Hourly Integrated Land–Atmosphere Interaction Observation Dataset for the High-Altitude Mountainous Region of Gyirong, Tibet (2021–2026)
Approximate English translation from simplified Chinese:
Jilong County, Shigatse City, Tibet, is located on the southern edge of the Himalayas, with high terrain and complex mountainous terrain, and the risk of natural disasters such as flash floods, mudslides and landslides caused or exacerbated by extreme weather is high. On August 26, 2026, a major mudslide disaster occurred at the Geelong Port in Geelong County, causing heavy casualties, which aroused widespread concern from all walks of life about extreme weather and natural disaster risks in the high and cold mountains of the Himalayan region. The disaster also further highlights the importance of long-term continuous meteorological observation in high and cold mountains, and strengthening disaster weather monitoring and scientific research. In order to give full play to the social and scientific research value of long-term scientific observation data, this data set is collated and open to sharing the year-to-hour continuous observation data of the 2021-2026 of the Gaohan Mountain Meteorological Tower in Shigatse City, Tibet, aiming to provide users with accessible and usable basic meteorological observation data in the field of disaster prevention and reduction of scientific research institutions, universities, relevant business departments and disaster prevention and reduction. On the one hand, the data can be used to analyze the structure of the atmospheric boundary layer, weather processes and extreme meteorological events in the high and cold mountains around Geelong, providing long-term observation basis for understanding the evolution of complex mountain weather systems and their environmental background; on the other hand, it can be combined with satellite remote sensing, reanalysis data, weather forecasting products and numerical model results to provide basic data support for regional extreme weather monitoring, disaster weather process analysis, risk identification and disaster prevention and mitigation research. The data set observatory is located in the county town of Geelong (28.86° north latitude, 85.29° east longitude, 4140m above sea level), about 65km from the Jelong Port in the affected area. The data includes 5 layers (1.0, 2.0, 4.0, 10.0, 20.0 m) wind direction, temperature, relative humidity, near ground air pressure, precipitation, radiation four components, and 5 layers of soil hydrothermal parameters (0.1, 0.2, 0.4, 0.8 and 1.6 meters). The data time range is from April 26, 2021 to August 27, 2026, with a time resolution of 1 hour, and the data time is based on Beijing time (UTC+8), and the observation records are collated in accordance with a unified time format. For missing, abnormal or invalid records in the original data, identified and processed according to uniform quality control standards (0: correct, 1: suspicious, 2: error, 4: interpolation data, 8: data missing, 9: no quality control). It should be noted that this data set should not be used directly to characterize the local precipitation and other micro-scale meteorological conditions in the disaster area, nor to directly determine the trigger mechanism of the mudslide. However, long-term continuous observation data can provide an important reference for understanding the extreme weather activities in the Geelong region, changes in atmospheric heat and power structure, and the weather background of natural disasters in high and cold mountains from the perspective of regional atmospheric environment and boundary layer processes, and can be used to demonstrate the potential application value of long-term scientific observations in the study of major natural disaster events.
Data file naming:
This dataset includes meteorological gradient data (MET), radiation data (RADM), soil data (SOIL), and turbulence data (FLUX). The data file (.csv) naming convention is:
QC_Data
Type_Site
Name_Year
.csv.
The table header information of the data file includes the abbreviation of the variable, the height/depth of the observation, and the unit, which is formatted as the variable name _ observation height/depth (unit).
Simplified Chinese Version:
西藏日喀则市吉隆县地处喜马拉雅山南缘，地形高差大、山地地形复杂，极端天气及由其诱发或加剧的山洪、泥石流、滑坡等自然灾害风险较高。2026年8月26日，吉隆县吉隆口岸发生重大泥石流灾害，造成重大人员伤亡，引发了社会各界对喜马拉雅高寒山区极端天气与自然灾害风险的广泛关注。此次灾害也进一步凸显了高寒山区开展长期连续气象观测、加强灾害天气监测与科学研究的重要性。 为充分发挥长期科学观测资料的社会和科研价值，本数据集整理并开放共享西藏日喀则市吉隆县高寒山区气象塔2021–2026年的逐小时连续观测资料，旨在为科研机构、高校、相关业务部门及防灾减灾领域用户提供可获取、可利用的基础气象观测数据。一方面，数据可用于分析吉隆及其周边高寒山区大气边界层结构、天气过程及极端气象事件特征，为认识复杂山区天气系统演变及其环境背景提供长期观测依据；另一方面，可与卫星遥感、再分析资料、天气预报产品和数值模式结果相结合，为区域极端天气监测、灾害天气过程分析、风险识别及防灾减灾研究提供基础数据支撑。 本数据集观测站位于吉隆县城（北纬28.86°，东经85.29°，海拔4140m），距离受灾区吉隆口岸直线距离约65km。数据包含5层（1.0、2.0、4.0、10.0、20.0米）风速风向、气温、相对湿度，近地面气压、降水、辐射四分量，以及5层土壤水热参数（0.1、0.2、0.4、0.8和1.6米）。数据时间范围为2021年4月26日至2026年8月27日，时间分辨率为1小时，数据时间采用北京时间（UTC+8），各观测记录按照统一时间格式进行整理。对于原始数据中的缺测、异常或无效记录，按照统一质量控制标准进行标识和处理（0：正确，1：可疑，2：错误，4：插补数据，8：数据缺失，9：未进行质量控制）。 需要说明的是，本数据集不宜直接用于表征灾区局地降水及其他微尺度气象条件，也不用于直接判定此次泥石流的触发机制。但是，长期连续观测资料能够从区域大气环境和边界层过程角度，为认识吉隆地区极端天气活动、大气热力和动力结构变化以及高寒山区自然灾害天气背景提供重要参考，并可用于展示长期科学观测在重大自然灾害事件研究中的潜在应用价值.
数据文件命名方式和使用方法
本套数据集文件包括气象梯度数据（MET）、辐射数据（RADM）、土壤数据（SOIL）以及湍流数据（FLUX）。数据文件命名规则为：QC_数据类型_站点名称_年份.csv。数据文件的表头信息包括变量的缩写、观测的高度/深度及单位，其格式为变量名_观测高度/深度（单位）。缺失数据为9999.9。
本数据要求的引用方式
数据的引用
马耀明, 马伟强, 谢志鹏, 王宾宾, 陈学龙, 韩存博. (2026). 西藏吉隆高寒山区地气相互作用逐小时综合观测数据集（2021–2026）. 国家青藏高原科学数据中心.
https://doi.org/10.11888/Atmos.tpdc.303600 .
https://cstr.cn/18406.11.Atmos.tpdc.303600 .
Ma, Y., Ma, W., Xie, Z., Wang, B., Chen, X., Han, C. (2026). Hourly Integrated Land–Atmosphere Interaction Observation Dataset for the High-Altitude Mountainous Region of Gyirong, Tibet (2021–2026). National Tibetan Plateau / Third Pole Environment Data Center.
https://doi.org/10.11888/Atmos.tpdc.303600 .
https://cstr.cn/18406.11.Atmos.tpdc.303600 .
(下载引用： RIS格式 RIS英文格式 Bibtex格式 Bibtex英文格式 )
文章的引用
1、Xie, Z. P., Ma, W. Q., Wang, B. B., Han, C. B., Ma, B., Chen, X. L., Wang, Y. J., Li, M. S., Zhong, L., Zhang, Y. S., Ma, W. Y., Shi, X. D., Li, W. M., Cai, Z. L., Hu, W., Liu, L., Yao, N., Xu, X., Xu, H. Y., ... Ma, Y. M. (2026). A comprehensive hourly land-atmosphere interaction dataset from a coordinated 15-station network spanning the environmental gradients of the Tibetan Plateau (2021-2024). Advances in Atmospheric Sciences.
https://doi.org/10.1007/s00376-026-6282-3 ( 查看 Bibtex格式 )
2、Wang, B., Ma, Y., Hu, Z., Li, X., Ma, W., Chen, X., Han, C., Xie, Z., Wang, Y., Li, M., Ma, B., Shi, X., Li, W., and Cai, Z. (2026). Quantifying the spatial-seasonal patterns of land–atmosphere water, heat and CO2 flux exchange over the Tibetan Plateau from an observational perspective. Earth Syst. Sci. Data, 18, 1147–1164,
https://doi.org/10.5194/essd-18-1147-2026 ( 查看 Bibtex格式 )
使用本数据时必须引用“文章的引用”中列出的文献，并进行数据的引用
The station is near the recent flood-affected area in Gyirong County, and the data are available up to August 27, 2026
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