change research [J]. Quaternary Sciences, 2017, 37(3): 431-441.
     [4] Liu, X. T., Yuan, Q., Ni, J. Research advances in modelling plant species distribution in China [J]. Chinese Journal of Plant Ecology, 2019, 43(4): 273-283.
     [5] Feng, J. M. Spatial patterns of species diversity of seed plants in China and their climatic explanation [J]. Biodiversity Science, 2008, 16(5): 470-476.
     [6] Piao, S. L., Fang, J. Y., He, J. S., et al. Spatial distribution of grassland biomass in China [J]. Chinese Journal of Plant Ecology, 2004, 28(4): 491-498.
     [7] Piao, S. L., Fang, J. Y., Zhou, L. M., et al. Changes in vegetation net primary productivity from 1982 to 1999 in China [J]. Global Biogeochemical Cycles, 2005, 19(2).
     [8] Liu, L., Yang, H., Xu, Y., et al. Forest biomass and net primary productivity in southwestern China: a meta-analysis focusing on environmental driving factors [J]. Forests, 2016, 7(12): 173.
     [9] Cui, S. P., Luo, X., Li, C. W., et al. Predicting the potential distribution of white-lipped deer using the MaxEnt model [J]. Biodiversity Science, 2018, 26(2): 171-176.
     [10] Zhang, X. J., Gao, X. M., Ji, C. J., et al. Response of abundance distribution of five species of Quercus to climate change in Northern China [J]. Chinese Journal of Plant Ecology, 2019, 43(9): 774-782.
     [11] Ni, J., Sykes, M. T., Prentice, I. C., et al. Modelling the vegetation of China using the process-based equilibrium terrestrial biosphere model BIOME3 [J]. Global Ecology and Biogeography, 2000, 9(6): 463-479.
     [12] Ni, J. Carbon storage in terrestrial ecosystems of China: estimates at different spatial resolutions and their responses to climate change [J]. Climatic Change, 2001, 49(3): 339-358.
     [13] Piao, S., Ciais, P., Huang, Y., et al. The impacts of climate change on water resources and agriculture in China [J]. Nature, 467(7311): 43-51.
     [14] Yan, H. Modeling spatial distribution of climate in China using thin plate smoothing spline interpolation [J]. Scientia Geographica Sinica, 2004, 24(2): 163-169.
     [15] 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 Climatology, 2005, 25(15): 1965-1978.
     [16] Tan, J. B., Li, A. N., Lei, G. B. Contrast on anusplin and cokriging meteorological spatial interpolation in southeastern margin of Qinghai-Xizang plateau [J]. Plateau Meteorology, 2016, 35(4): 875-886.
     [17] Hancock, P. A., Hutchinson, M. F. Spatial interpolation of large climate data sets using bivariate thin plate smoothing splines [J]. Environmental Modelling & Software, 2006, 21(12): 1684-1694.
     [18] Xu, T. B., Hutchinson, M. F. New developments and applications in the ANUCLIM spatial climatic and bioclimatic modelling package [J]. Environmental Modelling & Software, 2013, 40: 267-279.
     [19] Fick, S. E., Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas [J]. International Journal of Climatology, 2017, 37(12): 4302-4315.
     [20] Harris, I., Osborn, T. J., Jones, P., et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset [J]. Scientific Data, 2020, 7: 109.
     [21] Chen, L. X., Zhou, X. J., Li, W. L., et al. Characteristics of the climate change and its formation mechanism in China in last 80 years [J]. Acta Meteorologica Sinica, 2004, 62(5): 634-646.
     [22] Wang, J. B., Wang, J. W., Ye, H., et al. An interpolated temperature and precipitation dataset at 1 km grid resolution in China (2000-2012) [J/OL]. China Scientific Data, 2017, 2(1).
     [23] Peng, S. Z., Ding, Y. X., Liu, W. Z., et al. 1 km monthly temperature and precipitation dataset for China from 1901 to 2017 [J]. Earth System Science Data, 2019, 11(4): 1931-1946.
     [24] Chen, W., Sun, L. Q., Li, Q. L., et al. An interpolation dataset for temperature and precipitation at 1km grid resolution in Chinese mainland for recent 38 Years [J]. Meteorological Science and Technology, 2021, 49(3): 355-361.
     [25] Niu, Z. G., He, H. L., Zhu, G. F., et al. A spatial-temporal continuous dataset of the transpiration to evapotranspiration ratio in China from 1981-2015 [J]. Scientific Data, 2020(7): 369.
     [26] He, J., Yang, K., Tang, W., et al. The first high-resolution meteorological forcing dataset for land process studies over China [J]. Scientific Data, 2020(7): 25.
     [27] The Central Meteorological Administration Information Office. The Dataset for Climate of China’s Mainland [M]. Beijing: Meteorological Press, 1984.
     [28] Hutchinson, M. F., Xu, T. B. ANUSPLIN Version 4.4 User Guide [M]. Canberra: Fenner School of Environment and Society, the Australian National University, 2013.
     [29] Farr, T. G., Rosen, P. A., Caro, E., et al. The shuttle radar topography mission [J]. Reviews of Geophysics, 2007, 45(2): RG2004.
     [30] Liu, Z. H., Mcvicar, T., Niel, V., et al. Introduction of the professional interpolation software for meteorology data: ANUSPLINN [J]. Meteorological Monthly, 2008, 34(2): 92-100.]
     [31] Jiang, X. J., Liu, X. J., Huang, F., et al. Comparison of spatial interpolation methods for daily meteorological elements [J]. Chinese Journal of Applied Ecology, 2010, 21(3): 624-630.
     [32] The Editorial Committee of Vegetation Map of China, Chinese Academy of Science. Vegetation Atlas of China (1:1000 000) [M]. Beijing: Science Press, 2001.
     [33] Wei, L. F., Hu, X. F., Cheng Q., et al. A dataset of spatial distribution of bioclimatic variables in China at 1km resolution [J/OL]. China Scientific Data, 2022.
     [34] Wu, X. Q., Cheng Q., Wei, L. F., et al. A time series dataset of climate variables from 1951 to 2014 in karst region of southwestern China [J/OL]. China Scientific Data, 2022.
     

Data Product:

ID Data Name Data Size Operation
0Datapaper_ChinaClimate_1951-2010.pdf5291.00kbDownLoad
1 ChinaClimate_1951-1980_asc.rar 382460.08KB
2 ChinaClimate_1951-1980_grd1.rar 490279.92KB
3 ChinaClimate_1951-1980_grd2.rar 505307.81KB
4 ChinaClimate_1951-1980_tif.rar 343837.11KB
5 ChinaClimate_1981-2010_asc.rar 401774.98KB
6 ChinaClimate_1981-2010_grd1.rar 508168.87KB
7 ChinaClimate_1981-2010_grd2.rar 527189.16KB
8 ChinaClimate_1981-2010_tif.rar 359396.82KB
Co-Sponsors
Superintend