Zoom in

The Tibetan Plateau (TP) is the largest glacier enrichment area in the middle and low latitudes except the South Arctic and Greenland. The solid water body glaciers and liquid water bodies lakes and rivers together form the Asian Water Tower. The thermal and dynamic effects of the TP and their variability are one of the main driving forces for the TP to affect the Asian monsoon and global atmospheric circulation anomalies. To study the thermal properties of the TP itself and its feedback effect, it is necessary to use the results of climate model experiments to carry out the 100-year historical examination of the TP and its surrounding areas and the future 100-year prediction (temperature, precipitation, radiation, etc.).

This dataset consists of grid point temperature, precipitation, radiation and other data of the TP and its surrounding areas. Its horizontal range covers 40 ° E-180 °, 20 ° S-80 ° N, and the time resolution includes annual and seasonal average. The data are based on the results of the BCC-CSM2-MR model test conducted by the National Climate Center of China in the Coupled Model Intercomparison Project Phase 6 (CMIP6), including historical, SSP126, SSP245, SSP370, and SSP585 experiments. According to the bilinear interpolation method, the data are uniformly interpolated to the resolution level of 1 ° x1 °. The data can provide basic information on regional climate and water cycle changes for the second TP investigation period, provide reference for the field investigation results, and study the possible change mechanism.

File naming and required software

This dataset provides the monthly and annual mean gridded data among 40°E-180°, 20°S-80°N, ranging from 1850 to 2100. The historical simulation time range is 1850-2014, and the future projection data (SSP126, SSP245, SSP370, SSP585) time range is 2015-2100.
Data has been stored in netCDF format, and the annual average data named as "VAR_yearmean_BCC-CSM2-MR_EXP_r1i1p1f1_gr1x1_YYYY1-YYYY2.nc ", where VAR represents the variable name, EXP represents the experiment name, and YYYY1 and YYYY2 represent the data start and end years, respectively. For example, evspsbl_yearmean_BCC-CSM2-MR_historical_r1i1p1f1_gr1x1_1850-2014.nc represents the historical simulation of evaporation from 1850 to 2014. The seasonal mean data named as “VAR_SEA_BCC-CSM2-MR_EXP_r1i1p1f1_gr1x1_YYYY1-YYYY2.nc”, where VAR represents the variable name, SEA represents the seasonal mean, EXP represents the experiment name, and YYYY1 and YYYY2 represent the data start and end years, respectively. For example, evspsbl_MAM_BCC-CSM2-MR_ssp126_r1i1p1f1_gr1x1_2015-2100.nc represents the spring average (MAM) evaporation from 2015-2100 under the SSP126 scenario.
Data reading method: All netCDF files in this dataset can be read directly using Matlab, NCL, python and other languages.

Data Citations Data citation guideline What's data citation?

Li, Q. (2022). Historical simulation and future projection dataset of energy and water cycle in the Tibetan Plateau and its surrounding areas (1850-2100). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Atmos.tpdc.272848. CSTR: 18406.11.Atmos.tpdc.272848. (Download the reference： RIS | Bibtex )

1. Yu, J.W., Li, Q.Q., & Ding, Y.H., et al. (2022). Long-term trend of water vapor over the Tibetan Plateau in boreal summer under global warming. Science China Earth Sciences, 65(4), 662–674.( View Details | Bibtex)

2. Wu, Q.Y., Li, Q.Q., & Ding, Y.H., et al. (2022). Asian summer monsoon responses to the change of land‒sea thermodynamic contrast in a warming climate: CMIP6 projections. Advances in Climate Change Research, 13, 205-207.( 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

Second Tibetan Plateau Scientific Expedition Program

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