Surface downward radiation (SDR), including shortwave downward radiation (SWDR) and longwave downward radiation (LWDR), is of great importance to energy and climate studies. Considering the lack of reliable SDR data with a high spatiotemporal resolution in the East Asia-Pacific (EAP) region, we derived SWDR and LWDR at 10-min and 0.05° resolutions for this region from 2016-2020 based on the next-generation geostationary satellite Himawari-8 (H-8). The SDR product is unique in terms of its all-sky features, high accuracy and high resolution levels. The cloud effect is fully considered in the SDR product, and the influence of high aerosol loadings and topography on the SWDR are considered. Compared to benchmark products of the radiation, such as Clouds and the Earth’s Radiant Energy System (CERES) and the European Centre for Medium-Range Weather Forecasts (ECMWF) next-generation reanalysis (ERA5), and the Global Land Surface Satellite (GLASS), not only is the resolution of the new SDR product notably much higher but the product accuracy is also higher than that of those products. In particular, hourly and daily root mean square errors of hourly and daily of the new SWDR are 104.9 and 31.5 Wm-2, respectively, which are much smaller than those of CERES (at 121.6 and 38.6 Wm-2, respectively), ERA5 (at 176.6 and 39.5 Wm-2, respectively) and GLASS (daily of 36.5 Wm-2). Meanwhile, RMSEs of hourly and daily values of the new LWDR are 19.6 and 14.4 Wm-2, respectively, which are comparable to that of CERES and ERA5, and even better over high altitude regions.
HUSI Letu, WANG Tianxing, DU Yihan
This data set is the conventional meteorological observation data of the Ngoring Lake Grassland Observation site (GS) in the source region of the Yellow River from 2017 to 2020, obtained by using Kipp&Zonen CNR4, Vaisala HMP155A, PTB110 and other instruments, with a time resolution of half an hour. Mainly include wind speed, wind direction, temperature, relative humidity（specific humidity in 2020）, air pressure, downward short-wave radiation, downward long-wave radiation, precipitation.
MENG Xianhong, LI Zhaoguo
This data set is the conventional meteorological observation data of Maqu grassland observation site in the source region of the Yellow River from 2017 to 2020, obtained by using Kipp&Zonen CNR4, Vaisala HMP155A, PTB110 and other instruments, with a time resolution of half an hour. Mainly include wind speed, wind direction, temperature, relative humidity, air pressure, downward short-wave radiation, downward long-wave radiation, precipitation.
MENG Xianhong, LI Zhaoguo
Zoige Wetland observation point is located at Huahu wetland (102 ° 49 ′ 09 ″ E, 33 ° 55 ′ 09 ″ N) in Zoige County, Sichuan Province, with an initial altitude of 3435 m. The underlying surface is the alpine peat wetland, with well-developed vegetation, water and peat layer. This data set is the meteorological observation data of Zoige Wetland observation point from 2017 to 2019. It is obtained by using Kipp&Zonen CNR4, Vaisala HMP155A, PTB110 and other instruments. The time resolution is half an hour, mainly including wind speed, wind direction, air temperature, relative humidity, air pressure, downward short wave radiation, downward long wave radiation.
MENG Xianhong, LI Zhaoguo
As a powerful heat source, the Tibetan Plateau (TP) affects the onset, advance and retreat of the Asian monsoon, and the interaction between the westerly belt and the monsoon belt. In order to study the variation of TP thermal effect and its influence on the surrounding climate, the basic data related to TP heat source are needed. This data set is composed of monthly basic heat source data of the TP and its surrounding areas calculated from reanalysis data, and its horizontal range covers 40°E-180° and 20°S-80°N. The spatial resolution is 2.5 ° x2.5 °, and the datasets mainly included ERA5 and NCEP/NCAR reanalysis data.
LI Qingquan
1. Data content: air temperature, relative humidity, precipitation, air pressure, wind speed, average total radiation, total net radiation value and daily average water vapor pressure data. 2. Data source and processing method: Observed by American campel high-altitude automatic weather station, air temperature and humidity sensor model HMP155A; wind speed and wind direction model: 05103-45; net radiometer: CNR 4 Net Radiometer four component; atmospheric pressure sensor: CS106; Rain gauge: TE525MM. The automatic weather station automatically collects data every 10 minutes, and collects daily statistical data to obtain daily average weather data. 3. Data quality description: Data is automatically acquired continuously. 4. Data application results and prospects: The weather station is located in the middle of the glacier, and the meteorological data can provide data guarantee for simulating the response of oceanic glacier changes to global climate change in the context of future climate change.
LIU Jing
Solar global and direct radiation are measured by radiation sensors (Model TBQ-4-1, TBS-2, China), and temperature and humidity are measured by a HOBO weather station (Model H21, onset company, USA). This dataset is solar radiation and meteorological variables, including solar globla and direct radiation in the wavelength range of 270-3200nm, unit: w/m2. The units of temperature, humidity and water vapor pressure are ℃, %, hPa, respectively. The dataset of solar radiation and meteorological elements come from the measurements of data providers. Data coverage time is 2013-2016. The data set can be used to study the solar radiation and its change mechanism in a subtropical region, China.
BAI Jianhui
Clouds cover 70% of the earth's surface and are one of the important factors affecting the balance of atmospheric radiation and climate change. They are also an important part of the global water cycle. Considering the lack of reliable cloud parameter data with high temporal and spatial resolutions in the East Asia-Pacific (EAP) region, the 2016 data were developed using the next-generation geostationary satellite Himawari-8 with a temporal resolution of 1h and spatial resolutions of 0.1° and 0.25°. , 1° cloud parameters datasets. The cloud products include macro- and micro parameters. The macro parameters include: cloud cover (CF), cloud detection (CM), cloud phase detection (CP), cloud top pressure (CTP), cloud top height (CTH) ), cloud top temperature (CTT), cloud type (CT), supercooled water detection (SWC); micro parameters include cloud optical depth (COT), cloud particle effective radius (CER). These cloud parameters produced have reached the international advanced level in terms of precision.
HUSI Letu
The reconstruction of sunshine hours can better reflect the long-term change trend of surface solar radiation, but only the station data. Therefore, in order to obtain high-resolution grid point data and ensure its accuracy in long-term changes, it is necessary to fuse a variety of surface solar radiation related data. Using the geographic weighted regression (GWR) method, the MODIS 0.1 ° resolution cloud and aerosol retrieval and the surface sunshine hours are combined to reconstruct the surface solar radiation station data. By adding the combination judgment of adjacent point schemes, the accuracy of downscaling results of geographical weighted regression is effectively improved, and the multi-year average value and long-term trend of China are basically consistent with the observation and satellite remote sensing inversion results. Using geographic weighted regression and other methods, the surface wind speed and relative humidity data of 0.1 degree grid are generated; The improved Penman formula is used to calculate the land surface evapotranspiration data.
WANG Kaicun
This data set includes daily values of temperature, pressure, relative humidity, wind speed, wind direction, precipitation, radiation, water vapour pressure and other elements obtained from the Integrated Observation and Research Station of the Westerly Environment in Muztagh Ata from 18 May 2003 to 31 December 2016. The data are obtained by an automatic meteorological station (Vaisala) that recorded one measurement every 30 minutes. The data set was processed as a continuous time series after the original data were quality controlled. This data set satisfies the accuracy requirements of the meteorological observations of the National Weather Service and the World Meteorological Organization (WMO), and the systematic errors caused by the tracking data and sensor failure have been eliminated. The data set has mainly been applied in the fields of glaciology, climatology, environmental change research, cold zone hydrological process research and frozen soil science. Furthermore, this data set is mainly used by professionals engaged in scientific research and training in atmospheric physics, atmospheric environment, climate, glaciers, frozen soil and other disciplines.
WANG Yuanwei, XU Baiqing
As a key component of the earth's energy balance system, surface longwave downward radiation (LWDR) is of great significance to the study of ecology and climate change. With the continuous improvement of remote sensing estimation accuracy and spatial-temporal resolution and accuracy of reanalysis data, remote sensing and reanalysis data fusion will be a new way to further improve the reliability and spatial-temporal continuity of key parameters such as surface radiation. Considering the difference in spatial-temporal resolution and local regional accuracy of current multi-source LWDR data, the study combines the measured data of stations around the world, spatio-temporal fusion of remote sensing observation data (CERES) with reanalysis data ERA5 and GLDAS, and develops a high-precision surface longwave downward radiation dataset covering the world from 2000 to 2020 with a spatial-temporal resolution of 1h/0.25 °. The correlation coefficient (R), mean deviation error (bias) and root mean square error (RMSE) of the newly developed dataset and the site measured data verified on the land surface are 0.97, -0.95 Wm-2 and 22.38 Wm-2, respectively; On the ocean surface, it is 0.99, -0.88 Wm-2 and 10.96 Wm-2, respectively. In particular, compared with the existing data, the new dataset shows better accuracy and stability in the middle and low latitudes and complex terrain areas.
WANG Tianxing, WANG Shiyao
This dataset contains the flux measurements from the Qinghai Lake eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from January 1 to December 31 in 2021. The site (100° 29' 59.726'' E, 36° 35' 27.337'' N) was located on the Yulei Platform in Erlangjian scenic area, Qinghai Province. The elevation is 3209m. The EC was installed at a height of 16.1m, 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 (Gill&Li7500A) was about 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. The released data contained the following variables: DATE/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). The quality marks of sensible heat flux, latent heat flux and carbon flux are divided into three levels (quality marks 0 have good data quality, 1 have good data quality and 2 have poor data quality). 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.
Li Xiaoyan
This dataset contains the flux measurements from the Alpine meadow and grassland ecosystem Superstation superstation eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from January 1 to October 31 in 2021. The site (98°35′41.62″E, 37°42′11.47″N) was located in the alpine meadow and alpine grassland ecosystem, near the SuGe Road in Tianjun County, Qinghai Province. The elevation is 3718m. 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 (CSAT3A &EC150) was about 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. Data during December 18 to December 24, 2018 were missing due to the data collector failure. The released data contained the following variables: DATE/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). The quality marks of sensible heat flux, latent heat flux and carbon flux are divided into three levels (quality marks 0 have good data quality, 1 have good data quality and 2 have poor data quality). 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.
Li Xiaoyan
This dataset contains the flux measurements from the Subalpine shrub eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from January 1 to October 13 in 2021. The site (100°6'3.62"E, 37°31'15.67"N) was located near Dasi, Shaliuhe Town, Gangcha County, Qinghai Province. Data missing due to instrument failure. The elevation is 3495m. The EC was installed at a height of 2.5m, 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 (Gill&Li7500A) was about 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. The released data contained the following variables: DATE/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). The quality marks of sensible heat flux, latent heat flux and carbon flux are divided into three levels (quality marks 0 have good data quality, 1 have good data quality and 2 have poor data quality). 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.
Li Xiaoyan
This dataset contains the flux measurements from the temperate steppe eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from January 1 to October 14 in 2021. The site (100°14'8.99"E, 37°14'49.00"N) was located in Sanjiaocheng sheep breeding farm, Gangcha County, Qinghai Province. The elevation is 3210sm. The EC was installed at a height of 2.5 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 (CSAT3A &EC150) was about 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. Data during December 18 to December 24, 2018 were missing due to the data collector failure. The released data contained the following variables: DATE/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). The quality marks of sensible heat flux, latent heat flux and carbon flux are divided into three levels (quality marks 0 have good data quality, 1 have good data quality and 2 have poor data quality). 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.
Li Xiaoyan
1) Data content: database file of Central Asia Great Lakes region, including observation data of total radiation elements in basic ecological stations of Central Asia Great Lakes region from 2020 to 2021. 2) Data source and processing method: the data are from the observation data of 8 ecological stations (station numbers: 1130, 1131, 1132, 1133, 1134, 1135, 1137, 1138) without processing. 3) Data quality description: this data is site data, and the time resolution is every 1 minute. The data quality control process includes two steps (2) internal consistency check; (2) Time consistency check. 4) Data application achievements and prospects: this data is the basic observation data, which is an important part of the database of the Great Lakes region in Central Asia. It can provide data support for subsequent research fields such as meteorology, ecology, hydrology and environment, and support the development of project research.
LIU Tie
1) Data content: the 2020 updated database file of the Central Asia Great Lakes region database, which contains the observation data of the total radiation in the ecological stations of the Central Asia Great Lakes region in 2020. 2) Data source and processing method: the data are from the observation data of 6 ecological stations (station numbers: 1130, 1131, 1132, 1133, 1134, 1137) without processing. 3) Data quality description: this data is site data with a time resolution of 1 minute. The data quality control process includes two steps (1) internal consistency check; (2) Time consistency check. 4) Data application achievements and prospects: this data is the basic observation data, which is an important annual supplement to the database of the Great Lakes region of Central Asia, and can provide data support for subsequent research fields such as meteorology, ecology, hydrology and environment, and support the development of project research.
LIU Tie
The near surface atmospheric forcing and surface state dataset of the Tibetan Plateau was yielded by WRF model, time range: 2000-2010, space range: 25-40 °N, 75-105 °E, time resolution: hourly, space resolution: 10 km, grid number: 150 * 300. There are 33 variables in total, including 11 near surface atmospheric variables: temperature at 2m height on the ground, specific humidity at 2m height on the ground, surface pressure, latitudinal component of 10m wind field on the ground, longitudinal component of 10m wind field on the ground, proportion of solid precipitation, cumulative cumulus convective precipitation, cumulative grid precipitation, downward shortwave radiation flux at the surface, downward length at the surface Wave radiation flux, cumulative potential evaporation. There are 19 surface state variables: soil temperature in each layer, soil moisture in each layer, liquid water content in each layer, heat flux of snow phase change, soil bottom temperature, surface runoff, underground runoff, vegetation proportion, surface heat flux, snow water equivalent, actual snow thickness, snow density, water in the canopy, surface temperature, albedo, background albedo, lower boundary Soil temperature, upward heat flux (sensible heat flux) at the surface and upward water flux (sensible heat flux) at the surface. There are three other variables: longitude, latitude and planetary boundary layer height.
PAN Xiaoduo
This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Guazhou Station from January 1 to December 31, 2021. The site (95.673E, 41.405N) was located on a desert in the Liuyuan Guazhou, which is near Jiuquan city, Gansu Province. The elevation is 2014 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (2, 4, 8, 16, 32, and 48 m, towards north), wind speed and direction profile (windsonic; 2, 4, 8, 16, 32, and 48 m, towards north), air pressure (1.5 m), rain gauge (4 m), infrared temperature sensors (4 m, towards south, vertically downward), photosynthetically active radiation (4 m, towards south), soil heat flux (-0.05 m and -0.1m in south of tower), soil temperature/ moisture/ electrical conductivity profile -0.05, -0.1m, -0.2m, -0.4m, -0.6m and -0.8m in south of tower), four-component radiometer (4 m, towards south), sunshine duration sensor(4 m, towards south). The observations included the following: air temperature and humidity (Ta_1_2_1, Ta_1_4_1, Ta_1_8_1, Ta_1_16_1, Ta_1_32_1 and Ta_1_48_1; RH_2 m, RH_1_2_1, RH_1_4_1, RH_1_8_1, RH_1_16_1, RH_1_32_1, and RH_1_48_1) (℃ and %, respectively), wind speed (WS_1_2_1, WS_1_4_1, WS_1_8_1, WS_1_16_1, WS_1_32_1 and WS_1_48_1) (m/s), wind direction (WD_1_2_1, WD_1_4_1, WD_1_8_1, WD_1_16_1, WD_1_32_1 and WD_1_48_1) (°), air pressure (PA_1_1_1) (hpa), precipitation (P_1_4_1) (mm), four-component radiation (SWIN_1_4_1, incoming shortwave radiation; SWOUT_1_4_1, outgoing shortwave radiation; LWIN_1_4_1, incoming longwave radiation; LWOUT_1_4_1, outgoing longwave radiation; RN_1_4_1, net radiation) (W/m^2), infrared temperature (TC_1_4_1) (℃), photosynthetically active radiation (PPFD_1_4_1) (μmol/ (s m^2)), soil heat flux (SHF_1_5_1, SHF_1_10_1) (W/m^2), soil temperature (TS_1_5_1, TS_1_10_1, TS_1_20_1, TS_1_40_1, TS_1_60_1 and TS_1_80_1) (℃), soil moisture (SWC_1_5_1, SWC_1_10_1, SWC_1_20_1, SWC_1_40_1, SWC_1_60_1 and SWC_1_80_1) (%, volumetric water content),soil water potential (SWP_1_5_1, SWP_1_10_1, SWP_1_20_1, SWP_1_40_1, SWP_1_60_1 and SWP_1_80_1)(kpa), soil conductivity (EC_1_5_1, EC_1_10_1, EC_1_20_1, EC_1_40_1, EC_1_60_1 and EC_1_80_1)(μs/cm), Sun_time_1_4_1 (h). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. Missing or abnormal data is replaced by – 6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2021-6-10 10:30.
ZHAO Changming, ZHANG Renyi
This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Dunhuang Station from January 1 to December 31, 2021. The site (93.709° E, 40.348° N) was located on a wetland in the Dunhuang west lake, Gansu Province. The elevation is 994 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (4m and 8 m, towards north), wind speed and direction profile (windsonic; 4m and 8 m, towards north), air pressure (1 m), rain gauge (4 m), infrared temperature sensors (4 m, towards south, vertically downward), soil heat flux (-0.05 and -0.1m ), soil temperature/ moisture/ electrical conductivity profile (below the vegetation in the south of tower, -0.05 and -0.2 m), photosynthetically active radiation (4 m, towards south), four-component radiometer (4 m, towards south), sunshine duration sensor(4 m, towards south). The observations included the following: air temperature and humidity (Ta_1_4_1, Ta_1_8_1; RH_1_4_1, RH_1_8_1) (℃ and %, respectively), wind speed (WS_1_4_1, WS_1_8_1) (m/s), wind direction (WD_1_4_1, WD_1_8_1) (°), air pressure (PA_1_1_1) (hpa), precipitation (P_1_4_1) (mm), four-component radiation (SWIN_1_4_1, incoming shortwave radiation; SWOUT_1_4_1, outgoing shortwave radiation; LWIN_1_4_1, incoming longwave radiation; LWOUT_1_4_1, outgoing longwave radiation; RN_1_4_1, net radiation) (W/m^2), infrared temperature (TC_1_4_1) (℃), photosynthetically active radiation (PPFD_1_4_1) (μmol/ (s m-2)), soil heat flux (SHF_1_5_1、SHF_1_10_1) (W/m^2), soil temperature (TS_1_5_1、TS_1_20_1) (℃), soil moisture (SWC_1_5_1、SWC_1_20_1) (%, volumetric water content), soil conductivity (SWC_1_5_1、SWC_1_20_1)(μs/cm), sun time(Sun_time_1_4_1). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. Missing or abnormal data is replaced by – 6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2021-6-10 10:30.
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Suganhu station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from January 1 to December 27 in 2021. The site (94.12E, 38.99N was located in a desert in Suganhu, which is in Gansu Province. The elevation is 2823 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.
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Xiyinghe station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from January 1 to December 27 in 2021. The site (101.853E, 37.561N) was located on a alpine meadow in the Menyuan, Qinghai Province. The elevation is 3639 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.
ZHAO Changming, ZHANG Renyi
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 January 1 to December 27 in 2021. 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.
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Guazhou station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from January 1 to December 27 in 2021. The site (95.673E, 41.405N) was located in a desert in Liuyuan Guazhou, which is near Jiuquan city in Gansu Province. The elevation is 2016 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. 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.
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Guazhou station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from January 1 to December 27 in 2021. The site (102.73E, 36.692N) was located in a desert in Liuyuan Guazhou, which is near Jiuquan city in Gansu Province. The elevation is 2903 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. 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.
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Sidalong station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from January 1 to Dec 19 in 2021. The site (99.926E, 38.428N) was located on a forest in the Kangle Sunan, which is near Zhangye city, Gansu Province. The elevation is 3146 m. The EC was installed at a height of 4.0 m above the canopy , 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.
ZHAO Changming, ZHANG Renyi
This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Xiyinghe Station from January 1 to December 31, 2021. The site (101.853E, 37.561N) was located in Wuwei, Gansu Province. The elevation is 3614m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (2, 4, and 8 m, towards north), wind speed and direction profile (windsonic; 2, 4, and 8 m, towards north), air pressure (1.5 m), rain gauge (4 m), four-component radiometer (4 m, towards south), infrared temperature sensors (4 m, towards south, vertically downward), photosynthetically active radiation (4 m, towards south), soil heat flux (-0.05 m and -0.1m in south of tower), soil temperature/ moisture/ electrical conductivity profile (-0.05, -0.2 and -0.4 m in south of tower), sunshine duration sensor (4 m, towards south). The observations included the following: air temperature and humidity (Ta_1_2_1, Ta_1_4_1, and Ta_1_8_1; RH_1_2_1, RH_1_4_1and RH_1_8_1) (℃ and %, respectively), wind speed (WS_1_2_1, WS_1_4_1 and WS_1_8_1) (m/s), wind direction (WD_1_2_1, WD_1_4_1 and WD_1_8_1) (°), air pressure (PA_1_1_1) (hpa), precipitation (P_1_4_1) (mm), four-component radiation (SWIN_1_4_1, incoming shortwave radiation; SWOUT_1_4_1, outgoing shortwave radiation; LWIN_1_4_1, incoming longwave radiation; LWOUT_1_4_1 outgoing longwave radiation; Rn_1_4_1, net radiation) (W/m^2), infrared temperature (TC_1_4_1) (℃), photosynthetically active radiation (PPFD_1_4_1) (μmol/ (s/m^2)), soil heat flux (SHF_1_5_1, SHF_1_10_1) (W/m^2), soil temperature (TS_1_5_1, TS_1_20_1 and TS_1_40_1) (℃), soil moisture (SWC_1_5_1, SWC_1_20_1 and SWC_1_40_1) (%, volumetric water content), soil water potential (SWP_1_5_1, SWP_1_20_1 and SWP_1_40_1)(kpa) , soil conductivity (EC_1_5_1, EC_1_20_1 and EC_1_40_1)(μs/cm), Sun_time_1_4_1 (h). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. Missing or abnormal data is replaced by – 6999. The air pressure data were rejected because of program error; (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2021-6-10 10:30.
ZHAO Changming, ZHANG Renyi
This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Suganhu Station from January 1 to December 31, 2021. The site (94.125° E, 38.992° N) was located on a wetland in the Suganhu west lake, Gansu Province. The elevation is 2823 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (4m and 8m, towards north), wind speed and direction profile (windsonic; 4m and 8m, towards north), air pressure (1m), rain gauge (4m), infrared temperature sensors (4 m, towards south, vertically downward), soil heat flux (-0.05 and -0.1m ), soil temperature/ moisture/ electrical conductivity profile (below the vegetation in the south of tower, -0.1, -0.2 and -0.4m), photosynthetically active radiation (4 m, towards south), four-component radiometer (4 m, towards south), sunshine duration sensor(4 m, towards south). The observations included the following: air temperature and humidity (Ta_1_4_1, Ta_1_8_1; RH_1_4_1, RH_1_8_1) (℃ and %, respectively), wind speed (WS_1_4_1, WS_1_8_1) (m/s), wind direction (WD_1_4_1, WD_1_8_1) (°), air pressure (PA_1_1_1) (hpa), precipitation (P_1_4_1) (mm), four-component radiation (SWIN_1_4_1, incoming shortwave radiation; SWOUT_1_4_1, outgoing shortwave radiation; LWIN_1_4_1, incoming longwave radiation; LWOUT_1_4_1 outgoing longwave radiation; RN_1_4_1, net radiation) (W/m^2), infrared temperature (TC_1_4_1) (℃), photosynthetically active radiation (PPFD_1_4_1) (μmol/ (s m-2)), soil heat flux (SHF_1_5_1, SHF_1_10_1) (W/m^2), soil temperature (TS_1_10_1, TS_1_20_1, TS_1_40_1) (℃), soil moisture (SWC_1_10_1, SWC_1_20_1, SWC_1_40_1) (%, volumetric water content), soil conductivity (EC_1_10_1, EC_1_20_1, EC_1_40_1)(μs/cm), Sun_time_1_4_1 (h). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. Missing or abnormal data is replaced by – 6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2021-6-10 10:30.
ZHAO Changming, ZHANG Renyi
This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Sidalong Station from January 1 to December 31, 2021. The site (99.926°E, 38.428°N) was located on a forest in the Kangle Sunan, which is near Zhangye city, Gansu Province. The elevation is 3146 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (1, 2, 13, 24, and 48 m), wind speed and direction profile (windsonic; 1, 2, 13, 24, and 48 m), air pressure (1.5 m), rain gauge (24 m), infrared temperature sensors (4 m and 30m, vertically downward), photosynthetically active radiation (4 m and 30m), soil heat flux (-0.05 m and -0.1m), soil temperature/ moisture/ electrical conductivity profile -0.05, -0.1m, -0.2m, -0.4m and -0.6mr), four-component radiometer (30 m, towards south), sunshine duration sensor(30 m, towards south). The observations included the following: air temperature and humidity (Ta_1_1_1, Ta_1_2_1, Ta_1_13_1, Ta_1_24_1 and Ta_1_48_1; RH_1_1_1, RH_1_2_1, RH_1_13_1, RH_1_24_1 and RH_1_48_1) (℃ and %, respectively), wind speed (WS_1_1_1, WS_1_2_1, WS_1_13_1, WS_1_24_1, and WS_1_48_1) (m/s), wind direction (WD_1_1_1, WD_1_2_1, WD_1_13_1, WD_1_24_1, and WD_1_48_1) (°), air pressure (PA_1_1_1) (hpa), precipitation (P_1_24_1) (mm), four-component radiation (SWIN_1_30_1, incoming shortwave radiation; SWOUT_1_30_1, outgoing shortwave radiation; LWIN_1_30_1, incoming longwave radiation; LWOUT_1_30_1, outgoing longwave radiation; RN_1_30_1, net radiation) (W/m^2), infrared temperature (TC_1_4_1, TC_1_30_1) (℃), photosynthetically active radiation (PPFD_1_4_1, PPFD_1_30_1) (μmol/ (s m^2)), soil heat flux (SHF_1_5_1, SHF_1_10_1) (W/m^2), soil temperature (TS_1_5_1, TS_1_10_1, TS_1_20_1, TS_1_40_1 and TS_1_60_1) (℃), soil moisture (SWC_1_5_1, SWC_1_10_1, SWC_1_20_1, SWC_1_40_1 and SWC_1_60_1) (%, volumetric water content),soil water potential (SWP_1_5_1, SWP_1_10_1, SWP_1_20_1, SWP_1_40_1 and SWP_1_60_1)(kpa), soil conductivity (EC_1_5_1, EC_1_10_1, EC_1_20_1, EC_1_40_1 and EC_1_60_1)(μs/cm), Sun_time_1_30_1 (h). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. Missing or abnormal data is replaced by – 6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2021-6-10 10:30.
ZHAO Changming, ZHANG Renyi
This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Minqin Station from January 1 to December 31, 2021. The site (103.668E, 39.208N) was located in Minqin, Gansu Province. The elevation is 1020 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (4 and 8 m, towards north), wind speed and direction profile (windsonic; 4, and 8 m, towards north), air pressure (1.5 m), rain gauge (4 m), four-component radiometer (4 m, towards south), infrared temperature sensors (4 m, towards south, vertically downward), photosynthetically active radiation (4 m, towards south), soil heat flux (-0.05 m and -0.1m in south of tower), soil temperature/ moisture/ electrical conductivity profile (-0.1 and -0.2 m in south of tower), sunshine duration sensor (4 m, towards south). The observations included the following: air temperature and humidity (Ta_1_4_1, Ta_1_8_1; RH_1_4_1, RH_1_8_1) (℃ and %, respectively), wind speed (WS_1_4_1, WS_1_8_1) (m/s), wind direction (WD_1_4_1, WD_1_8_1) (°), air pressure (PA_1_1_1) (hpa), precipitation (P_1_4_1) (mm), four-component radiation (SWIN_1_4_1, incoming shortwave radiation; SWOUT_1_4_1, outgoing shortwave radiation; LWIN_1_4_1, incoming longwave radiation; LWOUT_1_4_1, outgoing longwave radiation; Rn_1_4_1, net radiation) (W/m^2), infrared temperature (TC_1_4_1) (℃), photosynthetically active radiation (PPFD_1_4_1) (μmol/ (s/m^2)), soil heat flux (SHF_1_5_1, SHF_1_10_1) (W/m^2), soil temperature (TS_1_10_1, TS_1_20_1) (℃), soil moisture (SWC_1_10_1, SWC_1_10_1) (%, volumetric water content), soil water potential (SWP_1_10_1 , SWP_1_20_1)(kpa) , soil conductivity (EC_1_10_1, EC_1_20_1) (μs/cm), Sun_time_1_4_1 (h). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. Missing or abnormal data is replaced by – 6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2021-6-10 10:30.
ZHAO Changming, ZHANG Renyi
This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Linze Station from January 1 to December 31, 2021. The site (100.062° E, 39.238° N) was located on a cropland (maize surface) in the Guzhai Xinghua, which is near Zhangye city, Gansu Province. The elevation is 1402 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (4 and 8 m, towards north), wind speed and direction profile (windsonic; 4 and 8 m, towards north), air pressure (1 m), rain gauge (4 m), four-component radiometer (4 m, towards south), infrared temperature sensors (4 m, towards south, vertically downward), photosynthetically active radiation (4 m, towards south), soil heat flux (2 duplicates below the vegetation; -0.05 and -0.1m in south of tower), soil temperature/ moisture/ electrical conductivity profile (-0.05 and -0.2m), sunshine duration sensor (4 m, towards south). The observations included the following: air temperature and humidity (Ta_1_4_1, Ta_1_8_1; RH_1_4_1, RH_1_8_1) (℃ and %, respectively), wind speed (WS_1_4_1, WS_1_8_1) (m/s), wind direction (WS_1_4_1, WS_1_8_1) (°), air pressure (PA_1_1_1) (hpa), precipitation (P_1_4_1) (mm), four-component radiation (SWIN_1_4_1, incoming shortwave radiation; SWOUT_1_4_1, outgoing shortwave radiation; LWIN_1_4_1, incoming longwave radiation; LWOUT_1_4_1 outgoing long wave radiation; RN_1_4_1, net radiation) (W/m^2), infrared temperature (TC_1_4_1) (℃), photosynthetically active radiation (PPFD_1_4_1) (μmol/ (s m-2)), soil heat flux (SHF_1_5_1, SHF_1_10_1) (W/m^2), soil temperature (TS_1_5_1, TS_1_20_1) (℃), soil moisture (SWC_1_5_1, SWC_1_20_1) (%, volumetric water content), soil water potential(SWP_1_5_1, SWP_1_20_1), soil conductivity (EC_1_5_1, EC_1_20_1) (μs/cm), Sun_time_1_4_1 (h). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. Missing or abnormal data is replaced by – 6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2021-10 10:30.
ZHAO Changming, ZHANG Renyi
This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Liancheng Station from January 4 to December 31, 2021. The site (102.737E, 36.692N) was located on a forest in the Tulugou national forest park, which is near Liancheng city, Gansu Province. The elevation is 2903 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (4 and 8 m, towards north), wind speed and direction profile (windsonic; 4 and 8 m, towards north), air pressure (1.5 m), rain gauge (2 m), four-component radiometer (4m, towards south), infrared temperature sensors (4m, towards south, vertically downward), photosynthetically active radiation (4m, towards south), soil heat flux (2 duplicates below the vegetation; -0.05 and -0.1m in south of tower), soil temperature/ moisture/ electrical conductivity profile (below the vegetation;-0.05 and -0.1m in south of tower), sunshine duration sensor(4 m, towards south). The observations included the following: air temperature and humidity (Ta_1_4_1 and Ta_1_8_1; RH_1_4_1 and RH_1_8_1) (℃ and %, respectively), wind speed (WS_1_4_1 and WS_1_8_1) (m/s), wind direction (WD_1_4_1 and WD_1_8_1) (°), air pressure (PA_1_1_1) (hpa), precipitation (P_1_4_1) (mm), four-component radiation (SWIN_1_4_1, incoming shortwave radiation; SWOUT_1_4_1, outgoing shortwave radiation; LWIN_1_4_1, incoming longwave radiation; LWOUT_1_4_1, outgoing longwave radiation; Rn_1_4_1, net radiation) (W/m^2), infrared temperature (TC_1_4_1) (℃), photosynthetically active radiation (PPFD_1_1_1) (μmol/ (s m-2)), soil heat flux (SHF_1_5_1, SHF_1_10_1) (W/m^2), soil temperature (TS_1_5_1, TS_1_10_1) (℃), soil moisture (SWC_1_5_1, SWC_1_10_1) (%, volumetric water content), soil water potential (SWP_1_5_1, SWP_1_10_1)(kpa), soil conductivity (EC_1_5_1, EC_1_10_1)(μs/cm), Sun_time_1_4_1 (h). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. Missing or abnormal data is replaced by – 6999. 2021.6.13-3021.9.8, the data is missing because the wire is bitten off. 8m wind speed and direction sensor failure; 5 and 10cm soil temperature/ moisture/ electrical conductivity sensor failure; 5 and 10cm soil water potential sensor failure; 4m infrared temperature sensor failure. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2021-8-20 10:30.
ZHAO Changming, ZHANG Renyi
This dataset includes data recorded by Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Dayekou Station from January 1 to December 31, 2021. The site (100.286° E, 38.556° N) was located on a glassland in the Dayekou, which is near Zhangye city, Gansu Province. The elevation is 2694 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (8 m), air pressure (2 m), rain gauge (2 m), infrared temperature sensors (2 m, towards south, vertically downward), soil heat flux (below the vegetation, -0.05 m; towards south), soil temperature/moisture/electrical conductivity profile (-0.05m) photosynthetically active radiation (2 m, towards south), four-component radiometer (2 m, towards south), sunshine duration sensor(2 m, towards south). The observations included the following: air temperature and humidity (Ta_1_8_1; RH_1_8_1) (℃ and %, respectively), wind speed (WS_1_8_1) (m/s), wind direction (WD_1_8_1) (°), air pressure (PA_1_1_1) (hpa), precipitation (P_1_4_1) (mm), four-component radiation (SWIN_1_4_1, incoming shortwave radiation; SWOUT_1_4_1, outgoing shortwave radiation; LWIN_1_4_1, incoming longwave radiation; LWOUT_1_4_1, outgoing longwave radiation; Rn, net radiation) (W/m^2), infrared temperature (℃), photosynthetically active radiation (PPFD_1_4_1) (μmol/ (s m^2)), soil heat flux (SHF_1_5_1) (W/m^2), soil temperature (TS_1_20_1)(℃), soil moisture (SWC_1_20_1)(%, volumetric water content), soil water potential (SWP_1_20_1)(kpa), soil conductivity (EC_1_20_1)(μs/cm). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. Missing or abnormal data is replaced by – 6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2021-6-10 10:30.
ZHAO Changming, ZHANG Renyi
Photosynthetically active radiation (PAR) is fundamental physiological variable driving the process of material and energy exchange, and is indispensable for researches in ecological and agricultural fields. In this study, we produced a 35-year (1984-2018) high-resolution (3 h, 10 km) global grided PAR dataset with an effective physical-based PAR model. The main inputs were cloud optical depth from the latest International Satellite Cloud Climatology Project (ISCCP) H-series cloud products, the routine variables (water vapor, surface pressure and ozone) from the ERA5 reanalysis data, aerosol from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) products and albedo from Moderate Resolution Imaging Spectroradiometer (MODIS) product after 2000 and CLARRA-2 product before 2000. The grided PAR products were evaluated against surface observations measured at seven experimental stations of the SURFace RADiation budget network (SURFRAD), 42 experimental stations of the National Ecological Observatory Network (NEON), and 38 experimental stations of the Chinese Ecosystem Research Network (CERN). The instantaneous PAR was validated at the SURFRAD and NEON, and the mean bias errors (MBEs) and root mean square errors (RMSEs) are 5.6 W m-2 and 44.3 W m-2, and 5.9 W m-2 and 45.5 W m-2, respectively, and correlation coefficients (R) are both 0.94 at 10 km scale. When averaged to 30 km, the errors were obviously reduced with RMSEs decreasing to 36.3 W m-2 and 36.3 W m-2 and R both increasing to 0.96. The daily PAR was validated at the SURFRAD, NEON and CERN, and the RMSEs were 13.2 W m-2, 13.1 W m-2 and 19.6 W m-2, respectively at 10 km scale. The RMSEs were slightly reduced to 11.2 W m-2, 11.6 W m-2, and 18.6 W m-2 when upscaled to 30 km. Comparison with the other well-known global satellite-based PAR product of the Earth's Radiant Energy System (CERES) reveals that our PAR product was a more accurate dataset with higher resolution than the CRERS. Our grided PAR dataset would contribute to the ecological simulation and food yield assessment in the future.
TANG Wenjun
The temporal resolution of temperature and radiation data in Central Asia is monthly scale, and the spatial resolution is 0.5 degree and 0.05 degree, respectively. The GCS_WGS_1984 projection coordinate system was used. Among them, the downward short wave radiation, air temperature and vapor pressure data of GLDAS, surface temperature / emissivity data of MOD11C3, surface albedo data of MCD43C3 and ASTER_GEDv4.1 are used for radiation data calculation; the temperature data was calculated by MOD06_ L2 cloud products and MOD07_ L2 atmospheric profile data was calculated. This data is based on the advanced remote sensing algorithm and makes full use of the current high-precision remote sensing data and products, which is different from the traditional climate model for the estimation of climate elements. The data can be used to analyze the spatial and temporal variation characteristics of water resources in Central Asia, analyze the supply-demand relationship of agricultural water resources and evaluate the development potential of water resources.
SONG Jinxi, JIANG Xiaohui
1) The Qinghai Tibet plateau surface meteorological driving data set (2019-2020) includes four meteorological elements: land surface temperature, mean total precipitation rate, mean surface downward long wave radiation flux and mean surface downward short wave radiation flux. 2) The data set is based on era5 reanalysis data, supplemented by MODIS NDVI, MODIS DEM and fy3d mwri DEM data products. The era5 reanalysis data were downscaled by multiple linear regression method, and finally generated by resampling. 3) All data elements of the Qinghai Tibet plateau surface meteorological driving data set (2019-2020) are stored in TIFF format. The time resolution includes (daily, monthly and annual), and the spatial resolution is unified as 0.1 ° × 0.1°。 4) This data is convenient for researchers and students who will not use such assimilated data in. NC format. Based on the long-term observation data of field stations of the alpine network and overseas stations in the pan third pole region, a series of data sets of meteorological, hydrological and ecological elements in the pan third pole region are established; Complete the inversion of meteorological elements, lake water quantity and quality, aboveground vegetation biomass, glacier and frozen soil change and other data products through intensive observation in key areas and verification of sample plots and sample points; Based on the Internet of things technology, a multi station networked meteorological, hydrological and ecological data management platform is developed to realize real-time acquisition, remote control and sharing of networked data.
ZHU Liping, DU Baolong
Surface solar irradiance (SSI) is one of the products of FY-4A L2 quantitative inversion. It covers a full disk without projection, with a spatial resolution of 4km and a temporal resolution of 15min (there are 40 observation times in the whole day since 20180921, except for the observation of each hour, there is one observation every 3hr before and after the hour）, and the spectral range is 0.2µ m～5.0 µ m. The output elements of the product include total irradiance, direct irradiance on horizontal plane and scattered irradiance, the effective measurement ranges between 0-1500 w / m2. The qualitative improvement of FY-4A SSI products in coverage, spatial resolution, time continuity, output elements and other aspects makes it possible to further carry out its fine application in solar energy, agriculture, ecology, transportation and other professional meteorological services. The current research results show that the overall correlation of FY-4A SSI product in China is more than 0.75 compared with ground-based observation, which can be used for solar energy resource assessment in China.
SHEN Yanbo, HU Yueming, HU Xiuqing
As an important part of global semi-arid grassland, adequately understanding the spatio-temporal variability of evapotranspiration (ET) over the temperate semi-arid grassland of China (TSGC) could advance our understanding of climate, hydrological and ecological processes over global semi-arid areas. Based on the largest number of in-situ ET measurements (13 flux towers) within the TSGC, we applied the support vector regression method to develop a high-quality ET dataset at 1 km spatial resolution and 8-day timescale for the TSGC from 1982 to 2015. The model performed well in validation against flux tower‐measured data and comparison with water-balance derived ET.
LEI Huimin
The data set collected long-term monitoring projects from multiple stations for atmosphere, hydrology and soil in the North Tibetan Plateau. The data set consisted of monitoring data obtained from the automatic weather station (AWS) and the atmospheric boundary layer tower (PBL) in the field. The sensors for temperature, humidity and pressure were provided by Vaisala of Finland; the sensors for wind speed and direction were provided by Met One of America, the radiation sensors were provided by APPLEY of America and EKO of Japan; the gas analyzers were provided by Licor of America; the soil water content instrument, ultrasonic anemometers and data collectors were provided by CAMPBELL of America. The observation system was maintained by professionals regularly (2-3 times a year), the sensors were calibrated and replaced, and the collected data were downloaded and reorganized. The data set was processed by forming a time continuous sequence after the raw data were quality-controlled. It met the accuracy level of the original meteorological observation data of the National Weather Service and the World Meteorological Organization (WMO). The quality control included the elimination of the missing data and the systematic error caused by the failure of the sensor.
HU Zeyong
Photosynthetic effective radiation absorption coefficient photosynthetically active radiation component is an important biophysical parameter. It is an important land characteristic parameter of ecosystem function model, crop growth model, net primary productivity model, atmosphere model, biogeochemical model and ecological model, and is an ideal parameter for estimating vegetation biomass. The data set contains the data of photosynthetically active radiation absorption coefficient in Qinghai Tibet Plateau, with spatial resolution of 500m, temporal resolution of 8D, and time coverage of 2000, 2005, 2010 and 2015. The data source is MODIS Lai / FPAR product data mod15a2h (C6) on NASA website. The data are of great significance to the analysis of vegetation ecological environment in the Qinghai Tibet Plateau.
FANG Huajun, Ranga Myneni
This data set includes meteorological data observed by the carbon flux station in the Guoluo Army Ranch in Qinghai. The temporal coverage is from 2005 to 2009, and the temporal resolution is 1 day. Meteorological and carbon flux data observation methods: vorticity-related observation instruments were used for automatic recording; biomass observation method: harvest method, weighing in a 60-degree oven for 48 hours. Both carbon flux and meteorological data were automatically recorded by the instruments and manually checked. During the data observation process, the operation of the instrument and the selection of the observation objects were in strict accordance with professional requirements, and the data could be applied to plant leaf photosynthetic parameter simulation and productivity estimation. This data contains observation items as follows: Temperature °C Precipitation mm Wind speed m/s Soil temperature at 5 cm depth °C Photosynthetically active radiation µmol/m²s Total radiation W/m²
ZHAO Xinquan
This data set includes the monthly average actual evapotranspiration of the Tibet Plateau from 2001 to 2018. The data set is based on the satellite remote sensing data (MODIS) and reanalysis meteorological data (CMFD), and is calculated by the surface energy balance system model (SEBS). In the process of calculating the turbulent flux, the sub-grid scale topography drag parameterization scheme is introduced to improve the simulation of sensible and latent heat fluxes. In addition, the evapotranspiration of the model is verified by the observation data of six turbulence flux stations on the Tibetan Plateau, which shows high accuracy. The data set can be used to study the characteristics of land-atmosphere interaction and the water cycle in the Tibetan Plateau.
HAN Cunbo, MA Yaoming, WANG Binbin, ZHONG Lei, MA Weiqiang*, CHEN Xuelong, SU Zhongbo
This data set is a national high-resolution solar radiation data set covering 34 years (1983.7-2017.6), with a resolution of 10 km. The data unit is W / m2. The data set is developed by merging the global high-resolution (3 hours, 10 km) surface solar radiation data set (1983-2017) with isccp-hxg cloud products as the main input, with ground based sunshine duration derived surface solar raidation data from 2261 meteorological stations in China by using the geographic weighted regression method. The validation results show that this dataset can provide more accurate simulation of long-term variability of surface solar radiation than that of gewex-srb, cmsaf-clara-a2 and the isccp-hxg based surface solar radiation product. This data can provide favorable data support for the application and research of long-term change of hydrology in land surface process simulation.
FENG Fei, WANG Kaicun
The dataset is a nearly 36-year (1983.7-2018.12) high-resolution (3 h, 10 km) global SSR (surface solar radiation) dataset, which can be used for hydrological modeling, land surface modeling and engineering application. The dataset was produced based on ISCCP-HXG cloud products, ERA5 reanalysis data, and MODIS aerosol and albedo products with an improved physical parameterization scheme. Validation and comparisons with other global satellite radiation products indicate that our SSR estimates were generally better than those of the ISCCP flux dataset (ISCCP-FD), the global energy and water cycle experiment surface radiation budget (GEWEX-SRB), and the Earth's Radiant Energy System (CERES). This SSR dataset will contribute to the land-surface process simulations and the photovoltaic applications in the future. The unit is W/㎡, instantaneous value.
TANG Wenjun
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.
Felix Nieberding, MA Yaoming, Cristian Wille, Gerardo Fratini, Magnus Ole Asmussen, Yuyang Wang*, MA Weiqiang*, Torsten Sachs
Terrestrial actual evapotranspiration (ETa) is an important component of terrestrial ecosystems because it links the hydrological, energy, and carbon cycles. However, accurately monitoring and understanding the spatial and temporal variability of ETa over the Tibetan Plateau (TP) remains very difficult. Here, the multiyear (2000-2018) monthly ETa on the TP was estimated using the MOD16-STM model supported by datasets of soil properties, meteorological conditions, and remote sensing. The estimated ETa correlates very well with measurements from 9 flux towers, with low root mean square errors (average RMSE = 13.48 mm/month) and mean bias (average MB = 2.85 mm/month), and strong correlation coefficients (R = 0.88) and the index of agreement values (IOA = 0.92). The spatially averaged ETa of the entire TP and the eastern TP (Lon > 90°E) increased significantly, at rates of 1.34 mm/year (p < 0.05) and 2.84 mm/year (p < 0.05) from 2000 to 2018, while no pronounced trend was detected on the western TP (Lon < 90°E). The spatial distribution of ETa and its components were heterogeneous, decreasing from the southeastern to northwestern TP. ETa showed a significantly increasing trend in the eastern TP, and a significant decreasing trend throughout the year in the southwestern TP, particularly in winter and spring. Soil evaporation (Es) accounted for more than 84% of ETa and the spatial distribution of temporal trends was similar to that of ETa over the TP. The amplitudes and rates of variations in ETa were greatest in spring and summer. The multi-year averaged annual terrestrial ETa (over an area of 2444.18×103 km2) was 376.91±13.13 mm/year, equivalent to a volume of 976.52±35.7 km3/year. The average annual evapotranspirated water volume over the whole TP (including all plateau lakes, with an area of 2539.49×103 km2) was about 1028.22±37.8 km3/year. This new estimated ETa dataset is useful for investigating the hydrological impacts of land cover change and will help with better management of watershed water resources across the TP.
MA Yaoming, CHEN Xuelong,
Central Asia (referred to as CA) is among the most vulnerable regions to climate change due to the fragile ecosystems, frequent natural hazards, strained water resources, and accelerated glacier melting, which underscores the need of high-resolution climate projection datasets for application to vulnerability, impacts, and adaption assessments. We applied three bias-corrected global climate models (GCMs) to conduct 9-km resolution dynamical downscaling in CA. A high-resolution climate projection dataset over CA (the HCPD-CA dataset) is derived from the downscaled results, which contains four static variables and ten meteorological elements that are widely used to drive ecological and hydrological models. The static variables are terrain height (HGT, m), land use category (LU_INDEX, 21 categories), land mask (LANDMASK, 1 for land and 0 for water), and soil category (ISLTYP, 16 categories). The meteorological elements are daily precipitation (PREC, mm/day), daily mean/maximum/minimum temperature at 2m (T2MEAN/T2MAX/T2MIN, K), daily mean relative humidity at 2m (RH2MEAN, %), daily mean eastward and northward wind at 10m (U10MEAN/V10MEAN, m/s), daily mean downward shortwave/longwave flux at surface (SWD/LWD, W/m2), and daily mean surface pressure (PSFC, Pa). The reference and future periods are 1986-2005 and 2031-2050, respectively. The carbon emission scenario is RCP4.5. The results show the data product has good quality in describing the climatology of all the elements in CA, which ensures the suitability of the dataset for future research. The main feature of projected climate changes in CA in the near-term future is strong warming (annual mean temperature increasing by 1.62-2.02℃) and significant increase in downward shortwave and longwave flux at surface, with minor changes in other elements. The HCPD-CA dataset presented here serves as a scientific basis for assessing the impacts of climate change over CA on many sectors, especially on ecological and hydrological systems.
QIU Yuan QIU Yuan
The Tibetan Plateau (TP), acting as a large elevated land surface and atmospheric heat source during spring and summer, has a substantial impact on regional and global weather and climate. To explore the multi-scale temporal variation in the thermal forcing effect of the TP，The data set of atmospheric heat source/sink in Tibetan Plateau was prepared as a quantitative analysis tool for calculating heat budget of gas column. the atmospheric heat source/sink dataset consists of three variables: surface sensible heat flux SH, latent heat release LH and net radiation flux RC. here we calculated the surface sensible heat and latent heat release based on 6-h routine observations at 80 (32) meteorological stations during the period 1979–2016：air temperature at 1.5 m and surface temperature and wind speed at 10 m are used to calculate surface sensible heat flux,the latent heat release is estimated precipitation data.The satellite datasets used to calculate the net radiation flux were the Global Energy and Water Cycle Experiment surface radiation budget satellite radiation(GEWEX/SRB) and Clouds and Earth’s Radiant Energy Systems/Energy Balanced And Filled (CERES/EBAF). The monthly shortwave and longwave radiation fluxes at the surface and at the top of the atmosphere (TOA) in GEWEX/SRB and CERES/EBAF were utilized to obtain the net radiation flux for the period 1984–2015 via statistical methods。
DUAN Anmin
This dataset contains the flux measurements from the Qinghai Lake eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from January 1 to December 31 in 2020. Due to the terrible climate in winter and spring, those instruments need maintenance in time. However, the Covid-19 blocked our maintenance, those data in January 1 to April 6 and November 1 to December 31 in 2020 were missing. The effective range of latent heat flux is -500~500 W/m2. The negative value may be caused by condensed water. The site (100° 29' 59.726'' E, 36° 35' 27.337'' N) was located on the Yulei Platform in Erlangjian scenic area, Qinghai Province. The elevation is 3209m. The EC was installed at a height of 16.1m, 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 (Gill&Li7500A) was about 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. The released data contained the following variables: DATE/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). The quality marks of sensible heat flux, latent heat flux and carbon flux are divided into three levels (quality marks 0 have good data quality, 1 have good data quality and 2 have poor data quality). 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.
Li Xiaoyan
This data set includes the daily averages of the temperature, pressure, relative humidity, wind speed, precipitation, global radiation, P2.5 concentration and other meteorological elements observed by the Qomolangma Station for Atmospheric and Environmental Observation and Research from 2005 to 2016. The data are aimed to provide service for students and researchers engaged in meteorological research on the Tibetan Plateau. The precipitation data are observed by artificial rainfall barrel, the evaporation data are observed by Φ20 mm evaporating pan, and all the others are daily averages and ten-day means obtained after half hour observational data are processed. All the data are observed and collected in strict accordance with the Equipment Operating Specifications, and some obvious error data are eliminated when processing the generated data.
MA Yaoming
This dataset includes the observed surface incident solar radiantion, and sunshine duration derived soalr radiation, and their homogenized series at 156 meteorological stations in Japan from 1870 to 2015. According to Yang's method, the surface solar radiation is calculated from the observed sunshine duration hours, and then the breakpoints of unnatural factors in the data series are adjusted by RH test homogenization method, so as to obtain the regional homogenized monthly solar radiation data set in Japan.
MA Qian, HE Yanyi, WANG Kaicun, SU Liangyuan
This meteorological data is the basic meteorological data of air temperature, relative humidity, wind speed, precipitation, air pressure, radiation, soil temperature and humidity observed in the observation site (86.56 ° e, 28.21 ° n, 4276m) of the comprehensive observation and research station of atmosphere and environment of Qomolangma, Chinese Academy of Sciences from 2019 to 2020. Precipitation is the daily cumulative value. All data are observed and collected in strict accordance with the instrument operation specifications, and some obvious error data are eliminated when processing and generating data The data can be used by students and scientific researchers engaged in meteorology, atmospheric environment or ecology (Note: when using, it must be indicated in the article that the data comes from Qomolangma station for atmospheric and environmental observation and research, Chinese Academy of Sciences (QOMS / CAS))
XI Zhenhua
Near surface atmospheric forcing data were produced by using Wether Research and Forecasting (WRF) model over the Heihe River Basin at hourly 0.05 * 0.05 DEG resolution, including the following variables: 2m temperature, surface pressure, water vapor mixing ratio, downward shortwave & upward longwave radiation, 10m wind field and the accumulated precipitation. The forcing data were validated by observational data collected by 15 daily Chinese Meteorological Bureau conventional automatic weather station (CMA), a few of Heihe River eco-hydrological process comprehensive remote sensing observation (WATER and HiWATER) site hourly observations were verified in different time scales, draws the following conclusion: 2m surface temperature, surface pressure and 2m relative humidity are more reliable, especially 2m surface temperature and surface pressure, the average errors are very small and the correlation coefficients are above 0.96; correlation between downward shortwave radiation and WATER site observation data is more than 0.9; The precipitation agreed well with observational data by being verified based on rain and snow precipitation two phases at yearly, monthly, daily time scales . the correlation coefficient between rainfall and the observation data at monthly and yearly time scales were up to 0.94 and 0.84; the correlation between snowfall and observation data at monthly scale reached 0.78, the spatial distribution of snowfall agreed well with the snow fractional coverage rate of MODIS remote sensing product. Verification of liquid and solid precipitation shows that WRF model can be used for downscaling analysis in complex and arid terrain of Heihe River Basin, and the simulated data can meet the requirements of watershed scale hydrological modeling and water resources balance. The data for 2000-2012 was provided in 2013. The data for 2013-2015 was updated in 2016. The data for 2016-2018 was updated in 2019. The data for 2019-2021 was updated in 2021.
PAN Xiaoduo
The data are fy-4a ground solar radiation products in Qinghai Tibet Plateau, including GHI \ DNI \ dif The channels involved in FY4 surface solar incident radiation inversion algorithm include six channels of imager visible light, near-infrared and short wave infrared: ch1 (0.45-0.49 μ m), CH2 (0.55-0.75 μ m), CH3 (0.75-0.90 μ m), CH4 (1.36-1.39 μ m), CH5 (1.58-1.64 μ m) and ch6 (2.1-2.35 μ m). The regression model relied on by the algorithm needs to be established through radiative transfer simulation and statistical analysis in advance. The regression model defines the regression relationship between the surface solar incident radiation and the multi-channel radiation observation of the imager, which is a function of the solar observation geometry and the most important influence parameters (cloud, aerosol, water vapor content, surface albedo, surface altitude, etc.). The algorithm uses the short wave radiation observation from channel 1 to channel 6 of FY-4 satellite imager to obtain the instantaneous state parameter information of atmosphere and surface, and obtains the surface altitude information from the surface elevation data. After determining the instantaneous atmospheric and surface states, combined with the solar angle and observation angle, according to the previously established regression model data, multi-dimensional linear interpolation is carried out to obtain the inversion products of surface solar incident radiation.
SHEN Yanbo, HU Yueming, HU Liqin
1) Data content (including elements and significance): 21 stations (Southeast Tibet station, Namucuo station, Zhufeng station, mustag station, Ali station, Naqu station, Shuanghu station, Geermu station, Tianshan station, Qilianshan station, Ruoergai station (northwest courtyard), Yulong Xueshan station, Naqu station (hanhansuo), Haibei Station, Sanjiangyuan station, Shenzha station, gonggashan station, Ruoergai station（ Chengdu Institute of biology, Naqu station (Institute of Geography), Lhasa station, Qinghai Lake Station) 2018 Qinghai Tibet Plateau meteorological observation data set (temperature, precipitation, wind direction and speed, relative humidity, air pressure, radiation and evaporation) 2) Data source and processing method: field observation at Excel stations in 21 formats 3) Data quality description: daily resolution of the site 4) Data application results and prospects: Based on long-term observation data of various cold stations in the Alpine Network and overseas stations in the pan-third pole region, a series of datasets of meteorological, hydrological and ecological elements in the pan-third pole region were established; Strengthen observation and sample site and sample point verification, complete the inversion of meteorological elements, lake water quantity and quality, above-ground vegetation biomass, glacial frozen soil change and other data products; based on the Internet of Things technology, develop and establish multi-station networked meteorological, hydrological, Ecological data management platform, real-time acquisition and remote control and sharing of networked data.
ZHU Liping,
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.
ZHAO Changming, ZHANG Renyi
The data set contains the eddy correlator observation data of Guazhou station of Lanzhou University cold and arid area scientific observation network of Lanzhou University from January 1, 2020 to December 31, 2020. The station is located in Liuyuan Town, Guazhou County, Jiuquan, Gansu Province, with desert on the underlying surface. The longitude and latitude of the observation point are 95.673e, 41.405n, and the altitude is 2014m. The frame height of eddy correlator is 4m, the sampling frequency is 10Hz, the ultrasonic direction is due north, and the distance between ultrasonic anemometer (csat3) and CO2 / H2O analyzer (li7500a) is 17cm. The original observation data of eddy correlator is 10Hz, and the released data is the 30 minute data processed by eddypro software. The main processing steps include: field value elimination, delay time correction, coordinate rotation (quadratic coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction. At the same time, the quality of each flux value is evaluated, mainly the atmospheric stability（ Δ St) and turbulence similarity characteristics (ITC). The 30min flux value output by eddypro software is also screened: (1) eliminate the data when the instrument is wrong; (2) Eliminate the data 1H before and after precipitation; (3) Eliminate the data with a loss rate of more than 10% every 30min in the 10Hz original data. The average period of observation data is 30 minutes, 48 data a day, and the missing data is marked as - 6999. The published observation data include: date / time, wind direction WDIR (°), horizontal wind speed wnd (M / s), standard deviation of lateral wind speed STD_ Uy (M / s), ultrasonic 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 identification QA of sensible heat flux_ HS, quality identification of latent heat flux QA_ Le, quality identification QA of carbon dioxide flux_ Fc。 The quality identification of sensible heat, latent heat and carbon dioxide flux is divided into nine levels (quality identification 1-3 has good data quality, 4-6 has good data quality, 7-8 has poor data quality (better than interpolated data), and 9 has poor data quality). The meaning of data time, for example, 0:30 represents the average of 0:00-0:30; The data is stored in *. XLS format. For observation data processing, please refer to Liu et al. (2011).
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Guazhou station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from January 1 to December 31 in 2019. The site (95.673E, 41.405N) was located in a desert in Liuyuan Guazhou, which is near Jiuquan city in Gansu Province. The elevation is 2016 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.
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Xiyinghe station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from January 1 to December 31 in 2019. The site (101.853E, 37.561N) was located on a alpine meadow in the Menyuan, Qinghai Province. The elevation is 3639 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.
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Suganhu station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from November 29 to December 31 in 2019. The site (94.12E, 38.99N was located in a desert in Suganhu, which is in Gansu Province. The elevation is 2823 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.
ZHAO Changming, ZHANG Renyi
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.
ZHAO Changming, ZHANG Renyi
The data set contains the observation data of vortex correlator at Minqin station of cold and arid area scientific observation network of Lanzhou University from January 1, 2020 to December 31, 2020. The station is located in Minqin County, Wuwei City, Gansu Province, between Badain Jaran Desert and Tengger Desert in Western China. The longitude and latitude of the observation point are 103.668e, 39.208n and 1020m above sea level. The frame height of eddy correlator is 4m, the sampling frequency is 10Hz, the ultrasonic direction is due north, and the distance between ultrasonic anemometer (csat3) and CO2 / H2O analyzer (li7500a) is 17cm. The original observation data of eddy correlator is 10Hz, and the released data is the 30 minute data processed by eddypro software. The main processing steps include: field value elimination, delay time correction, coordinate rotation (quadratic coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction. At the same time, the quality of each flux value is evaluated, mainly the atmospheric stability（ Δ St) and turbulence similarity characteristics (ITC). The 30min flux value output by eddypro software is also screened: (1) eliminate the data when the instrument is wrong; (2) Eliminate the data with a loss rate of more than 10% every 30min in the 10Hz original data. The average period of observation data is 30 minutes, 48 data a day, and the missing data is marked as - 6999. The published observation data include: date / time, wind direction WDIR (°), horizontal wind speed wnd (M / s), standard deviation of lateral wind speed STD_ Uy (M / s), ultrasonic 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 identification QA of sensible heat flux_ HS, quality identification of latent heat flux QA_ Le, quality identification QA of carbon dioxide flux_ Fc。 The quality identification of sensible heat, latent heat and carbon dioxide flux is divided into nine levels (quality identification 1-3 has good data quality, 4-6 has good data quality, 7-8 has poor data quality (better than interpolated data), and 9 has poor data quality). The meaning of data time, for example, 0:30 represents the average of 0:00-0:30; The data is stored in *. XLS format.
ZHAO Changming, ZHANG Renyi
This dataset contains the flux measurements from the Sidalong station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from Mar 26 to Dec 31 in 2020. The site (99.926E, 38.428N) was located on a forest in the Kangle Sunan, which is near Zhangye city, Gansu Province. The elevation is 3146 m. The EC was installed at a height of 4.0 m above the canopy , 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.
ZHAO Changming, ZHANG Renyi
The data set includes the eddy correlator observation data of suganhu station of Lanzhou University cold and arid area scientific observation network of Lanzhou University from January 1, 2020 to December 31, 2020. The station is located in Sugan lake, Gansu Province, with wetland on the underlying surface. The longitude and latitude of the observation point are 94.12e, 38.99n and 2823m above sea level. The frame height of eddy correlator is 4m, the sampling frequency is 10Hz, the ultrasonic direction is due north, and the distance between ultrasonic anemometer (csat3) and CO2 / H2O analyzer (li7500a) is 17cm. The original observation data of eddy correlator is 10Hz, and the released data is the 30 minute data processed by eddypro software. The main processing steps include: field value elimination, delay time correction, coordinate rotation (quadratic coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction. At the same time, the quality of each flux value is evaluated, mainly the atmospheric stability（ Δ St) and turbulence similarity characteristics (ITC). The 30min flux value output by eddypro software is also screened: (1) eliminate the data when the instrument is wrong; (2) Eliminate the data with a loss rate of more than 10% every 30min in the 10Hz original data. The average period of observation data is 30 minutes, 48 data a day, and the missing data is marked as - 6999. The published observation data include: date / time, wind direction WDIR (°), horizontal wind speed wnd (M / s), standard deviation of lateral wind speed STD_ Uy (M / s), ultrasonic 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 identification QA of sensible heat flux_ HS, quality identification of latent heat flux QA_ Le, quality identification QA of carbon dioxide flux_ Fc。 The quality identification of sensible heat, latent heat and carbon dioxide flux is divided into nine levels (quality identification 1-3 has good data quality, 4-6 has good data quality, 7-8 has poor data quality (better than interpolated data), and 9 has poor data quality). The meaning of data time, for example, 0:30 represents the average of 0:00-0:30; The data is stored in *. XLS format.
ZHAO Changming, ZHANG Renyi
The data set contains the eddy correlator observation data of xiyinghe station of Lanzhou University cold and arid area scientific observation network of Lanzhou University from January 1, 2020 to December 31, 2020. The station is located in taola village, Xianmi Township, Menyuan County, Haibei, Qinghai, with alpine meadow on the underlying surface. The longitude and latitude of the observation point are 101.855e, 37.561n and the altitude is 3616m. The frame height of eddy correlator is 4m, the sampling frequency is 10Hz, the ultrasonic direction is due north, and the distance between ultrasonic anemometer (csat3) and CO2 / H2O analyzer (li7500a) is 17cm. The original observation data of eddy correlator is 10Hz, and the released data is the 30 minute data processed by eddypro software. The main processing steps include: field value elimination, delay time correction, coordinate rotation (quadratic coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction. At the same time, the quality of each flux value is evaluated, mainly the atmospheric stability（ Δ St) and turbulence similarity characteristics (ITC). The 30min flux value output by eddypro software is also screened: (1) eliminate the data when the instrument is wrong; (2) Eliminate the data with a loss rate of more than 10% every 30min in the 10Hz original data. The average period of observation data is 30 minutes, 48 data a day, and the missing data is marked as - 6999. Data from September 10 to October 22 are missing. The published observation data include: date / time, wind direction WDIR (°), horizontal wind speed wnd (M / s), standard deviation of lateral wind speed STD_ Uy (M / s), ultrasonic 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 identification QA of sensible heat flux_ HS, quality identification of latent heat flux QA_ Le, quality identification QA of carbon dioxide flux_ Fc。 The quality identification of sensible heat, latent heat and carbon dioxide flux is divided into nine levels (quality identification 1-3 has good data quality, 4-6 has good data quality, 7-8 has poor data quality (better than interpolated data), and 9 has poor data quality). The meaning of data time, for example, 0:30 represents the average of 0:00-0:30; The data is stored in *. XLS format.
ZHAO Changming, ZHANG Renyi
CMADS V1.1(The China Meteorological Assimilation Driving Datasets for the SWAT model Version 1.1) Version of the data set introduced the STMAS assimilation algorithm. It was constructed using multiple technologies and scientific methods, including loop nesting of data, projection of resampling models, and bilinear interpolation. The CMADS series of datasets can be used to drive various hydrological models, such as SWAT, the Variable Infiltration Capacity (VIC) model, and the Storm Water Management model (SWMM). It also allows users to conveniently extract a wide range of meteorological elements for detailed climatic analyses. Data sources for the CMADS series include nearly 40,000 regional automatic stations under China’s 2,421 national automatic and business assessment centres. This ensures that the CMADS datasets have wide applicability within the country, and that data accuracy was vastly improved. The CMADS series of datasets has undergone finishing and correction to match the specific format of input and driving data of SWAT models. This reduces the volume of complex work that model builders have to deal with. An index table of the various elements encompassing all of East Asia was also established for SWAT models. This allows the models to utilize the datasets directly, thus eliminating the need for any format conversion or calculations using weather generators. Consequently, significant improvements to the modelling speed and output accuracy of SWAT models were achieved. Most of the source data in the CMADS datasets are derived from CLDAS in China and other reanalysis data in the world. The integration of air temperature (2m), air pressure, humidity, and wind speed data (10m) was mainly achieved through the LAPS/STMAS system. Precipitation data were stitched using CMORPH’s global precipitation products and the National Meteorological Information Center’s data of China (which is based on CMORPH’s integrated precipitation products). The latter contains daily precipitation records observed at 2,400 national meteorological stations and the CMORPH satellite’s inversion precipitation products.The inversion algorithm for incoming solar radiation at the ground surface makes use of the discrete longitudinal method by Stamnes et al.(1988)to calculate radiation transmission. The resolutions for CMADS V1.0, V1.1, V1.2, and V1.3 were 1/3°, 1/4°, 1/8°, and 1/16°, respectively. In CMADS V1.0 (at a spatial resolution of 1/3°), East Asia was spatially divided into 195 × 300 grid points containing 58,500 stations. Despite being at the same spatial resolution as CMADS V1.0, CMADS V1.1 contains more data, with 260 × 400 grid points containing 104,000 stations. For both versions, the stations’ daily data include average solar radiation, average temperature (2m), average pressure, maximum and minimum temperature (2m), specific humidity, cumulative precipitation, and average wind speed (10m). The CMADS comprises other variables for any hydrological model(under 'For-other-model' folder): Daily Average Temperature (2m), Daily Maximum Temperature (2m), Daily Minimum Temperature (2m), Daily cumulative precipitation (20-20h), Daily average Relative Humidity, Daily average Specific Humidity, Daily average Solar Radiation, Daily average Wind (10m), and Daily average Atmospheric Pressure. Introduction to metadata of CMADS CMADS storage path description:(CMADS was divided into two datesets) 1.CMADS-V1.0 For-swat --specifically driving the SWAT model 2.CMADS-V1.0 For-other-model --specifically driving the other hydrological model(VIC,SWMM,etc.) CMADS-- For-swat-2009 folder contain:(Station and Fork ) 1).Station Relative-Humidity-58500 Daily average relative humidity(fraction) Precipitation-58500 Daily accumulated 24-hour precipitation(mm) Solar radiation-58500 Daily average solar radiation(MJ/m2) Tmperature-58500 Daily maximum and minimum 2m temperature(℃) Wind-58500 Daily average 10m wind speed(m/s) Where R, P, S, T, W+ dimensional grid number - the number of longitude grid is the station in the above five folders respectively.(Where R,P,S,T,W respective Daily average relative humidity,Daily cumulative precipitation(24h),Daily mean solar radiation(MJ/m2),Daily maximum and minimum temperature(℃) and Daily mean wind speed (m/s)) respectively.Data format is (.dbf) 2).Fork (Station index table over East Asia) PCPFORK.txt (Precipitation index table) RHFORK.txt (Relative humidity index table) SORFORK.txt (Solar radiation index table) TMPFORK.txt (Temperature index table) WINDFORK.txt (Wind speed index) CMADS-- For-swat-2012 folder contain:(Station and Fork ) Storage structure is consistency with For-swat- 2009 .However, all the data in this directory are only available in TXT format and can be readed by SWAT2012. 3) For-other-model (Includes all weather input data required by the any hydrologic model (daily).) Atmospheric-Pressure-txt Daily average atmospheric pressure(hPa) Average-Temperature-txt Daily average 2m temperature(℃) Maximum-Temperature-txt Daily maximum 2m temperature(℃) Minimum-Temperature-txt Daily minimum 2m temperature(℃) Precipitation-txt Daily accumulated 24-hour precipitation (mm) Relative-Humidity-txt Daily average relative humidity(fraction) Solar-Radiation-txt Daily average solar radiation(MJ/m2) Specific-Humidity-txt Daily average Specific Humidity(g/kg) Wind-txt Daily average 10m wind speed(m/s) Data storage information: data set storage format is .dbf and .txt Other data information: Total data:45GB Occupied space: 50GB Time: From year 2008 to year 2014 Time resolution: Daily Geographical scope description: East Asia Longitude: 60° E The most east longitude: 160°E North latitude: 65°N Most southern latitude: 0°N Number of stations: 58500 stations Spatial resolution: 1/3 * 1/3 * grid points Vertical range: None
Meng Xianyong, Wang Hao
Daily and Monthly evapotranspiration (5km x 5km spatial resolution) for global land area was derived from satellite data and a surface energy balance method (EB). The global 5 km daily and monthly ET dataset is produced with the revised SEBS algorithm in Chen et al. 2019 JGR and Chen et al. 2013 (JAMC). For how to obtain seamless daily evaporation data by thermal infrared, please refer to Chen et al. 2021 JGR. This paper also compares different evaporation products. The results show that this product is significantly better than Landflux, GLEAM, MOD16, GLDAS and ERA-Interim products in irrigation area. The downscaling of reanalysis forcing data is detailed in this paper. MODIS LST, NDVI, Global forest height, GlobAlbedo, GLASS LAI have been used in this ET calculation. The ET dataset will be updated to near-present with the availability of input dataset. The global 5 km sensible heat flux, net radiation, latent heat flux will be open with the email contact with Dr. Xuelong Chen. Daily ET File name: 20001201-ET-V1.mat, 2000-year, 12-month,01-day, ET-Evapotranspiration, V1-version 1;unit: mm/day (unit8 need transfer to single or double and should be divided by 10);data type: unit8 was used to save the disk space, 255 is used for ocean and water body pixels. Monthly ET File name: ETm200012-ET-V1.mat, 2000-year, 12-month, ET-Evapotranspiration, V1-version 1;unit: mm/month (int16 need transfer to single or double and should be divided by 10);data type: int16 was used to save the disk space, 0 is used for ocean and water body pixels. The daily ET dataset is produced with a similar method and satellite data as in Chen, X., et al., 2014: Development of a 10 year (2001–2010) 0.1° dataset of land-surface energy balance for mainland China, Atmos. Chem. Phys., 14, 13097–13117, doi:10.5194/acp-14-13097-2014. The calculation of roughness length and kB_1 for global land were updated by the method in Chen, X., et al, 2019, A Column Canopy‐Air Turbulent Diffusion Method for Different Canopy Structures, Journal of Geophysical Research: Atmospheres, 2019.01.15, 124. Most of the satellite input data were from MODIS. Meteorological data was from ERA-Interim. Global canopy height information was derived from GLAS and MODIS NDVI. The daily ET has a mean bias (MB) of 0.04 mm/day, RMSE is 1.56 (±0.25) mm/day.
CHEN Xuelong
Accurate evapotranspiration (ET) estimation is important for understanding hydrological cycle and water resources management in the cropland. Based on eight flux sites within the North China Plain (NCP) and the surrounding area, which were integrated together for the first time, we applied support vector regression method to develop ET dataset for the cropland in NCP from 1982 to 2015 with 1/12° spatial resolution and eight-day temporal interval.
LEI Huimin
This dataset contains the fluxes and meteorological data of Weishan (Gaoying) flux site of Tsinghua University from May 17, 2005 to September 26, 2006. The site (116.0542° E, 36.6487° N, 30 m above sea level) was built on March 18, 2005 and is located in Xiaozhuang Town, Chiping District, Liaocheng City, Shandong Province. It belongs to Weishan Irrigation District along the lower Yellow River. The local climate is characterized as temperate monsoons, with an average annual temperature of 13.8 ℃, an average annual precipitation of 553mm, most of which occurs between June and October, and an average annual potential evaporation of 1950mm. The soil type is silt loam. For the soil of the top 5 cm, the average saturated soil water content, field capacity and wilting point in volumetric values are 0.43, 0.33 and 0.10 m3m-3, respectively. The height of the flux tower is 10m, and the area within about 1 km radius around the flux tower is largely homogeneous winter wheat-summer maize rotation cropland. The winter wheat is generally sown in mid-October and harvested in early June of the following year, while the summer maize is usually planted directly into the stubbles of wheat at the same location immediately after the harvest of wheat and is harvested in late September to early October. See the file named “Supplementary data_WeishanGaoying20052006.xlsx” for specific sowing, harvesting and irrigation dates. The surface flux data is measured by the eddy covariance system, which is composed of a three-dimensional sonic anemometer (CSAT3, Campbell Scientific, Inc., Logan, UT, USA) and an open-path infrared gas analyzer (IRGA) (LI-7500, LI-COR, Inc., Lincoln, NE, USA) with an installation height of 3.7m. The 30-minute net ecosystem carbon exchange (NEE), latent heat flux (LE) and sensible heat flux (H) data were obtained after the raw 10Hz data were processed by Eddypro software. The preprocessing steps included despiking, double coordinate rotation, 30-min block averaging, time lag compensation, spectral corrections, the Webb-Pearman-Leuning (WPL) density correction, a quality check using the “0-1-2 system”. Then the 30-min data were screened as follows: (1) remove bad quality fluxes with quality flag 2; (2) limit H and LE to - 200 ~ 500 W m-2 and - 200 ~ 800 W m-2, respectively; (3) the data during the precipitation events were excluded. Then, REddyproc software is used to filter the data under low turbulence mixing conditions (i.e. filter the flux data according to the friction wind speed u*), fill the gaps in the time series, and then the NEE was divided into ecosystem respiration (Reco) and gross primary production (GPP) by the nighttime partitioning method. The published dataset includes: year, month, day, time, atmospheric pressure (P), infrared surface temperature (Tsurf), wind speed (Ws), wind direction (Wd), air temperature (Tair) and relative humidity (rH) at 2m, downward short wave radiation (Rsd), upward short wave radiation (Rsu), downward long wave radiation (Rld), upward long wave radiation (Rlu), Net radiation (Rn), incident photosynthetically active radiation (PAR_dn), reflected photosynthetically active radiation (PAR_up), precipitation (precip), groundwater level (GW), 5cm/10cm/20cm/40cm/80cm/160cm soil water content (soil_VW_ 5cm / 10cm / 20cm / 40cm / 80cm / 160cm) and soil temperature (soil_T_5cm / 10cm / 20cm / 40cm / 80cm / 160cm), soil heat flux at 5cm depth (soil_ G) , raw data of net ecosystem carbon exchange (NEE_raw), raw data of latent heat flux (LE_raw), raw data of sensible heat flux (H_raw), net ecosystem carbon exchange after gap filling (NEE_ f) , latent heat flux after gap filling (LE_f), sensible heat flux after gap filling (H_f), ecosystem respiration imputation (Reco_f), gross primary productivity (GPP_f). The data are stored in .xlsx format at 30-minute intervals. Null values in the dataset are represented by NA. Please refer to Lei and Yang (2010a, 2010b) for detailed information of this site and the observation instruments.
LEI Huimin
Accurate evapotranspiration (ET) estimation is important for understanding hydrological cycle and water resources management in the cropland. Based on eight flux sites within the North China Plain (NCP) and the surrounding area, which were integrated together for the first time, we applied support vector regression method to develop ET dataset for the cropland in NCP from 2001 to 2015 with 1km spatial resolution and eight-day temporal interval.
LEI Huimin
Ec-earth-heihe USES the output of the global model of ec-earth as the driving field to simulate the 6-hour data of the Heihe river basin in 2006-2080 under the scenarios of 1980-2005 and RCP4.5.Spatial scope: the grid center of the simulation area is located at (40.30n, 99.50e), the horizontal resolution is 3 km, and the number of simulated grid points in the model is 161 (meridional) X 201 (zonal). Projection: LAMBERT conformal projection, two standard latitudes of 30N and 60N. Time range: from January 1, 1980 to December 31, 2010, with an interval of 6 hours. Description of file contents: monthly storage by grads without format.Except the maximum and minimum temperature as the daily scale, the other variables are all 6-hour data. MATLAB can be used to read, visible tmax_erain_xiong_heihe.m file description. Data description of heihe river basin: 1) Anemometer west wind (m/s) abbreviation usurf 2) Anemometer south wind(m/s), abbreviation vsurf 3) Anemometer temperature (deg K) abbreviation tsurf 4) maximal temperature (deg K) abbreviation tmax 5) minimal temperature (deg K) abbreviated tmin 6) Anemom specific humidity (g/kg) abbreviation qsurf 7) Accumulated precipitation (mm/hr) abbreviation precip 8) Accumulated evaporation (mm/hr) abbreviation evap 9) Accumulated sensible heat (watts/m**2/hr) abbreviation sensible 10) Accumulated net infrared radiation (watts/m * * 2 / hr) abbreviation netrad File name definition: Abbreviation-ec-earth-6hour，YTD For example, precip-ec-earth-6hour.198001，Is the data of 6-hour precipitation in January, 1980 (1) historical 6-hour data driven by the ec-earth global climate model from 1980 to 2005 (2) produce 6-hour data of heihe river basin under the scenario of RCP 4.5 for the global climate model ec-earth from 2006 to 2080
XIONG Zhe
This dataset contains the flux measurements from the Alpine meadow and grassland ecosystem Superstation superstation eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from January 1 to December 31 in 2020，but instrument failure and COVID-2019 resulted in lack of data from February 1 to June 27. The site (98°35′41.62″E, 37°42′11.47″N) was located in the alpine meadow and alpine grassland ecosystem, near the SuGe Road in Tianjun County, Qinghai Province. The elevation is 3718m. 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 (CSAT3A &EC150) was about 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. Data during December 18 to December 24, 2018 were missing due to the data collector failure. The released data contained the following variables: DATE/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). The quality marks of sensible heat flux, latent heat flux and carbon flux are divided into three levels (quality marks 0 have good data quality, 1 have good data quality and 2 have poor data quality). 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.
This dataset contains the flux measurements from the Subalpine shrub eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from January 1 to December 31 in 2020. The site (100°6'3.62"E, 37°31'15.67" N ) was located near Dasi, Shaliuhe Town, Gangcha County, Qinghai Province. Data missing due to instrument failure. The elevation is 3495m. The EC was installed at a height of 2.5m, 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 (Gill&Li7500A) was about 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. The released data contained the following variables: DATE/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). The quality marks of sensible heat flux, latent heat flux and carbon flux are divided into three levels (quality marks 0 have good data quality, 1 have good data quality and 2 have poor data quality). 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.
Li Xiaoyan
This dataset contains the flux measurements from the temperate steppe eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from January 1 to December 31 in 2020, but instrument failure and COVID-2019 resulted in lack of data from April 13 to July 20. The site (100°14'8.99"E, 37°14'49.00"N) was located in Sanjiaocheng sheep breeding farm, Gangcha County, Qinghai Province. The elevation is 3210sm. The EC was installed at a height of 2.5 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 (CSAT3A &EC150) was about 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. Data during December 18 to December 24, 2018 were missing due to the data collector failure. The released data contained the following variables: DATE/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). The quality marks of sensible heat flux, latent heat flux and carbon flux are divided into three levels (quality marks 0 have good data quality, 1 have good data quality and 2 have poor data quality). 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.
The spatial-temporal distribution map of topographic shadows in the upper reaches of Heihe River (2018), which is calculated based on the SRTM DEM and the solar position (http://www.esrl.noaa.gov/gmd/grad/solcalc/azel.html). The spatial resolution is 100 m and the time resolution is 15 min. The datased can be used in the fields of ecological hydrology and remote sensing research. Using the observed solar radiation at several automatic weather stations in the upper reaches of Heihe River, the accuracy of the calculation results is verified. Results show that the dataset can accurately capture the temporal and spatial changes of the topographic shadow at the stations, and the time error is within 20 minutes.
ZHANG Yanlin
(1) This data set is the carbon flux data set of Shenzha alpine wetland from 2016 to 2019, including air temperature, soil temperature, precipitation, ecosystem productivity and other parameters. (2) The data set is based on the field measured data of vorticity, and adopts the internationally recognized standard processing method of vorticity related data. The basic process includes: outlier elimination coordinate rotation WPL correction storage item calculation precipitation synchronization data elimination threshold elimination outlier elimination U * correction missing data interpolation flux decomposition and statistics. This data set also contains the model simulation data calibrated based on the vorticity correlation data set. (3) the data set has been under data quality control, and the data missing rate is 37.3%, and the missing data has been supplemented by interpolation. (4) The data set has scientific value for understanding carbon sink function of alpine wetland, and can also be used for correction and verification of mechanism model.
Da Wei
This data set contains the eddy correlation observation data of arou super station upstream of heihe hydrological and meteorological observation network on January 1, 2015 and December 31, 2017.Site is located in qilian county, qinghai province, arou township grass daban village, the underlying surface is alpine grassland.The longitude and latitude of the observation point are 100.4643E, 38.0473N, and the altitude is 3033m.The height of the vortex correlative instrument is 3.5m, the sampling frequency is 10Hz, the ultrasonic orientation is due north, and the distance between the ultrasonic wind speed temperature meter (CSAT3) and the CO2/H2O analyzer (Li7500A) is 15cm. The original observation data of the vortex correlator is 10Hz, and the published data are the 30-minute data processed by Eddypro. The main steps of the processing include: elimination of outliers, correction of delay time, coordinate rotation (quadratic coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction, etc.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 flux value output by Eddypro software was also screened :(1) to eliminate the data in case of instrument error;(2) data of 1h before and after precipitation were removed;(3) data with a miss rate of more than 10% per 30min in 10Hz original data were excluded;(4) observation data of weak turbulence at night (u* less than 0.1m/s) were excluded.The average period of observation data was 30 minutes, with 48 data in a day, and the missing data was marked as -6999.Suspicious data caused by instrument drift and other reasons are marked with red font. Among them, calibration data of vortex system Li7500A on April 16-17 is missing.When the memory card fails to store data, resulting in the loss of 10Hz data (9.20-10.21,11.3-11.18), the data is replaced by the 30min flux data output by the collector. The published observations 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 (℃), the water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar) (m/s), Mr. Hoff length L (m), 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,Mass identification of co2 flux.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 is 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. For information of hydrometeorological network or site, please refer to Li et al. (2013), and for data processing, please refer to Liu et al. (2011).
CHE Tao, LIU Shaomin, LI Xin, XU Ziwei, ZHANG Yang, TAN Junlei
This dataset contains the flux measurements from site No.14 eddy covariance system (EC) in the flux observation matrix from 30 May to 21 September, 2012. The site (100.35310° E, 38.85867° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1570.23 m. The EC was installed at a height of 4.6 m; 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. Raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including 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. Moreover, 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), which was proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), representing high-, medium-, and low-quality data, respectively. 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 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; the missing data were replaced with -6999. Moreover, 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/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), 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 *.xlsx format. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, XU Ziwei
This data set contains the eddy correlation-meter observation data of the mixed forest station downstream of heihe hydrometeorological observation network from January 1, 2017 to December 31, 2017.The station is located in Inner Mongolia ejin banner four road bridge, under the surface is populus and tamarix.The longitude and latitude of the observation point are 101.1335e, 41.9903n and 874 m above sea level.The rack height of the vortex correlativity instrument is 22m, the sampling frequency is 10Hz, the ultrasonic orientation is due north, and the distance between the ultrasonic wind speed and temperature meter (CSAT3) and CO2/H2O analyzer (Li7500) is 17cm. The original observation data of the vortex correlativity instrument is 10Hz, and the published data is the 30-minute data processed by Eddypro software. The main processing steps include: outliers, delay time correction, coordinate rotation (quadratic 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 by Eddypro software was also screened :(1) data when instrument error was eliminated;(2) data of 1h before and after precipitation are excluded;(3) remove the data with a missing rate of more than 10% in the original 10Hz data within every 30 minutes;(4) the observation data of weak turbulence at night (u* less than 0.2m/s) were excluded.The average observation period was 30 minutes, 48 data per day, and the missing data was marked as -6999.April 7 solstice April 8 due to instrument calibration, 3.24-4.08 infrared gas analyzer error, data missing.Suspicious data caused by instrument drift, etc., are identified in red font.When 10Hz data is missing due to a problem with the memory card storage data, the data is replaced by the 30min flux data output by the collector. The published observational data 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 (℃), the water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar) (m/s), Mr. Hoff length L (m), 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,Quality indicator for co2 flux QA_Fc.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 is 2).The meaning of data time, such as 0:30 represents the average of 0:00-0:30;The data is stored in *.xls format. For information of hydrometeorological network or station, please refer to Li et al. (2013), and for observation data processing, please refer to Liu et al. (2011).
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
The dataset of LST (land surface temperature) observed by the thermal camera (ThermaCAM SC2000 and ThermaCAM S60) at 24°×18° was obtained in the Yingke oasis, Huazhaizi desert steppe and Linze grassland foci experimental areas on May 20, 24,28 and 30, Jun. 1, 4, 16 and 29, Jul. 7, 8 and 11, 2008. Meanwhile, the optical photos were acquired in Yingke oasis maize field, Huazhaizi desert No. 1 and 2 plots, Huazhaizi desert maize field and Linze grassland. The dataset of ground truth measurement was synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner), OMIS-II, Landsat TM and ASTER.
HE Tao, KANG Guoting, REN Huazhong, YAN Guangkuo, WANG Haoxing, WANG Tianxing, LI Hua, Liu Qiang, XIA Chuanfu, ZHOU Chunyan, ZHOU Mengwei, CHEN Shaohui, YANG Tianfu
This data set contains the observation data of vortex-correlograph in the middle reaches of heihe hydrometeorological observation network from January 1, 2015 to December 31, 2015.The station is located in the daman irrigation district of zhangye city, gansu province.The latitude and longitude of the observation point is 100.37223E, 38.85551N, and the altitude is 1556.06m.The rack height of the vortex correlativity meter is 4.5m, the sampling frequency is 10Hz, the ultrasonic orientation is due north, and the distance between the ultrasonic wind speed and temperature meter (CSAT3) and CO2/H2O analyzer (Li7500A) is 17cm. The original observation data of the vortex correlativity instrument is 10Hz, and the published data is the 30-minute data processed by Eddypro software. The main processing steps include: outliers, delay time correction, coordinate rotation (quadratic 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 by Eddypro software was also screened :(1) data when instrument error was eliminated;(2) data of 1h before and after precipitation are excluded;(3) remove the data with a missing rate of more than 10% in the original 10Hz data within every 30 minutes;(4) the observation data of weak turbulence at night (u* less than 0.1m/s) were excluded.The average observation period was 30 minutes, 48 data per day, and the missing data was marked as -6999.Li7500A of the eddy current system was calibrated from April 12 to 14, and data was missing. The published observational data 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 (℃), the water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar) (m/s), Mr. Hoff length L (m), 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,Quality indicator for co2 flux QA_Fc.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 is 2).The meaning of data time, such as 0:30 represents the average of 0:00-0:30;The data is stored in *.xls format. For information of hydrometeorological network or station, please refer to Liu et al. (2018), and for observation data processing, please refer to Liu et al. (2011).
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
The data set contains observation data from the Tianlaochi small watershed automatic weather station. The latitude and longitude of the station are 38.43N, 99.93E, and the altitude is 3100m. Observed items are time, average wind speed (m/s), maximum wind speed (m/s), 40-60cm soil moisture, 0-20 soil moisture, 20-40 soil moisture, air pressure, PAR, air temperature, relative humidity, and dew point temperature , Solar radiation, total precipitation, 20-40 soil temperature, 0-20 soil temperature, 40-60 soil temperature. The observation period is from May 25, 2011 to September 11, 2012, and all parameter data are compiled on a daily scale.
ZHAO Chuanyan, MA Wenying
This dataset contains the flux measurements from the large aperture scintillometer (LAS) at A’rou Superstation in the hydrometeorological observation network of Heihe River Basin between 14 October, 2012, and 31 December, 2013. There were two types of LASs at A’rou Superstation: German BLS450 and China zzlas. The north tower was set up with the zzlas receiver and the BLS450 transmitter, and the south tower was equipped with the zzlas transmitter and the BLS450 receiver. Zzlas has been in use since 14 October, 2012, and the observation period of BLS450 was from 9 August to 10 December, 2013. The site (north: 100.467° E, 38.050° N; south: 100.450° E, 38.033° N) was located in Caodaban village of A’rou town in Qilian county, Qinghai Province. The underlying surface between the two towers was alpine meadow. The elevation is 3033 m. The effective height of the LASs was 9.5 m, and the path length was 2390 m. The data were sampled at 5 Hz and 1 Hz intervals for BLS450 and zzlas, respectively, and then averaged over 1 min. The raw data acquired at 1 min intervals were processed and quality controlled. The data were subsequently averaged over 30 min periods, in which sensible heat flux was iteratively calculated by combining Cn2 with meteorological data according to the Monin-Obukhov similarity theory. The main quality control steps were as follows: (1) The data were rejected when Cn2 exceeded the saturated criterion (BLS450: Cn2>7.25E-14, zzlas: Cn2>7.84E-14). (2) The data were rejected when the demodulation signal was small (BLS450: Average X Intensity<1000; zzlas: Demod>-20 mv). (3) The data were rejected when collected during precipitation. (4) The data were rejected if collected at night when weak turbulence occurred (u* was less than 0.1 m/s). In the iteration process, the universal functions of Thiermann and Grassl, 1992 and Andreas, 1988 were selected for BLS450 and zzlas, respectively. Several instructions were included with the released data. (1) The data were primarily obtained from BLS450 measurements, and missing flux measurements from the BLS450 instrument were substituted with measurements from the zzlas instrument. The missing data were denoted by -6999. Due to the drift of the zzlas signal, data from 10 November to 23 November, 2012, and 14 March to 10 April, 2013, were excluded. Due to the LAS tower’s lean, the data from 10 April to 31 May, 2013, were not collected. (2) The dataset contained the following variables: data/time (yyyy-m-d h:mm), the structural parameter of the air refractive index (Cn2, m-2/3), and the sensible heat flux (H_LAS, W/m^2). In this dataset, a time of 0:30 corresponds to the average data for the period between 0:00 and 0:30, and the data were stored in *.xls format. Moreover, suspicious data were marked in red. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
LI Xin, CHE Tao, XU Ziwei, ZHANG Yang, TAN Junlei
This dataset contains the flux measurements from the Huazhaizi desert steppe station eddy covariance system (EC) in the flux observation matrix from 6 June to 15 September, 2012. The site (100.31860° E, 38.76519° N) was located in a desert surface, which is near Zhangye, Gansu Province. The elevation is 1731.00 m. The EC was installed at a height of 2.85 m; 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. Raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including 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. Moreover, 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), which was proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), representing high-, medium-, and low-quality data, respectively. 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 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; the missing data were replaced with -6999. Moreover, 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/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), 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 *.xlsx format. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, XU Ziwei
This dataset contains the flux measurements from the Sidaoqiao superstation eddy covariance system (EC) in the lower reaches of the Heihe hydrometeorological observation network from 6 July to 31 December, 2013. The site (101.137° E, 42.001° N) was located in the Tamarix surface, Ejin Banner in Inner Mongolia. The elevation is 873 m. The EC was installed at a height of 8 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 0.15 m. The raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), 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), as proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), which represent high-, medium-, and low-quality data, respectively. In addition to the above processing steps, the half-hourly flux data were screened using 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 0.12 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/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), 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. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
The China Meteorological Forcing Dataset (CMFD) is a high spatial-temporal resolution gridded near-surface meteorological dataset that was developed specifically for studies of land surface processes in China. The dataset was made through fusion of remote sensing products, reanalysis dataset and in-situ observation data at weather stations. Its record starts from January 1979 and keeps extending (currently up to December 2018) with a temporal resolution of three hours and a spatial resolution of 0.1°. Seven near-surface meteorological elements are provided in CMFD, including 2-meter air temperature, surface pressure, specific humidity, 10-meter wind speed, downward shortwave radiation, downward longwave radiation and precipitation rate.
YANG Kun, HE Jie, WENJUN TANG , LU Hui, QIN Jun , CHEN Yingying, LI Xin
The total solar radiation and the total radiation of absorption and scattering material attenuation are measured by the international general solar radiation meter (li200sz, li-cor, Inc., USA). The measured data are total solar radiation, including direct and diffuse solar radiation, with a wavelength range of 400-1100nm. The unit of measurement is w / m2, and the typical error is ± 3% (incidence angle is within 60 °) under natural lighting. The data of sodankyl ä station in the Arctic comes from cooperation with the site and website download. The coverage time of sodankyl ä station in the Arctic is updated to 2018.
BAI Jianhui
This data set contains the daily values of temperature, air pressure, relative humidity, wind speed, precipitation, and total radiation observed at the Namco station from 1 October 2005 to 31 December 2016. The data set was processed as a continuous time series after the original data were quality controlled. After the systematic error caused by missing data points and sensor failure was eliminated, the data set reaches the accuracy of raw meteorological observation data required by the National Weather Service and the World Meteorological Organization (WMO). The data can provide information for professionals engaged in scientific research and training related to atmospheric physics, atmospheric environment, climate, glaciers, frozen soils and other disciplines. This data set has mainly been applied in the fields of glaciology, climatology, environmental change, cold zone hydrological processes, frozen soil science, etc. The measured parameters had the following units and accuracies: Air temperature, unit: °C, accuracy: 0.1 °C; air relative humidity, unit: %, accuracy: 0.1%; wind speed, unit: m/s, accuracy: 0.1 m/s; wind direction, unit: °, accuracy: 0.1 °; air pressure, unit: hPa, accuracy: 0.1 hPa; precipitation, unit: mm, accuracy: 0.1 mm; total radiation, unit: W/m2, accuracy: 0.1 W/m2.
WANG Yuanwei, WU Guangjian
The data set contains the vortex correlator observation data of the farmland station downstream of heihe hydrometeorological observation network from January 1, 2015 to November 5, 2015.The station is located in the four Bridges of ejin banner in Inner Mongolia.The latitude and longitude of the observation point are 101.1338e, 42.0048n, and 875m above sea level.The height of the vortex correlation instrument is 3.5m, the sampling frequency is 10Hz, the ultrasonic direction is due to the north, and the distance between the ultrasonic wind speed and temperature instrument (CSAT3) and the CO2/H2O analyzer (Li7500A) is 15cm. The original observation data of vorticity correlativity is 10Hz, and the released data is the data of 30 minutes processed by Eddypro software. The main steps of its 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 by Eddypro software was also screened.(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.Suspicious data caused by instrument drift shall be identified in red.On April 21, solstice, June 22, the instrument was being replaced, during which the data was missing, and the station was dismantled on November 5. Observations published 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 (℃), the water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar) (m/s), Mr. Hoff length L (m), 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,Carbon dioxide flux mass identification QA_Fc.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 Li et al. (2013) for hydrometeorological network or site information, and Liu et al. (2011) for observation data processing.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
This dataset contains the flux measurements from site No.8 eddy covariance system (EC) in the flux observation matrix from 28 May to 21 September, 2012. The site (100.37649° E, 38.87254° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1550.06 m. The EC was installed at a height of 3.2 m; 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. Raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including 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. Moreover, 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), which was proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), representing high-, medium-, and low-quality data, respectively. 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 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; the missing data were replaced with -6999. Moreover, 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/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), 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 *.xlsx format. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, XU Ziwei
The data set contains the vortex correlator observation data of sidaqiao superstation in the downstream of heihe hydrometeorological observation network from January 1, 2016 to December 31, 2016.The station is located in the fourth bridge of ejin banner in Inner Mongolia, tamarisk is the underlying surface.The latitude and longitude of the observation point is 101.1374e, 42.0012n, and the altitude is 873 m.The height of the vortex correlativity instrument is 8m, the sampling frequency is 10Hz, the ultrasonic direction is due to the north, and the distance between the ultrasonic wind speed and temperature instrument (CSAT3) and the CO2/H2O analyzer (Li7500) is 15cm. The original observation data of vorticity correlativity is 10Hz, and the released data is the data of 30 minutes processed by Eddypro software. The main steps of its 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 by Eddypro software was also screened.(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.From April 14 to 23, data was missing due to errors and calibration of the vortex system Li7500.During the period from May 1 to August 23, the intermittent error of Li7500 resulted in the loss of latent heat flux and carbon dioxide flux.Suspicious data caused by instrument drift shall be identified in red. Observations published 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 (℃), the water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar) (m/s), Mr. Hoff length L (m), 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,Carbon dioxide flux mass identification QA_Fc.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 Li et al. (2013) for hydrometeorological network or site information, and Liu et al. (2011) for observation data processing.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
The data set contains the flux observation data of scintillator with large aperture from sidaoqiao station downstream of heihe hydrometeorological observation network.There are two groups of large aperture scintillators at the downstream sidaoqiao station.On the east side (point 1), there is a large aperture scintillator of model BLS900. The north tower is the receiving end and the south tower is the transmitting end. The observation period of BLS900_1 is from March 13, 2014 to December 31, 2014.On the west side (no. 2 point), there is a large aperture scintillator of BLS900 model. The north tower is the receiving end and the south tower is the transmitting end, and the observation time of BLS900_2 is from January 1, 2014 to November 8, 2014.The station is located in ejin banner of Inner Mongolia, the underlying surface involves tamarisk, populus populus, bare land and cultivated land.The latitude and longitude of the north tower of point 1 is 101.147e, 42.005n, and that of the south tower is 101.131e, 41.987n.The latitude and longitude of the north tower at point 2 is 101.137e, 42.008n, and the latitude and longitude of the south tower is 101.121e, 41.990 N, with an altitude of about 873m.The effective height of the large aperture scintillation instrument is 25.5m, the diameter length of LAS at point 1 is 2390m, and that of LAS at point 2 is 2380m, and the sampling frequency is 1min. Large aperture flicker meter raw observation data for 1 min, data released for 30 min after processing and quality control of data, including sensible heat flux is mainly combined with the automatic meteorological station observation data, based on similarity theory alonzo mourning - Mr. Hoff is obtained by iterative calculation, the quality control of the main steps include: (1) excluding Cn2 reach saturation data (BLS900_1: Cn2 > 7.25 e-14, BLS900_2: Cn2 > 7.33 E - 14).(2) data with weak demodulation signal strength (Average X Intensity<1000) were eliminated;(3) data at the time of precipitation were excluded;(4) data of weak turbulence under stable conditions were excluded (u* < 0.1m/s).In the iterative calculation process, for BLS900, the stability universal function of Thiermann and Grassl, 1992 was selected.Please refer to Liu et al.(2011, 2013) for detailed introduction. Some notes on the released data :(1) the data of LAS point 1 in the downstream is mainly BLS900_1, and the missing moment is marked by -6999;LAS data of downstream point 2 is mainly BLS900_2, and the missing moment is marked by -6999.(2) data table head: Date/Time: Date/Time (format: yyyy-m-d h:mm), Cn2: structural parameters of air refraction index (unit: m-2/3), H_LAS: sensible heat flux (unit: W/m2).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 Li et al.(2013) for hydrometeorological network or site information, and Liu et al.(2011) for observation data processing.
LIU Shaomin, LI Xin, XU Ziwei, CHE Tao, REN Zhiguo, TAN Junlei
NCEP/NCAR Reanalysis 1 is an assimilation of data from the past (1948-recent). It was developed by the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP–NCAR) in the US to act as an advanced analysis and prediction system. Most of the data are from the original daily average data of the PSD (Physical Sciences Division). However, the data from 1948 to 1957 are slightly different because these data are conventional (non-Gaussian) grid data. The information published on the official website is generally from 1948 to the present, and the latest information is generally updated every two days. For data on an isostatic surface, the general vertical resolution is 17 layers, from 1000 hPa to 10 hPa. The horizontal resolution is typically 2.5° x 2.5°. The NCEP reanalysis data are systematically comparable among international atmospheric science reanalysis data sets. Compared with the reanalysis data of the European Center, the initial year is earlier, and the latest data updates are more frequent. These two sets of reanalysis data are currently the most widely used data sets in the world. For details of the data, please visit the following website: https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html
LUO Dehai, YAO Yao
The meteorological field is located at 3200m above sea level in Pailugou watershed of Qilian Mountain, which belongs to the high mountain forest line zone, the ecotone of Picea crassifolia forest and alpine shrub. This data set includes precipitation, air temperature, radiation, wind speed, etc., with units are mm, ℃, W/m^2 and m/s respectively. The date of data recording is from June 2012 to October 2013, in which the temperature data is partially missing due to the instrument.
HE Zhibin
The measurement data of the sun spectrophotometer can be directly used to perform inversion on the optical thickness of the non-water vapor channel, Rayleigh scattering, aerosol optical thickness, and moisture content of the atmospheric air column (using the measurement data at 936 nm of the water vapor channel). The aerosol optical property data set of the Tibetan Plateau by ground-based observations was obtained by adopting the Cimel 318 sun photometer, and both the Mt. Qomolangma and Namco stations were involved. The temporal coverage of the data is from 2009 to 2016, and the temporal resolution is one day. The sun photometer has eight observation channels from visible light to near infrared. The center wavelengths are 340, 380, 440, 500, 670, 870, 940 and 1120 nm. The field angle of the instrument is 1.2°, and the sun tracking accuracy is 0.1°. According to the direct solar radiation, the aerosol optical thickness of 6 bands can be obtained, and the estimated accuracy is 0.01 to 0.02. Finally, the AERONET unified inversion algorithm was used to obtain aerosol optical thickness, Angstrom index, particle size spectrum, single scattering albedo, phase function, birefringence index, asymmetry factor, etc.
CONG Zhiyuan
This dataset contains the flux measurements from the Daman superstation eddy covariance system (EC) at the highest layer in the flux observation matrix from 30 May to 15 September, 2012. The site (100.37223° E, 38.85551° N) was located in a cropland (maize surface) in Daman irrigation district, which is near Zhangye, Gansu Province. The elevation is 1556.06 m. The EC was installed at a height of 34 m; 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. Raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including 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. Moreover, 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), which was proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), representing high-, medium-, and low-quality data, respectively. 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 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; the missing data were replaced with -6999. Moreover, 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/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), 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 *.xlsx format. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, XU Ziwei
The data set contains the flux observation data of large aperture scintillator from daman station in the middle reaches of heihe hydrometeorological observation network.The large aperture scintiometer of German BLS450_NQ and Dutch Kipp&zonen models has been installed at the dameng station in the middle reaches. The north tower is the receiving end of Kipp&zonen and the transmitting end of BLS450_NQ, and the south tower is the transmitting end of Kipp&zonen and the receiving end of BLS450_NQ.The observation period of BLS450_NQ is from January 1, 2014 to December 31, 2014, and the observation period of Kipp&zonen is from January 1, 2014 to March 1, 2014.The station is located in dazman irrigation district, zhangye city, gansu province. The underlying surface involves corn, orchards and greenhouses, but mainly corn.The latitude and longitude of the north tower is 100.379 E, 38.861 N, and the latitude and longitude of the south tower is 100.369 E, 38.847 N, with an altitude of about 1556m.The effective height of the large aperture scintillator is 22.45m, the optical diameter length is 1854m, and the sampling frequency is 1min. Large aperture flicker meter raw observation data for 1 min, data released for 30 min after processing and quality control of data, including sensible heat flux is mainly combined with the automatic meteorological station observation data, based on similarity theory alonzo mourning - Mr. Hoff is obtained by iterative calculation, the quality control of the main steps include: (1) excluding Cn2 reach saturation data (BLS450_NQ: Cn2 > 1.43 e-13, Kipp&zonen: Cn2 e-13 > 1.54);(2) data with weak demodulation signal strength were eliminated (BLS450_NQ: Mininum X<50, Kipp&zonen: Demod>-20mv);(3) data at the time of precipitation were excluded;(4) data of weak turbulence under stable conditions were excluded (u* < 0.1m/s).In the iterative calculation process, for BLS450_NQ, the stability universal function of Thiermann and Grassl, 1992 was selected.For Kipp&zonen, take Andreas 1988's stability universal function.Please refer to Liu et al.(2011, 2013) for detailed introduction. Some notes on the released data :(1) the data of mid-range LAS is mainly BLS450_NQ, the missing moment is supplemented by Kipp&zonen observation, and the missing of both is marked by -6999.(2) missing period: on June 21, 2014, solstice, 27, due to the lack of data from the automatic meteorological station, the sensible heat flux H_LAS observed at LAS during this period could not be calculated;On June 29, 2014, solstice on July 2, July 21, solstice 22, September 24, solstice 25, and December 21, solstice 30, data was missing due to LAS instrument failure.(3) data table head: Date/Time: Date/Time (format: yyyy-m-d h:mm), Cn2: structural parameters of air refraction index (unit: m-2/3), H_LAS: sensible heat flux (unit: W/m2).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 Li et al.(2013) for hydrometeorological network or site information, and Liu et al.(2011) for observation data processing.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
Solar radiation data were obtained using the internationally accepted solar radiation meter (LI200SZ, LI-COR, Inc., USA). The measured data are total solar radiation, including direct and diffuse solar radiation, with a wavelength range of 400-1100 nm. The units of the measurement results are W/㎡, and the typical error under natural lighting is ±3% (within an incident angle of 60°). Data from different locations in the three poles (Everest Station and Namco Station on the Tibetan Plateau, Sodankylä Station in the Arctic, and Dome A Station in the Antarctic) are derived from site cooperation and website downloads. The temporal coverage of data from the Everest Station and Namco Station on the Tibetan Plateau is from 2009 to 2016, that from the Sodankylä Station in the Arctic is from 2001 to 2017, and that from the Dome A Station in the Antarctic is from 2005 to 2014.
BAI Jianhui
The dataset contains the observation data of 10m tower vortex correlator on January 1, 2014, solstice, December 31, 2014.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 eddy correlation instrument is 10Hz, the frame height is 5m, the ultrasonic direction is due to the north, and the distance between the ultrasonic anemometer (Gill&CSAT3 (replaced on October 9, 2014) and the CO2/H2O analyzer (Li7500A) is 18cm (15cm after October 9). 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), Angle correction, 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.Data missing due to power converter damage. 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.
LIU Shaomin, XU Ziwei
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。
LIU Shaomin, XU Ziwei
Contact Support
Northwest Institute of Eco-Environment and Resources, CAS
0931-4967287
poles@itpcas.ac.cn
Links
National Tibetan Plateau Data CenterFollow Us
A Big Earth Data Platform for Three Poles © 2018-2020 No.05000491 | All Rights Reserved
｜ 
No.11010502040845
Tech Support: westdc.cn
