祁连山综合观测网：黑河流域地表过程综合观测网（景阳岭站涡动相关仪-2020）

该数据集包含了2020年1月1日至2020年12月31日的黑河流域地表过程综合观测网上游景阳岭站涡动相关仪观测数据。站点位于青海省祁连县景阳岭垭口，下垫面是高寒草甸。观测点的经纬度是101.1160E, 37.8384N，海拔3750m。涡动相关仪的架高4.5m，采样频率是10Hz，超声朝向是正北向，超声风速温度仪（CSAT3B）与CO2/H2O分析仪（Li7500DS）之间的距离是15cm。 涡动相关仪的原始观测数据为10Hz，发布的数据是采用Eddypro软件处理的30分钟数据，其处理的主要步骤包括：野点值剔除，延迟时间校正，坐标旋转（二次坐标旋转），频率响应修正，超声虚温修正和密度（WPL）修正等。同时对各通量值进行质量评价，主要是大气平稳性（Δst）和湍流相似性特征（ITC）的检验。对Eddypro软件输出的30min通量值也进行了筛选：（1）剔除仪器出错时的数据；（2）剔除降水前后1h的数据；（3）剔除10Hz原始数据中每30min内缺失率大于10%的数据。观测数据的平均周期为30分钟，一天48个数据，缺失数据标记为-6999。由于仪器的问题，3.7-3.16, 5.31-7.17, 8.13-8.20, 9.24-10.7数据缺失。 发布的观测数据包括：日期/时间Date/Time，风向Wdir（°），水平风速Wnd（m/s），侧向风速标准差Std_Uy（m/s），超声虚温Tv（℃），水汽密度H2O（g/m3），二氧化碳浓度CO2（mg/m3），摩擦速度Ustar（m/s），奥布霍夫长度L（m），感热通量Hs（W/m2），潜热通量LE（W/m2），二氧化碳通量Fc（mg/(m2s)），感热通量的质量标识QA_Hs，潜热通量的质量标识QA_LE，二氧化碳通量的质量标识QA_Fc。感热、潜热、二氧化碳通量的质量标识分为九级（质量标识1-3数据质量好，4-6数据质量较好，7-8数据质量较差（较插补数据好）；9数据质量差））。数据时间的含义，如0:30代表0:00-0:30的平均；数据以*.xls格式存储。 黑河流域地表过程综合观测网或站点信息请参考Liu et al. (2018)，观测数据处理请参考Liu et al. (2011)。This dataset contains eddy covariance observations collected at the Jingyangling Station, an upstream site of the Heihe River Basin Comprehensive Observation Network for Surface Processes, spanning from January 1, 2020 to December 31, 2020. The station is situated at the Jingyangling Pass, Qilian County, Qinghai Province, with an alpine meadow as its underlying surface. The geographic coordinates of the observation site are 101.1160°E, 37.8384°N, and the elevation is 3750 m. The eddy covariance system has an installation height of 4.5 m, a sampling frequency of 10 Hz, with the sonic anemometer oriented towards true north. The distance between the sonic anemometer thermometer (model CSAT3B) and the CO2/H2O gas analyzer (model Li7500DS) is 15 cm. The raw observation data from the eddy covariance system are sampled at 10 Hz. The publicly released dataset consists of 30-minute averaged data processed using the EddyPro software. The primary processing steps include: outlier removal, time lag correction, second-order coordinate rotation, frequency response correction, sonic virtual temperature correction, and density correction (WPL), among other procedures. Concurrently, quality assessments were performed for each flux product, focusing on tests of atmospheric stationarity (Δst) and turbulence similarity characteristics (ITC). Additionally, the 30-minute flux outputs from EddyPro were screened using the following criteria: (1) exclude data collected during instrument failures; (2) remove data within 1 hour before and after precipitation events; (3) discard data with a missing rate exceeding 10% in the 10 Hz raw data within each 30-minute interval. The observation data have an average period of 30 minutes, yielding 48 data points per day, and missing data are marked with the value -6999. Due to instrument malfunctions, data from March 7 to March 16, May 31 to July 17, August 13 to August 20, and September 24 to October 7 are missing. The publicly released observation data include the following variables: Date/Time, wind direction (Wdir, °), horizontal wind speed (Wnd, m/s), lateral wind speed standard deviation (Std_Uy, m/s), sonic virtual temperature (Tv, ℃), water vapor density (H2O, g/m³), carbon dioxide concentration (CO2, mg/m³), friction velocity (Ustar, m/s), Obukhov length (L, m), sensible heat flux (Hs, W/m²), latent heat flux (LE, W/m²), carbon dioxide flux (Fc, mg/(m²s)), quality flag for sensible heat flux (QA_Hs), quality flag for latent heat flux (QA_LE), and quality flag for carbon dioxide flux (QA_Fc). The quality flags for sensible heat, latent heat, and carbon dioxide fluxes are graded into nine levels: flags 1–3 denote good data quality, 4–6 denote relatively good data quality, 7–8 denote relatively poor data quality (better than interpolated data), and 9 denotes poor data quality. The meaning of the data timestamp is as follows: 0:30 represents the average value over the period 0:00–0:30. All data are stored in *.xls format. For detailed information on the Heihe River Basin Comprehensive Observation Network for Surface Processes or the individual stations, please refer to Liu et al. (2018); for the processing procedures of the observation data, please refer to Liu et al. (2011).