This dataset includes the temperature, precipitation, relative humidity, wind speed, wind direction and other daily values in the observation point of Shiquan River Source. The data is observed from July 2, 2012 to August 5, 2014, and from September 30, 2015 to December 25, 2015. It is measured by automatic meteorological station (Onset Company) and a piece of data is recorded every 2 hours. The original data forms a continuous time series after quality control, and the daily mean index data is obtained through calculation. The original data meets the accuracy requirements of China Meteorological Administration (CMA) and the World Meteorological Organization (WMO) for meteorological observation. Quality control includes eliminating the systematic error caused by the missing point data and sensor failure. The data is stored as an excel file.
ZHANG Yinsheng
1.The data content: air temperature, relative humidity, precipitation, air pressure, wind speed and vapor pressure. 2. Data sources and processing methods: campel mountain type automatic meteorological station observation by the United States, including air temperature and humidity sensor model HMP155A;Wind speed and direction finder models: 05103-45;The atmospheric pressure sensor: CS106;The measuring cylinder: TE525MM.Automatic meteorological station every ten minutes automatic acquisition data, after complete automatic acquisition daily meteorological data then daily mean value were calculated statistics. 3.Data quality description: automatic continuous access to data. 4.Data application results and prospects: the weather stations set in the upper of the glacier terminal, meteorological data can be used to simulate for predict the future climate change under the background of type Marine glacial changes in response to global climate change research provides data.
LIU Jing
The data set contains the meteorological element observation data of ebao station in the upper reaches of heihe hydrometeorological observation network on January 1, 2015 and December 31, 2016.The station is located in ebao town, qilian county, qinghai province.The longitude and latitude of the observation point are 100.9151E, 37.9492N, and the altitude is 3294m.The air temperature and relative humidity sensor is set up at 5m, facing due north.The barometer is installed in the anti-skid box on the ground;The tipping bucket rain gauge is installed at 10m;The wind speed and direction sensor is mounted at 10m, facing due north;The four-component radiometer is installed at 6m, facing due south;Two infrared thermometers are installed at 6m, facing south, with the probe facing vertically downward;The soil temperature probe is buried at the surface of 0cm and underground of 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm, 2m south of the meteorological tower.The soil moisture probe is buried underground at 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm, 2m south of the meteorological tower.The soil heat flow plates (3 pieces) are successively buried 6cm underground, 2m south of the meteorological tower. Observation projects are: air temperature and humidity (Ta_5m, RH_5m) (unit: c, percentage), pressure (Press) (unit: hundred mpa), precipitation (Rain) (unit: mm), wind speed (WS_10m) (unit: m/s), wind (WD_10m) (unit: degrees), the radiation of four component (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts per square meter), the surface radiation temperature (IRT_1, IRT_2) (unit:C), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: wattage/m2), soil temperature (Ts_0cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm) (unit: water content by volume, percentage). Processing and quality control of observation data :(1) 144 data per day (every 10min) should be ensured.The four-component radiation and infrared temperature were between October 11, 2015 and November 5, 2015.The instrument of the observation tower was re-adjusted between 11.1 and 11.5, and the data was missing;(2) eliminate the moments with duplicate records;(3) data that obviously exceeds the physical significance or the range of the instrument is deleted;(4) the part marked with red letters in the data is questionable data;(5) the format of date and time is uniform, and the date and time are in the same column.For example, the time is: 2015-9-10 10:30;(6) naming rules: AWS+ site name. 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
The data set contains the meteorological element observation data of jingyangling station in the upper reaches of heihe hydrometeorological observation network on January 1, 2015 and December 31, 2017.The site is located in pass, jingyangling mountain, qilian county, qinghai province.The longitude and latitude of the observation point are 101.1160E, 37.8384N and 3750m above sea level.The air temperature and relative humidity sensor is set up at 5m, facing due north.The barometer is installed in the anti-skid box on the ground;The tipping bucket rain gauge is installed at 10m;The wind speed and direction sensor is mounted at 10m, facing due north;The four-component radiometer is installed at 6m, facing due south;Two infrared thermometers are installed at 6m, facing south, with the probe facing vertically downward;The soil temperature probe is buried at the surface of 0cm and underground of 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm, 2m south of the meteorological tower.The soil moisture probe is buried underground at 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm, 2m south of the meteorological tower.The soil heat flow plates (3 pieces) are successively buried 6cm underground, 2m south of the meteorological tower. Observation projects are: air temperature and humidity (Ta_5m, RH_5m) (unit: c, percentage), pressure (Press) (unit: hundred mpa), precipitation (Rain) (unit: mm), wind speed (WS_10m) (unit: m/s), wind (WD_10m) (unit: degrees), the radiation of four component (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts per square meter), the surface radiation temperature (IRT_1, IRT_2) (unit:Soil temperature (Ts_0cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm) (unit: percent). Processing and quality control of observation data :(1) 144 data per day (every 10min) should be ensured.(2) eliminate the moments with duplicate records;(3) data that obviously exceeds the physical significance or the range of the instrument is deleted;(4) the part marked with red letters in the data is questionable data;(5) the format of date and time is uniform, and the date and time are in the same column.For example, the time is: 2015-9-10 10:30;(6) naming rules: AWS+ site name. 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 data set contains the data of meteorological elements observed in the pass station upstream of heihewen meteorological observation network on January 1, 2015 and December 31, 2015.The site is located in da dong shu pass, qilian county, qinghai province.The longitude and latitude of the observation point are 100.2421E, 38.0142N, and the altitude is 4148m.Data including two observation points, all in pass observatory, located about 10 m, a set of continuous observation in 2015 (30 min output), another set for September 18, 2015 in 10 m high pass new stations (10 min), specific include: air temperature, relative humidity sensors at 5 m, toward the north (two sets of observation, 10 min and 30 min output);The barometer is installed in the skid-proof box on the ground (two groups of observation, 10min and 30min output respectively);The tipping bucket rain gauge is installed at 10m;The wind speed and direction sensor is mounted at 10m, facing due north (two groups, 10min and 30min output respectively).The four-component radiometer consists of two observation points, one is installed at the meteorological tower 6m, facing due south (10min output), and the other is installed on the support 1.5m above the ground (30min output).Two infrared thermometers are installed at 6m, facing south, with the probe facing vertically downward;The soil temperature probe was buried at 0cm on the surface and 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm underground (the two groups were observed for 10min and 30min respectively).The soil moisture probe was buried in the ground at 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm (the two groups were observed for 10min and 30min respectively).The soil heat flow plate was buried 6cm underground (observed in two groups, 10min (3 heat flow plates) and 30min (2 heat flow plates)). Observation projects are: air temperature and humidity (Ta_5m, RH_5m) (unit: c, percentage), pressure (Press) (unit: hundred mpa), precipitation (Rain) (unit: mm), wind speed (WS_10m) (unit: m/s), wind (WD_10m) (unit: degrees), the radiation of four component (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts per square meter), the surface radiation temperature (IRT_1, IRT_2) (unit:C), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: wattage/m2), soil temperature (Ts_0cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm) (unit: water content by volume, percentage). Processing and quality control of observation data :(1) 144 or 48 data per day (every 10min or 30min) should be ensured.The four-component long-wave radiation output of 30min was between January 1, 2015 and January 1, 2015.The observation data was lost between 5.24 and 7.12 after 30min due to the collector problem.(2) eliminate the moments with duplicate records;(3) data that obviously exceeds the physical significance or the range of the instrument is deleted;(4) the part marked with red letters in the data is questionable data;(5) the format of date and time is uniform, and the date and time are in the same column.For example, the time is: 2015-9-10 10:30;(6) naming rules: AWS+ site name. 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
The data set is the average wind speed of the Central Asia including three temperate deserts, the Karakum, Kyzylkum and Muyunkun Deserts, and one of the world's largest arid zones. The data was obtained by GLDAS global three-hour assimilation data extraction calculation. The data is in tif format. The space and time resolutions are 0.25° and 3 hours respectively. The time is from 01, January, 2017 to 31, December, 2017. The data set uses the the Geodetic coordinate system. We can use the data to calculate the sand flux. It can be used for the investigation of the Desert oil and gas field, and oasis cities.
GAO Xin
This data set includes the daily values of temperature, pressure, relative humidity, wind speed, wind direction, precipitation, radiation, and water vapor pressure observed from 22 international exchange stations in Sri Lanka from January 1, 2008 to October 1, 2018. The data was downloaded from the NCDC of NOAA. The data set processing method is that the original data is quality-controlled to form a continuous time series. It satisfies the accuracy of the original meteorological observation data of the National Weather Service and the World Meteorological Organization (WMO), and eliminates the systematic error caused by the failure of the tracking data and the sensor. The meteorological site information contained in this dataset is as follows: LATITUDE LONGITUDE ELEVATION  COUNTRY  STATION NAME +09.800  +080.067   +0015.0   SRI LANKA  KANKASANTURAI +09.650  +080.017   +0003.0   SRI LANKA  JAFFNA +09.267  +080.817   +0002.0   SRI LANKA  MULLAITTIVU +08.983  +079.917   +0003.0   SRI LANKA  MANNAR +08.750  +080.500   +0098.0   SRI LANKA  VAVUNIYA +08.539  +081.182   +0001.8   SRI LANKA  CHINA BAY +08.301  +080.428   +0098.8   SRI LANKA  ANURADHAPURA +08.117  +080.467   +0117.0   SRI LANKA  MAHA ILLUPPALLAMA +08.033  +079.833   +0002.0   SRI LANKA  PUTTALAM +07.706  +081.679   +0006.1   SRI LANKA  BATTICALOA +07.467  +080.367   +0116.0   SRI LANKA  KURUNEGALA +07.333  +080.633   +0477.0   SRI LANKA  KANDY +07.181  +079.866   +0008.8   SRI LANKA  BANDARANAIKE INTL COLOMBO +06.900  +079.867   +0007.0   SRI LANKA  COLOMBO +06.822  +079.886   +0006.7   SRI LANKA  COLOMBO RATMALANA +06.967  +080.767   +1880.0   SRI LANKA  NUWARA ELIYA +06.883  +081.833   +0008.0   SRI LANKA  POTTUVIL +06.817  +080.967   +1250.0   SRI LANKA  DIYATALAWA +06.983  +081.050   +0667.0   SRI LANKA  BADULLA +06.683  +080.400   +0088.0   SRI LANKA  RATNAPURA +06.033  +080.217   +0013.0   SRI LANKA  GALLE +06.117  +081.133   +0020.0   SRI LANKA  HAMBANTOTA
DENG Chuangwu
The data set contains the data of the meteorological element gradient observation system of the upper reaches of the heihe hydrological and meteorological observation network's arou super station 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 air temperature, relative humidity and wind speed sensors are installed at 1m, 2m, 5m, 10m, 15m and 25m, respectively. There are 6 floors in total, facing due north.Wind direction sensor is mounted at 10m, facing due north;The barometer is installed at 2m;The tilting rain gauge is installed on the 40m observation tower of the super station in aru.The four-component radiometer is installed at 5m, facing due south;Two infrared thermometers are mounted at 5m, facing due south, with the probe facing down vertically;The photosynthetic effective radiometer was installed at 5m, facing south, and the probe direction was vertical upward.Part of the soil sensor is buried 2m away from the south of the tower, and the soil heat flow plate (self-calibration) (3 pieces) are all buried 6cm underground.Mean soil temperature sensor (tcavr) was buried 2cm and 4cm underground.The soil temperature probe is buried at the surface 0cm and underground 2cm, 4cm, 6cm, 10cm, 15cm, 20cm, 30cm, 40cm, 60cm, 80cm, 120cm, 160cm, 200cm, 240cm, 280cm and 320cm. There are three duplicates in the two layers of 4cm and 10cm.The soil moisture sensor was buried in the ground at 2cm, 4cm, 6cm, 10cm, 15cm, 20cm, 30cm, 40cm, 60cm, 80cm, 120cm, 160cm, 200cm, 240cm, 280cm and 320cm respectively, and there were three replications in the two layers of 4cm and 10cm. Observation items include: wind speed (WS_1m, WS_2m, WS_5m, WS_10m, WS_15m, WS_25m) (unit: m/s), wind direction (WD_10m) (unit: degrees), air temperature and humidity (Ta_1m, Ta_2m, Ta_5m, Ta_10m, Ta_15m, Ta_25m and RH_1m, RH_2m, RH_5m, RH_10m, RH_5m) (unit: Celsius, percentage), air pressure (Press) (unit:Hundred mpa), precipitation (Rain) (unit: mm), the radiation of four component (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts per square meter), the surface radiation temperature (IRT_1, IRT_2) (unit: c), photosynthetic active radiation (PAR) (unit: second micromoles/m2), the average soil temperature (TCAV) (unit: c), soil heat flux (Gs_1, Gs_2, Gs_3) (unit:W/m2), soil moisture (Ms_2cm, Ms_4cm_1, Ms_4cm_2, Ms_4cm_3, Ms_6cm, Ms_10cm_1, Ms_10cm_2, Ms_10cm_3, Ms_15cm, Ms_20cm, Ms_30cm, Ms_60cm, Ms_80cm, Ms_120cm, Ms_160cm, Ms_280cm, Ms_320cm) (unit:Soil temperature (Ts_0cm, Ts_2cm, Ts_4cm_1, Ts_4cm_2, Ts_4cm_3, Ts_6cm, Ts_10cm_1, Ts_10cm_2, Ts_15cm, Ts_20cm, Ts_30cm, Ts_60cm, Ts_80cm, Ts_120cm, Ts_160cm, Ts_280cm, Ts_320cm) (unit:Degrees Celsius. Processing and quality control of observation data :(1) 144 data per day (every 10min) should be ensured.The data of soil temperature and humidity and soil heat flux were missing between September 9, 2015 and September 19, 2015 and between September 30 and October 20, 2015 due to power supply problems.(2) eliminate the moments with duplicate records;(3) data that obviously exceeds the physical significance or the range of the instrument is deleted;(4) the part marked with red letters in the data is questionable data;(5) the format of date and time is uniform, and the date and time are in the same column.For example, the time is: June 10, 2015 10:30;(6) naming rules: AWS+ site name. 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 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
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
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