Based on the historical daily maximum temperature data and reanalysis data set of stations, a daily maximum temperature statistical downscaling model based on first-order autoregressive and multiple linear regression models is developed. Driven by the IPCC cmip6 scenario data of the global climate model (cnrm-cm6-1), the statistical downscaling model predicts the number of five heat wave indexes (heat wave events) of 65 stations in Central Asia from 2015 to 2100 (HWM), heat wave frequency (HWF), heat wave intensity (HWM), maximum duration of heat wave (HWD), heat wave amplitude (HWA)). Finally, the heat wave change scenario data sets of 65 stations in Central Asia under four emission scenarios (ssp126, ssp245, ssp370, ssp585) from 2015 to 2100 were obtained.

File naming and required software

The data is stored in text format, and the file name is SDMMHWASSP126.txt, where SDM stands for statistical downscaling results, HWN stands for heat wave index, and SSP126 stands for situational data in SSP126. Such as SDMHWASSP126. TXT represents the statistical downscaling data set of heat wave index HWN in SSP126 scenario

Data Citations Data citation guideline What's data citation?

Cite as:

Fan, L. (2021). Scenario projection data set of heat wave indices in Central Asia（2015-2100）. A Big Earth Data Platform for Three Poles, DOI: 10.11888/Atmos.tpdc.271860. CSTR: 18406.11.Atmos.tpdc.271860. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Fan, L., Yan, Z., Chen, D., & Li, Z. (2021). Assessment of Central Asian heat extremes by statistical downscaling: Validation and future projection for 2015‒2100. Advances in Climate Change Research, Retrieved from https://doi.org/10.1016/j.accre.2021.09.00( 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

Pan-Third Pole Environment Study for a Green Silk Road-A CAS Strategic Priority A Program (No:XDA20000000)

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the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results).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)