Zoom in

China's daily snow depth simulation and prediction data set is the estimated daily snow depth data of China in the future based on the nex-gdpp model data set. The artificial neural network model of snow depth simulation takes the maximum temperature, minimum temperature, precipitation data and snow depth data of the day as the input layer of the model, The snow depth data of the next day is used as the target layer of the model to build the model, and then the snow depth simulation model is trained and verified by using the data of the national meteorological station. The model verification results show that the iterative space-time simulation ability of the model is good; The spatial correlations of the simulated and verified values of cumulative snow cover duration and cumulative snow depth are 0.97 and 0.87, and the temporal and spatial correlations of cumulative snow depth are 0.92 and 0.91, respectively. Based on the optimal model, this model is used to iteratively simulate the daily snow depth data in China in the future. The data set can provide data support for future snow disaster risk assessment, snow cover change research and climate change research in China. The basic information of the data is as follows: historical reference period (1986-2005) and future (2016-2065), as well as rcp4.5 and rcp8.5 scenarios and 20 climate models. Its spatial resolution is 0.25 ° * 0.25 °. The projection mode of the data is ease GR, and the data storage format is NC format.

The following is the data file information in NC

Time: duration (unit: day)

Lon = 320 matrix, 320 columns in total

Lat = 160 matrix, 160 rows in total

X Dimension: Xmin = 60.125; // Coordinates of the corner points of the lower left corner grid in the X direction of the matrix

Y Dimension: Ymin = 15.125; // Coordinates of the corner points of the grid at the lower left corner of the Y-axis of the matrix

File naming and required software

The future daily snow depth data is stored in NC. The file name is "rcp45access1-0.nc", in which rcp45 represents the climate situation and access1-0.nc represents the climate model. The data includes the snow cover in China every day from January 1, 2016 to December 31, 2065. The opening method is to open, browse and edit with metalinf or panoply software. The data is large. It is recommended to use MATLAB and python programming to open it.

Data Citations Data citation guideline What's data citation?

Chen, H., Yang, J., Ding, Y. (2021). Daily snow depth simulation prediction dataset for China. A Big Earth Data Platform for Three Poles, DOI: 10.11888/Snow.tpdc.271636. CSTR: 18406.11.Snow.tpdc.271636. (Download the reference： RIS | Bibtex )

1. Chen, H., Yang, J., Ding, Y., He, Q., & Ji, Q. (2021). Simulation of Daily Snow Depth Data in China Based on the NEX-GDDP. Water, 13(24), 3599. doi:10.3390/w13243599( 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

National Key Research and Development Program of China

the Strategic Priority Research Program of Chinese Academy of Sciences

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)

Related Resources

Comments

Current page automatically show English comments Show comments in all languages