Multi-scale surface flux and meteorological elements observation dataset in the Haihe River Basin (Huailai station-eddy covariance system-10m tower, 2015)

The data set contains the observation data of the vorticity correlator of 10m tower on December 31, 2015 from January 1, 2015 to solstice.Station is located in huailai county, hebei province, east garden town, under the surface of irrigated corn.The latitude and longitude of the observation point is 115.7880E, 40.3491N, and the altitude is 480m.The acquisition frequency of vortex correlativity instrument is 10Hz, the frame height is 5m, the ultrasonic direction is due to the north, and the distance between the ultrasonic anometer (CSAT3) and the CO2/H2O analyzer (Li7500A) is 15cm. The released data is the 30-minute data obtained from the post-processing of the original collected 10Hz data with Eddypro software. The main steps of the processing include: outfield value elimination, delay time correction, coordinate rotation (secondary coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction.Quality assessment for each intercompared to at the same time, mainly is the atmospheric stability (Δ st) and turbulent characteristics of similarity (ITC) test.The 30min pass value output after processing was also screened :(1) the data when the instrument was wrong was removed;(2) data of 1h before and after precipitation were excluded;(3) the missing rate of 10Hz original data is more than 10% every 30min;(4) the observed data of weak turbulence at night were excluded (u* less than 0.1m/s).The average period of observation data was 30 minutes, 48 data a day, and the missing data was marked as -6999.May 14 solstice May 20 and May 24 solstice June 6 due to power converter damage, data missing. The observation data released by vortex correlator include:Date/Time for the Date/Time, wind Wdir (°), Wnd horizontal wind speed (m/s), standard deviation Std_Uy lateral wind speed (m/s), ultrasonic virtual temperature Tv (K), the water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar) (m/s), the length of cloth hoff, sensible heat flux Hs (W/m2), latent heat flux LE (W/m2), carbon dioxide flux Fc (mg/(m2s)), the quality of the sensible heat flux identifier QA_Hs, the quality of the latent heat flux identifier QA_LE.The quality of the sensible heat and latent heat, carbon dioxide flux identification is divided into three (quality id 0: (Δ st < 30, the ITC < 30);1: (Δ st < 100, ITC < 100);The rest are 2).The meaning of data time, such as 0:30 represents the average between 0:00 and 0:30;The data is stored in *.xls format. Please refer to Guo et al, 2020 for information of observation test or site, and Liu et al. (2013) for data processing.

0 2020-10-28

Multi-scale surface flux and meteorological elements observation dataset in the Hai River Basin (Huailai station-eddy covariance system-40m tower, 2016)

The data set contains the observation data of 40m tower vortex correlator on January 1, 2016, solstice, 2016, December 31, 2016.The station is located in east garden town, huailai county, hebei province.The latitude and longitude of the observation point is 115.7923E, 40.3574N, and the altitude is 480m.The acquisition frequency of vortex correlativity instrument is 10Hz, the frame height is 3.5m, the ultrasonic direction is due to the north, and the distance between the ultrasonic anemometer (CSAT3) and the CO2/H2O analyzer (EC150) is 0cm. The released data is the 30-minute data obtained from the post-processing of the original collected 10Hz data with Eddypro software. The main steps of the processing include: outfield value elimination, delay time correction, coordinate rotation (secondary coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction.Quality assessment for each intercompared to at the same time, mainly is the atmospheric stability (Δ st) and turbulent characteristics of similarity (ITC) test.The 30min pass value output after processing was also screened :(1) the data when the instrument was wrong was removed;(2) data of 1h before and after precipitation were excluded;(3) the missing rate of 10Hz original data is more than 10% every 30min;(4) the observed data of weak turbulence at night were excluded (u* less than 0.1m/s).The average period of observation data was 30 minutes, 48 data a day, and the missing data was marked as -6999.There are many negative values of water vapor density measured by EC150 in winter, filled with -6999. The observation data released by vortex correlator include:Date/Time for the Date/Time, wind Wdir (°), Wnd horizontal wind speed (m/s), standard deviation Std_Uy lateral wind speed (m/s), ultrasonic virtual temperature Tv (K), the water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar) (m/s), the length of cloth hoff, sensible heat flux Hs (W/m2), latent heat flux LE (W/m2), carbon dioxide flux Fc (mg/(m2s)), the quality of the sensible heat flux identifier QA_Hs, the quality of the latent heat flux identifier QA_LE.The quality of the sensible heat and latent heat, carbon dioxide flux identification is divided into three (quality id 0: (Δ st < 30, the ITC < 30);1: (Δ st < 100, ITC < 100);The rest are 2).The meaning of data time, such as 0:30 represents the average between 0:00 and 0:30;The data is stored in *.xls format.The data was missing during the period from May 26 to May 29 due to instrument calibration. Guo et al, 2020 is used for site introduction and Liu et al, 2013 for data processing

0 2020-10-27

Multi-scale surface flux and meteorological elements observation dataset in the Hai River Basin (Huailai station-eddy covariance system-10m tower, 2016)

The data set contains the observation data of 10m tower vortex correlator on January 1, 2016, solstice, 2016, December 31, 2016.The station is located in east garden town, huailai county, hebei province.The latitude and longitude of the observation point is 115.7880E, 40.3491N, and the altitude is 480m.The acquisition frequency of vortex correlativity instrument is 10Hz, the frame height is 5m, the ultrasonic direction is due to the north, and the distance between the ultrasonic anometer (CSAT3) and the CO2/H2O analyzer (Li7500A) is 15cm. The released data is the 30-minute data obtained from the post-processing of the original collected 10Hz data with Eddypro software. The main steps of the processing include: outfield value elimination, delay time correction, coordinate rotation (secondary coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction.Quality assessment for each intercompared to at the same time, mainly is the atmospheric stability (Δ st) and turbulent characteristics of similarity (ITC) test.The 30min pass value output after processing was also screened :(1) the data when the instrument was wrong was removed;(2) data of 1h before and after precipitation were excluded;(3) the missing rate of 10Hz original data is more than 10% every 30min;(4) the observed data of weak turbulence at night were excluded (u* less than 0.1m/s).The average period of observation data was 30 minutes, 48 data a day, and the missing data was marked as -6999.On May 27, BBB 0, July 22, there was a problem with the ultrasonic anemometer, and the data was missing. The observation data released by vortex correlator include:Date/Time for the Date/Time, wind Wdir (°), Wnd horizontal wind speed (m/s), standard deviation Std_Uy lateral wind speed (m/s), ultrasonic virtual temperature Tv (K), the water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar) (m/s), the length of cloth hoff, sensible heat flux Hs (W/m2), latent heat flux LE (W/m2), carbon dioxide flux Fc (mg/(m2s)), the quality of the sensible heat flux identifier QA_Hs, the quality of the latent heat flux identifier QA_LE.The quality of the sensible heat and latent heat, carbon dioxide flux identification is divided into three (quality id 0: (Δ st < 30, the ITC < 30);1: (Δ st < 100, ITC < 100);The rest are 2).The meaning of data time, such as 0:30 represents the average between 0:00 and 0:30;The data is stored in *.xls format. Guo et al, 2020 is used for site introduction and Liu et al, 2013 for data processing。

0 2020-10-27

Multi-scale surface flux and meteorological elements observation dataset in the Hai River Basin (Huailai station-eddy covariance system-40m tower, 2017)

The data set contains the observation data of 40m tower vortex correlator on January 1, 2017, solstice, 2017, December 31, 2017.The station is located in east garden town, huailai county, hebei province.The latitude and longitude of the observation point is 115.7923E, 40.3574N, and the altitude is 480m.The acquisition frequency of vortex correlativity instrument is 10Hz, the frame height is 3.5m, the ultrasonic direction is due to the north, and the distance between the ultrasonic anemometer (CSAT3) and the CO2/H2O analyzer (EC150) is 0cm. The released data is the 30-minute data obtained from the post-processing of the original collected 10Hz data with Eddypro software. The main steps of the processing include: outfield value elimination, delay time correction, coordinate rotation (secondary coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction.Quality assessment for each intercompared to at the same time, mainly is the atmospheric stability (Δ st) and turbulent characteristics of similarity (ITC) test.The 30min pass value output after processing was also screened :(1) the data when the instrument was wrong was removed;(2) data of 1h before and after precipitation were excluded;(3) the missing rate of 10Hz original data is more than 10% every 30min;(4) the observed data of weak turbulence at night were excluded (u* less than 0.1m/s).The average period of observation data was 30 minutes, 48 data a day, and the missing data was marked as -6999.There are many negative values of water vapor density measured by EC150 in winter, filled with -6999. The observation data released by vortex correlator include:Date/Time for the Date/Time, wind Wdir (°), Wnd horizontal wind speed (m/s), standard deviation Std_Uy lateral wind speed (m/s), ultrasonic virtual temperature Tv (K), the water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar) (m/s), the length of cloth hoff, sensible heat flux Hs (W/m2), latent heat flux LE (W/m2), carbon dioxide flux Fc (mg/(m2s)), the quality of the sensible heat flux identifier QA_Hs, the quality of the latent heat flux identifier QA_LE.The quality of the sensible heat and latent heat, carbon dioxide flux identification is divided into three (quality id 0: (Δ st < 30, the ITC < 30);1: (Δ st < 100, ITC < 100);The rest are 2).The meaning of data time, such as 0:30 represents the average between 0:00 and 0:30;The data is stored in *.xls format.The data was missing during the period from May 26 to May 29 due to instrument calibration. Guo et al, 2020 is used for site introduction and Liu et al, 2013 for data processing.

0 2020-10-27

Multi-scale surface flux and meteorological elements observation dataset in the Hai River Basin (Huailai station-eddy covariance system-10m tower, 2017)

This data set contains the observation data of 10 m tower eddy covariance instrument from January 1, 2017 to December 31, 2017. The site is located in donghuayuan Town, Huailai County, Hebei Province. The longitude and latitude of the observation point are 115.7880e, 40.3491n and 480m above sea level. The acquisition frequency of the eddy correlator is 10Hz, the height of the frame is 5m, the ultrasonic direction is due north, and the distance between the ultrasonic anemometer (csat3) and the CO2 / H2O analyzer (li7500a) is 15cm. The released data is 30 minutes data obtained by post-processing the original collected 10Hz data by eddypro software. The main processing steps include: outlier value elimination, delay time correction, coordinate rotation (secondary coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction. At the same time, the quality evaluation of each flux value is mainly the test of atmospheric stability (Δ st) and turbulence similarity characteristics (ITC). The 30 min flux values output after processing were also screened: (1) the data of instrument error; (2) the data of 1 h before and after precipitation; (3) the data of 10 Hz original data missing more than 10% every 30 min; (4) the observation data of weak turbulence at night (U * less than 0.1 M / s) were eliminated. The average period of observation data is 30 minutes. There are 48 data in a day, and the missing data is marked as - 6999. From May 27 to July 22, the data was missing due to problems with the ultrasonic anemometer. The observational data released by eddy correlator include date / time, wind direction WDIR (°), horizontal wind speed wnd (M / s) and standard deviation of lateral wind speed STD_ Uy (M / s), ultrasonic virtual temperature TV (k), water vapor density H2O (g / m3), carbon dioxide concentration CO2 (mg / m3), friction velocity ustar (M / s), obuhof length, sensible heat flux HS (w / m2), latent heat flux Le (w / M2), carbon dioxide flux FC (mg / (M2S)), quality identification of sensible heat flux QA_ HS, quality identification of latent heat flux QA_ LE。 The quality identification of sensible heat, latent heat and carbon dioxide flux can be divided into three levels (quality mark 0: (Δ st < 30, ITC < 30); 1: (Δ st < 100, ITC < 100); the rest are 2). The meaning of data time, for example, 0:30 represents the average of 0:00-0:30; the data is stored in *. XLS format. Guo et al, 2020 is used for site introduction and Liu et al, 2013 for data processing

0 2020-10-27

A long term hourly eddy covariance dataset of consistently processed CO2 and H2O Fluxes from the Tibetan Alpine Steppe at Nam Co (2005 - 2019)

The data set contains nearly 15 years of eddy covariance data from an alpine steppe ecosystem on the central Tibetan Plateau.The data was processed following standardized quality control methods to allow for comparability between the different years of our record and with other data sets. To ensure meaningful estimates of ecosystem atmosphere exchange, careful application of the following correction procedures and analyses was necessary: (1) Due to the remote location, continuous maintenance of the eddy covariance (EC) system was not always possible, so that cleaning and calibration of the sensors was performed irregularly. Furthermore, the high proportion of bare soil and high wind speeds led to accumulation of dirt in the measurement path of the infrared gas analyzer (IRGA). The installation of the sensor in such a challenging environment resulted in a considerable drift in CO2 and H2O gas density measurements. If not accounted for, this concentration bias may distort the estimation of the carbon uptake. We applied a modified drift correction procedure following Fratini et al. (2014) which, instead of a linear interpolation between calibration dates, uses the CO2 concentration measurements from the Mt. Waliguan atmospheric observatory as reference time series. (2) We applied rigorous quality filtering of the calculated fluxes to retain only fluxes which represent actual physical processes. (3) During the long measurement period, there were several buildings constructed in the near vicinity of the EC system. We investigated the influence of these obstacles on the turbulent flow regime to identify fluxes with uncertain land cover contribution and exclude them from subsequent computations. (4) We calculated the de-facto standard correction for instrument surface heating during cold conditions (hereafter called sensor self heating correction) following Burba et al. (2008) and a revision of the original method following Frank and Massman (2020). (5)Subsequently, we applied the traditional and widely used gap filling procedure following Reichstein et al. (2005) to provide a more complete overview of the annual net ecosystem CO2 exchange.(6) We estimated the flux uncertainty by calculating the random flux error (RE) following Finkelstein and Sims (2001) and by using the standard deviation of the fluxes used for gap filling(NEE_fsd) as a measure for spatial and temporal variation.

0 2020-09-11

Cold and Arid Research Network of Lanzhou university (eddy covariance system of Liancheng station, 2019)

This dataset contains the flux measurements from the Liancheng station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from August 17 to November 1 in 2019. The site (102.737E, 36.692N) was located on a forest in the Tulugou national forest park, which is near Yongdeng city, Gansu Province. The elevation is 2912 m. The EC was installed at a height of 4.0 m, and the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (CSAT3&Li7500A) was 0.17 m. The raw data acquired at 10 Hz were processed using the Eddypro post-processing software, including the spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. The observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC): class 1-3 (high quality), class 4-6 (good), class 7-8 (poor, better than gap filling data), class9 (rejected). In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data collected before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day, and the missing data were replaced with -6999. Suspicious data were marked in red. The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m3), CO2 mass density (CO2, mg/m3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m2), latent heat flux (LE, W/m2), carbon dioxide flux (Fc, mg/ (m2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xls format. Detailed information can be found in the suggested references.

0 2020-07-25

Cold and Arid Research Network of Lanzhou university (eddy covariance system of Minqin station, 2019)

This dataset contains the flux measurements from the Minqin station eddy covariance system (EC) in the middle reaches of the Shiyanghe integrated observatory network from August 29 to December 31 in 2019. The site (103.668E, 39.208N) was located on a alpine meadow in the Wuwei, Gansu Province. The elevation is 1020 m. The EC was installed at a height of 4.0 m, and the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (CSAT3&Li7500A) was 0.17 m. The raw data acquired at 10 Hz were processed using the Eddypro post-processing software, including the spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. The observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC): class 1-3 (high quality), class 4-6 (good), class 7-8 (poor, better than gap filling data), class9 (rejected). In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record; and data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day, and the missing data were replaced with -6999. Suspicious data were marked in red. The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m3), CO2 mass density (CO2, mg/m3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m2), latent heat flux (LE, W/m2), carbon dioxide flux (Fc, mg/ (m2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xls format. Detailed information can be found in the suggested references.

0 2020-07-25

Qilian Mountains integrated observatory network: Dataset of the Heihe River Basin integrated observatory network (eddy covariance system of Jingyangling station, 2018)

This dataset contains the flux measurements from the Jingyangling station eddy covariance system (EC) in the upperstream reaches of the Heihe integrated observatory network from August 28 to December 31 in 2018. The site (101.1160E, 37.8384N) was located in the Jingyangling, near Qilian County in Qinghai Province. The elevation is 3750 m. The EC was installed at a height of 4.5 m, and the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (CSAT3&Li7500) was 0.15 m. The raw data acquired at 10 Hz were processed using the Eddypro post-processing software, including the spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. The observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC): class 1-3 (high quality), class 4-6 (good), class 7-8 (poor, better than gap filling data), class9 (rejected). In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data collected before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 10% of the 30 min raw record. There were 48 records per day, and the missing data were replaced with -6999. Suspicious data were marked in red. Data during insufficient power supply, data were missing occasionally. The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m3), CO2 mass density (CO2, mg/m3), friction velocity (ustar, m/s), stability (L), sensible heat flux (Hs, W/m2), latent heat flux (LE, W/m2), carbon dioxide flux (Fc, mg/ (m2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xls format. Detailed information can be found in the suggested references. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) for data processing) in the Citation section.

0 2020-07-25