Spatially extensive long-term quality-assured land-atmosphere interactions dataset over the Tibetan Plateau

本数据集集成了12个青藏高原野外观测台站2005-2021年间逐小时地气相互作用综合观测数据，包含多层气象数据、多层土壤数据以及湍流数据。12个野外观测台站分别为珠穆朗玛大气与环境综合观测研究站（QOMS）、藏东南高山环境综合观测研究站（SETORS）、纳木错多圈层综合观测研究站（NAMORS）、阿里荒漠环境综合观测研究站（NASED）、慕士塔格西风带环境综合观测研究站（MAWORS）、鄂陵湖站（Ngoring_Lake）、玛曲站（Maqu）、唐古拉站（TGL），大沙龙站（Dashalong）、阿柔站（Arou）、垭口站（Yakou）和景阳岭站（Jingyangling）。多层气象数据包括风速、风向、气温、湿度、气压、辐射四分量；多层土壤数据包括土壤温度和土壤湿度；湍流数据包括感热通量和潜热通量。同时针对青藏高原野外观测数据中存在的实际问题，为各个台站不同要素针对性地发展了数据质量控制方案，构建了完善的高原野外观测数据处理系统。所有观测要素都经过了严格的数据质量控制流程并提供了数据质量控制码（0：正确数据，1：可疑数据，2：错误数据，4：插补后的数据，8：缺失数据，9：未经数据质量控制）。本数据能广泛应用于青藏高原气象要素特征分析、遥感产品评估和遥感反演算法的发展、数值模拟的评估和发展等研究。

This dataset integrates comprehensive hourly observations of land-atmosphere interactions from 12 field observation stations on the Tibetan Plateau during the period of 2005 to 2021, including multi-layer meteorological data, multi-layer soil data, and turbulence data. The 12 field observation stations are the National Observation and Research Station for Qomolangma Special Atmospheric Processes and Environmental Changes (QOMS), the South-East Tibetan Plateau Station for integrated observation and research of alpine environment (SETORS), the Tibet Nam Co High-cold-lake and Environmental National Observation and Research Station (NAMORS), the Ngari Station for Desert Environment Observation and Research (NASED), the Muztagh Ata Westerly Observation and Research Station (MAWORS), Ngoring_Lake, Maqu, and TGL, Dashalong, Arou, Yakou, and Jingyangling Station. The multilayer meteorological data include wind speed, wind direction, air temperature, humidity, air pressure, and four components of radiation fluxes; the multilayer soil data include soil temperature and soil moisture; and the turbulence data include sensible heat flux and latent heat flux. Meanwhile, in view of the actual problems existing in the field observation data on the Tibetan Plateau, a data quality control program has been developed for different elements of each station, and a comprehensive field observation data processing system has been constructed. All observation elements have undergone a strict data quality control processes and provided data quality control codes (0: correct data, 1: suspicious data, 2: incorrect data, 4: gap-filled data, 8: missing data, 9: not subjected to data quality control). This data can be widely applied in the analysis of meteorological element characteristics, evaluation of remote sensing product, development of remote sensing inversion algorithms, and evaluation and development of numerical simulations on the Tibetan Plateau.

马耀明, 谢志鹏, 陈莹莹, 刘绍民, 车涛, 徐自为, 尚伦宇, 何晓波, 孟宪红, 马伟强, 徐柏青, 赵华标, 王君波, 邬光剑, 李新. (2023). 青藏高原地气相互作用综合观测数据集（2005-2021）. 国家青藏高原科学数据中心. https://doi.org/10.11888/Atmos.tpdc.300977 . https://cstr.cn/18406.11.Atmos.tpdc.300977

Ma, Y., Xie, Z., Chen, Y., Liu, S., Che, T., Xu, Z., Shang, L., He, X., Meng, X., Ma, W., Xu, B., Zhao, H., Wang, J., Wu, G., Li, X. (2023). Spatially extensive long-term quality-assured land-atmosphere interactions dataset over the Tibetan Plateau. National Tibetan Plateau / Third Pole Environment Data Center. https://doi.org/10.11888/Atmos.tpdc.300977

Tibetan Plateau Data Centre
https://data.tpdc.ac.cn/en/data/3b65181a-7f17-4ac1-a034-492fbbd5ec55

Download dataset from WaterNet (use tar -xf TibetanPlateauData.tgz to extract):
https://waternet.ca/fileserver/T-2026-09-03-E1fGRv2CuSk6VgJPOb5UiVw/TibetanPlateauData.tgz

本数据集文件包括气象数据(Met)，土壤数据(Soil)以及湍流数据(Flux)，提供逐小时的观测数据（Level0）以及经过数据质量控制的数据产品（Level1）。Level0数据文件命名规则为:数据类型_站点名称_年份.csv，Level1数据文件命名规则为QC_数据类型_站点名称_年份.csv。同时，该数据集还提供各站点各要素逐月尺度的数据完整性和正确数据比例，数据完整性文件命名规则为：数据类型_站点名称_avail.csv，其中数值100表示该月该要素观测数据无缺失

This dataset file includes meteorological data (Met), soil data (Soil), and turbulence data (Flux), providing hourly observation data (Level0) and data products that have undergone data quality control (Level1). The naming convention for Level0 data files is: data type_ Site Name_ Year. csv, Level1 data file naming convention is QC_ Data type_ Site Name_ Year. csv. At the same time, the dataset also provides monthly data integrity and correct data proportion for each element at each site. The naming rule for data integrity files is: data type_ Site Name_ Avail.csv, where a value of 100 indicates that there are no missing observational data for this element in that month.