This dataset includes data recorded by the Heihe integrated observatory network obtained from an observation system of Meteorological elements gradient of Daman Superstation from January 1 to December 31, 2018. The site (100.372° E, 38.856° N) was located on a cropland (maize surface) in the Daman irrigation, which is near Zhangye city, Gansu Province. The elevation is 1556 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (AV-14TH;3, 5, 10, 15, 20, 30, and 40 m, towards north), wind speed and direction profile (windsonic; 3, 5, 10, 15, 20, 30, and 40 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 2.5 m, 8 m in west of tower), four-component radiometer (PIR&PSP; 12 m, towards south), two infrared temperature sensors (IRTC3; 12 m, towards south, vertically downward), photosynthetically active radiation (LI190SB; 12 m, towards south, vertically upward; another four photosynthetically active radiation, PQS-1; two above the plants (12 m) and two below the plants (0.3 m), towards south, each with one vertically downward and one vertically upward), soil heat flux (HFP01SC; 3 duplicates with G1 below the vegetation; G2 and G3 between plants, -0.06 m), a TCAV averaging soil thermocouple probe (TCAV; -0.02, -0.04 m), soil temperature profile (AV-10T; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), soil moisture profile (CS616; -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m). The observations included the following: air temperature and humidity (Ta_3 m, Ta_5 m, Ta_10 m, Ta_15 m, Ta_20 m, Ta_30 m, and Ta_40 m; RH_3 m, RH_5 m, RH_10 m, RH_15 m, RH_20 m, RH_30 m, and RH_40 m) (℃ and %, respectively), wind speed (Ws_3 m, Ws_5 m, Ws_10 m, Ws_15 m, Ws_20 m, Ws_30 m, and Ws_40 m) (m/s), wind direction (WD_3 m, WD_5 m, WD_10 m, WD_15 m, WD_20 m, WD_30m, and WD_40 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation (PAR) (μmol/ (s m-2)), average soil temperature (TCAV, ℃), soil heat flux (Gs_1, below the vegetation; Gs_2, and Gs_3, between plants) (W/m^2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm, and Ts_160 cm) (℃), soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, and Ms_160 cm) (%, volumetric water content), above the plants photosynthetically active radiation of upward and downward (PAR_U_up and PAR_U_down) (μmol/ (s m-2)), and below the plants photosynthetically active radiation of upward and downward (PAR_D_up and PAR_D_down) (μmol/ (s m-2)). 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.The meterological data during September 17 and November 7 and TCAV data after November 7 were wrong because the malfunction of datalogger. The missing data were denoted 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: 2018-6-10 10:30. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) for data processing) in the Citation section.
LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
This dataset contains the flux measurements from site No.16 eddy covariance system (EC) in the flux observation matrix from 6 June to 17 September, 2012. The site (100.36411° E, 38.84931° N) was located in a cropland (maize surface) in Daman irrigation district, which is near Zhangye, Gansu Province. The elevation is 1564.31 m. The EC was installed at a height of 4.9 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 (Gill&Li7500) was 0.2 m. Raw data acquired at 10 Hz were processed using the Eddypro post-processing software (Li-Cor Company, http://www.licor.com/env/products/ eddy_covariance/software.html), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, angle of attack 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 site No.7 eddy covariance system (EC) in the flux observation matrix from 29 May to 18 September, 2012. The site (100.36521° E, 38.87676° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1556.39 m. The EC was installed at a height of 3.8 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 0.15 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 includes meteorological data from the Ngari Desert Observation and Research Station from 2009 to 2017. It includes the following basic meteorological parameters: temperature (1.5 m from the ground, once every half hour, unit: Celsius), relative humidity (1.5 m from the ground, once every half hour, unit: %), wind speed (1.5 m from the ground, once every half hour, unit: m/s), wind direction (1.5 m from the ground, once every half hour, unit: degrees), atmospheric pressure (1.5 m from the ground, once every half hour, unit: hPa), precipitation (once every 24 hours, unit: mm), water vapour pressure (unit: kPa), evaporation (unit: mm), downward shortwave radiation (unit: W/m2), upward shortwave radiation (unit: W/m2), downward longwave radiation (unit: W/m2), upward longwave radiation (unit: W/m2), net radiation (unit: W/m2), surface albedo (unit: %). The temporal resolution of the data is one day. The data were directly downloaded from the Ngari automatic weather station. The precipitation data represent daily precipitation measured by the automatic rain and snow gauge and corrected based on manual observations. The other observation data are the daily mean value of the measurements taken every half hour. Instrument models of different observations: temperature and humidity: HMP45C air temperature and humidity probe; precipitation: T200-B rain and snow gauge sensor; wind speed and direction: Vaisala 05013 wind speed and direction sensor; net radiation: Kipp Zonen NR01 net radiation sensor; atmospheric pressure: Vaisala PTB210 atmospheric pressure sensor; collector model: CR 1000; acquisition interval: 30 minutes. The data table is processed and quality controlled by a particular person based on observation records. Observations and data acquisition are carried out in strict accordance with the instrument operating specifications, and some data with obvious errors are removed when processing the data table.
ZHAO Huabiao
The hydrological ecological process at the loess basin scale and its response to global climate change is a project of the Major Research plan of the National Natural Science Foundation of China - Environmental and Ecological Science in Western China. The project is led by liu wenzhao, a researcher from the institute of water and soil conservation, ministry of water resources, Chinese academy of sciences. The project runs from January 2003 to December 2005. The project submitted data: The CLIGEN parameter and output dataset of the Loess Plateau: It was generated during the evaluation and improvement of the practicality of the weather generator CLIGEN in the Loess Plateau. The dataset includes parameter data files for driving CLIGEN and 100-year daily weather data files generated by running CLIGEN from 71 meteorological stations on the Loess Plateau. The 71 sites are distributed in 7 provinces (Shanxi, Shanxi, Gansu, Inner Mongolia, Ningxia, Henan, and Qinghai). Each file is individually saved in ASCII format and can be opened for viewing with text programs. This data set is generated based on long-term serial daily meteorological data measured by 71 meteorological stations on the Loess Plateau. Daily meteorological parameters include: precipitation, maximum, minimum, and average temperature, solar radiation, relative humidity, wind speed and direction. The data comes from the China Meteorological Science Data Sharing Service Network and the Loess Plateau Soil and Water Conservation Database. Among them, solar radiation data is available at only 12 sites on the Loess Plateau. The solar radiation parameters at other sites are generated by kriging space interpolation. The dew point temperature is calculated using the average temperature and relative humidity.
LIU Wenzhao
The data set contains meteorological observations from Guoluo Station from January 1, 2017, to December 31, 2017, and includes temperature (Ta_1_AVG), relative humidity (RH_1_AVG), vapour pressure (Pvapor_1_AVG), average wind speed (WS_AVG), atmospheric pressure (P_1), average downward longwave radiation (DLR_5_AVG), average upward longwave radiation (ULR_5_AVG), average net radiation (Rn_5_AVG), average soil temperature (Ts_TCAV_AVG), soil water content (Smoist_AVG), total precipitation (Rain_7_TOT), downward longwave radiation (CG3_down_Avg), upward longwave radiation (CGR3_up_Avg), average photosynthetically active radiation (Par_Avg), etc. The temporal resolution is 1 hour. Missing observations have been assigned a value of -99999.
HU Linyong
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
Based on the geostationary satellites and reanalysis data, the China Regional Atmospheric Driving Dataset is a set of atmospheric driving data sets with high spatiotemporal resolution prepared by the China Meteorological Administration, with a spatial resolution of 0.1 ° × 0.1 ° and a temporal resolution of 1 Hours, covering a range of 75 ° -135 ° east longitude and 15 ° -55 ° north latitude, include 6 elements of near-surface temperature, relative humidity, ground pressure, near-surface wind speed, incident solar radiation on the ground, and ground precipitation rate. The preparation process of precipitation products is as follows: The 6-hour cumulative precipitation estimated from the multi-channel data of the China Fengyun-2 geostationary satellite is integrated with the 6-hour cumulative precipitation from conventional ground observations to obtain 6-hour cumulative precipitation spatial distribution data, and then use the high-resolution cloud classification information retrieved from the multi-channel inversion of the geostationary satellites determines the interpolation time weight of the cumulative precipitation and obtains an estimated one-hour cumulative precipitation. The preparation process of the radiation data is as follows: The surface incident solar radiation based on FY-2C, uses the radiation transmission model DISORT (Discrete Ordinates Radiative Transfer Program for a Multi-Layered Plane-parallel Medium) to calculate the radiation transmission and obtains the data of surface incident solar radiation in China. Preparation process of other elements: The space and time interpolation method is used for the NCEP reanalysis data of 1.0 ° × 1.0 ° to obtain driving factors such as near-surface air temperature, relative humidity, ground pressure, and near-surface wind speed of 0.1 ° × 0.1 ° per hour. Physical meaning of each variable: Meteorological Elements || Variable Name || Unit || Physical Meaning | Surface temperature || TBOT || K || Surface temperature (2m) | Surface pressure || PSRF || Pa || Surface pressure | Relative humidity on the ground || RH || kg / kg || Relative humidity near the ground (2m) | Wind speed on the ground || WIND || m / s || Wind speed near the ground (anemometer height) | Surface incident solar radiation || FSDS || W / m2 || Surface incident solar radiation | Precipitation Rate || PRECTmms || mm / hr || Precipitation Rate For more information, see the data documentation published with the data.
SHI Chunxiang
The research project on land surface data assimilation system in western China belongs to the major research plan of "environment and ecological science in western China" of the national natural science foundation. the person in charge is Li Xin, researcher of the institute of environment and engineering in cold and arid regions of the Chinese academy of sciences. the project runs from January 2003 to December 2005. One of the data collected in this project is the reanalysis data of surface climate factors in western China in 2002. This data set is generated based on the daily 1 × 1 provided by the National Environmental Prediction Center (NCEP). However, the re-analysis of the data has the following problems: (1) the temporal and spatial resolution is not high enough (the horizontal resolution is 1 degree and the time is 6 hours); (2) The low-level errors in plateau areas are large; (3) The data are standard isosurface data and need interpolation. The 2002 reanalysis data set of surface climate elements in western China was generated by combining NCEP reanalysis data and MM5 model by Dr. Longxiao and Professor Qiu Chongjian of Lanzhou University using Newton relaxation data assimilation method (Nudging), including 10m horizontal and vertical wind speed (m/s), 2m air temperature (k), 2m mixing ratio, surface pressure (Pa), upstream and downstream short wave and long wave radiation (w/m2), convective precipitation and large scale precipitation (mm/s) at 0.25 degree per hour throughout 2002. I. preparation background The quality of the driving data seriously affects the ability of the land surface model to simulate the land surface state, so a very important component of the land surface modeling research is the driving data used to drive the land surface model. No matter how realistic these models are in describing the surface process, no matter how accurate the boundary and initial conditions they input, if the driving data are not accurate, they cannot get the results close to reality. Land surface models are so dependent on the quality of externally provided data that any error in these externally provided data will seriously affect the ability of land surface models to simulate soil moisture, runoff, snow cover and latent heat flux. These externally provided data include: precipitation, radiation, temperature, wind field, humidity and pressure. The 2002 reanalysis data set of surface climate elements in western China uses Newton relaxation data assimilation method (Nudging) to combine NCEP reanalysis data and MM5 model to generate driving data with higher spatial and temporal resolution suitable for complex terrain in western China. Second, the basic parameters of the operation mode 1. Using the US PSU/NCAR mesoscale model MM5 as a simulation model; The selection of simulation grid domain: center (32°N, 90°E), grid distance of 36km, number of horizontal grid points of 131*151, vertical resolution of 25 layers, and mode top of 100hPa；; 2. The data used for initialization are 1 * 1 GRIB grid data of NCEP in the United States. 3. The time step is 120s. Third, the physical process 1. physical process treatment of cloud and precipitation: Grell cumulus cloud parameterization scheme is adopted for sub-grid scale precipitation, and Reisner mixed phase microphysical explicit scheme is adopted for distinguishable scale precipitation; 2. MRF parameterization scheme is adopted for planetary boundary layer process. 3. the radiation process adopts CCM2 radiation scheme. IV. File Format and Naming It is stored in a monthly folder and contains 24 hours of data every day. The naming rules are as follows: 2002***&.forc, where * * * is Julian day and 2002***& is time (in hours), where. forc is the file extension. V. data format Stored in binary floating point type, each data takes up 4 bytes.
LONG Xiao, QIU Chongjian
I. overview The data set includes wind and sand activity data of Ulanbuh Desert and Kubuqi Desert along the upper Yellow River from April to May 2011 and April 2012, mainly including wind speed profile, surface roughness, wind-sand flow structure, sand transport rate data under different vegetation coverage and different parts of sand dunes. II. Data Processing Instructions The wind speed and direction are observed by 014A wind speed sensor 024A wind direction sensor and CR200 data acquisition instrument produced by MetOne company, and the sediment transport amount is observed by stepped sediment collection instrument. III. Description of Data Content The data are stored in EXCEL table, mainly including wind speed profile, surface roughness, wind-sand flow structure and sand transport rate data under different vegetation coverage. IV. Data Usage Instructions This paper evaluates the sandstorm hazards along the Yellow River, estimates the amount of sandstorm entering the Yellow River in the upper reaches of the Yellow River, and provides data support for the establishment of an early warning system for sandstorm hazards in the region.
XUE Xian, DU Heqiang
The Chinese regional surface meteorological element data set is a set of near-surface meteorological and environmental element reanalysis data set developed by the Qinghai-Tibet Plateau Research Institute of the Chinese Academy of Sciences. The data set is based on the existing Princeton reanalysis data, GLDAS data, GEWEX-SRB radiation data and TRMM precipitation data in the world, and is made by combining the conventional meteorological observation data of China Meteorological Administration. The temporal resolution is 3 hours and the horizontal spatial resolution is 0.1, including 7 factors (variables) including near-surface air temperature, near-surface air pressure, near-surface air specific humidity, near-surface full wind speed, ground downward short wave radiation, ground downward long wave radiation and ground precipitation rate. The physical meaning of each variable: | Meteorological Element || Variable Name || Unit || Physical Meaning | near-surface temperature ||temp|| K || instantaneous near-surface (2m) temperature | surface pressure || pres|| Pa || instantaneous surface pressure | specific humidity of near-surface air || shum || kg/ kg || instantaneous specific humidity of near-surface air | near ground full wind speed || wind || m /s || instantaneous near ground (anemometer height) full wind speed | downward short wave radiation || srad || W/m2 || 3-hour average (-1.5 HR ~+1.5 HR) downward short wave radiation | Downward Long Wave Radiation ||lrad ||W/m2 ||3-hour Average (-1.5 hr ~+1.5 hr) Downward Long Wave Radiation | precipitation rate ||prec||mm/hr ||3-hour average (-3.0 HR ~ 0.0 HR) precipitation rate For more information, please refer to the "User's Guide for China Meteorological Al Forcing Dataset" published with the data. The main changes in the latest version (01.06.0014) are: 1. Extend the data to December 2015 (except for short-wave and long-wave data, only until October 2015; the data from November to December 2015 are interpolated based on GLDAS data, and the error may be too large); 2. Set the minimum wind speed at 0.05 m/s; 3. Fixed a bug in the previous radiation algorithm to make our short wave and long wave data more reasonable in the morning and evening periods. 4. bug of precipitation data has been corrected, and the period involved in the change is 2011-2015.
YANG Kun, HE Jie
The station data information of 21 regular meteorological observation stations in Heihe River Basin and surrounding areas and 13 national benchmark stations around Heihe River provided by Heihe plan data management center are used to make statistics and collation of daily wind speed and calculate the monthly wind speed data of 1961-2010 for many years. The spatial stability analysis is carried out to calculate the variation coefficient. If the variation coefficient is greater than 100%, the geographical weighted regression is used to calculate the relationship between the station and the geographical terrain factors, and the monthly wind speed distribution trend is obtained; if the variation coefficient is less than or equal to 100%, the common least square regression is used to calculate the relationship between the station wind speed value and the geographical terrain factors (longitude and latitude, elevation, slope, aspect, etc.) The trend of monthly wind speed distribution is obtained, and the residual after removing the trend is fitted and corrected by HASM (high accuracy surface modeling method). Finally, the monthly average wind speed distribution of the Heihe River Basin in 1961-2010 is obtained by adding the trend surface results and the residual correction results. Time resolution: monthly average wind speed for many years from 1961 to 2010. Spatial resolution: 500M.
YUE Tianxiang, ZHAO Na
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
The meteorological field is located in 2700m grassland in the Pailougou watershed of Qilian Mountain. The date of data recording is from May 2013 to September 2013, including air humidity at 1.5m, air temperature at 3.0m, atmospheric pressure at 2.8m, precipitation at 1.3m, wind speed at 2.2m and total solar radiation at 3.1m. The units are%, ℃, PA, m, m/s and W·m-2, respectively.
HE Zhibin
1. Data overview: This data set is the daily scale meteorological gradient data of Qilian station from October 1, 2011 to December 31, 2011 (installed at the end of September 2011). The observation of vg1000 gradient observation system started on October 1, 2011, recording data every 30 mins, and finally generating daily scale data. Through the long-term monitoring of wind speed and direction, air temperature and humidity, radiation and other conventional meteorological elements, combined with high-precision, high scanning frequency data collector for data storage and processing analysis. 2. Data content: The main observation elements include four layers of air temperature, humidity and two-dimensional ultrasonic wind, rain and snow meter, eight layers of ground temperature, soil moisture, etc. 3. Space time scope: Geographic coordinates: longitude: longitude: 99 ° 52 ′ E; latitude: 38 ° 15 ′ n; altitude: 3232.3m
HAN Chuntan, CHEN Rensheng
1. Data overview: Eddy covariance system is a micrometeorological measurement method.It USES the principle of vorticity correlation to measure the material exchange and energy exchange of the atmosphere cushion surface with a fast response sensor.The core of open circuit eddy covariance system is composed of CR1000 data collector, CSAT3 3d ultrasonic wind speed and direction sensor, and li-7500 open circuit CO2/H2O gas analyzer (EC150).The eddy covariance system is a newly purchased instrument of this project, which takes a long time to order. It was installed in early October 2011, and the data is relatively short.This data set is the vorticity covariance data of qilian station from October 1, 2011 to December 31, 2011 at 30min. 2. Data content: The observation items are: horizontal wind speed Ux (m/s), horizontal wind speed Uy (m/s), vertical wind speed Uz (m/s), ultrasonic temperature Ts (Celsius), co2 concentration (mg/m^3), water vapor concentration (g/m^3), pressure press (KPa).The data sampling rate is 10Hz per second. 3. Space and time range: Geographical coordinates: longitude: 99° 52’e;Latitude: 38°15 'N;Height: 3232.3 m
CHEN Rensheng, HAN Chuntan
1. Data overview: This data set is eddy covariance Flux data of qilian station from January 1, 2013 to December 31, 2013. 2. Data content: The observation items are: horizontal wind speed Ux (m/s), horizontal wind speed Uy (m/s), vertical wind speed Uz (m/s), ultrasonic temperature Ts (Celsius), co2 concentration co2 (mg/m^3), water vapor concentration h2o (g/m^3), pressure press (KPa), etc.The data is 30min Flux data. 3. Space and time range: Geographical coordinates: longitude: 99° 52’e;Latitude: 38°15 'N;Height: 3232.3 m
CHEN Rensheng, HAN Chuntan
1. Data overview: This data set is eddy covariance Flux data of qilian station from January 1, 2012 to December 31, 2012. 2. Data content: The observation items are: horizontal wind speed Ux (m/s), horizontal wind speed Uy (m/s), vertical wind speed Uz (m/s), ultrasonic temperature Ts (Celsius), co2 concentration co2 (mg/m^3), water vapor concentration h2o (g/m^3), pressure press (KPa), etc.The data is 30min Flux data. 3. Space and time range: Geographical coordinates: longitude: 99° 52’e;Latitude: 38°15 'N;Height: 3232.3 m
CHEN Rensheng, HAN Chuntan
This data set contains the meteorological data of 45 regional stations in Zhangye area of Gansu Province from 2008 to 2009. There are two factors (air temperature and rainfall): Dongdashan forest farm and Anyang in Ganzhou district; Horseshoe temple in Sunan County; Longqu in Zhangye; Junma farm in Shandan; Mawei Lake in Gaotai; Banqiao in Linze. The observation of the three elements (wind direction, air temperature and rainfall) are: the Imperial City, the big river and recreation in Sunan County. The observation of the four elements (wind direction, wind speed, air temperature and rainfall) are: Tiancheng, Baba, luotuocheng, Xinba and Nanhua in Gaotai County; Pingchuan, Xinhua, nijiaying and yinggezui in Linze County; Jing'an, hongshawo forest farm, pingpingpingbao, Daman, alkali beach and shigangdun in Ganzhou district; Gushanzi, Longshoushan forest farm, Laojun, Liqiao, dongle, Junma first farm in Shandan County Liudun and junmachang in Qilian Mountain; Liuba, Sanbao, zhaizhaizhaizi, shuangshusi, haichaoba and dadonggan in Minle County; Xishui in Sunan County. The observation of the five factors (relative humidity, wind direction, wind speed, air temperature and rainfall) are: Yanzhishan forest farm in Shandan County; Minghua in Sunan County. The observation of the five factors (air pressure, wind direction, wind speed, air temperature and rainfall) are: Yanzhishan forest farm in Shandan County; Minghua in Sunan County. The six elements of observation (air pressure, humidity, wind direction, wind speed, air temperature and rainfall) are as follows: East top of dacha, dacha and crescent platform in Sunan County. The data recording unit shall comply with the ground meteorological observation specifications, and the data storage shall be expressed as an integer, as follows: ten times record of temperature expansion; ten times record of precipitation expansion; ten times record of wind speed expansion. The data format is ASCII text file.
Gansu meteorological bureau, Zhangye city meteorological bureau
This data set contains the observation data of Zhangye National Climate Observatory from 2008 to 2009. The station is located in Zhangye, Gansu Province, with longitude and latitude of 100 ° 17 ′ e, 39 ° 05 ′ N and altitude of 1456m. The observation items include: atmospheric wind temperature and humidity gradient observation (2cm, 4cm, 10cm, 20m and 30m), wind direction, air pressure, photosynthesis effective radiation, precipitation, radiation four components, surface temperature, multi-layer soil temperature (5cm, 10cm, 15cm, 20cm and 40cm), soil moisture (10cm, 20cm, 50cm, 100cm and 180cm) and soil heat flux (5cm, 10cm and 15cm). Please refer to the instruction document published with the data for specific header and other information.
Zhangye city meteorological bureau
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