Meteorological data is an important indicator for understanding regional desertification. At present, Dunhuang is facing a severe desertification situation, but meteorological data in the region is still relatively scattered. This study is based on the Dunhuang Natural Data Statistical Yearbook and systematically summarizes key data such as local temperature and precipitation since the 21st century. This data will help evaluate the ecological environment of Dunhuang and propose appropriate solutions to curb desertification.
The meteorological data used in this study is sourced from the Dunhuang Natural Data Statistical Yearbook, covering long-term observation records since the 21st century. The data indicators include average temperature, daily maximum temperature, daily minimum temperature, sunshine hours, precipitation, and average wind speed, reflecting the main climatic characteristics of the region. The yearbook data has undergone official statistics and review, and has high reliability and traceability, providing basic support for analyzing climate change trends and desertification processes in the Dunhuang region. In addition, the data is recorded on an annual and daily scale, which facilitates time series analysis and cross year comparisons.
The collected meteorological data is digitized and imported into a computer for organization. Data processing includes unifying time scales, filling missing values, and necessary unit conversions, such as converting temperature to degrees Celsius and precipitation to millimeters. Daily observation data can be further summarized and calculated as monthly or annual averages for long-term climate trend analysis. The data has also undergone time series sorting and preliminary statistical analysis, including the calculation of maximum, minimum, mean, and standard deviation, to ensure that the data can be directly used for desertification process assessment and related model research.
All data is sourced from official statistical yearbooks and has undergone strict statistical and auditing procedures, ensuring high reliability. During the collection process, outliers and missing measurements were marked and processed, and missing data was supplemented through linear interpolation or the average of adjacent years. Compare repeated observations with long-term trends to ensure data continuity and consistency. The processed data has been stored in a unified format and the original data backup has been retained to ensure data traceability and long-term stability.
| # | number | name | type |
| 1 | 2020YFA0608400 | National key R & D plan |
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.NCDC.DESERTIFICATION.DB7166.2026
10.12072/ncdc.desertification.db7166.2026
