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
This dataset is derived from the Nagqu Station of Plateau Climate and Environment (31.37N, 91.90E, 4509 a.s.l), Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences. The ground is flat, with open surrounding terrain. An uneven growth of alpine steppe, with a height of 3–20 cm. The observation time of this dataset is from January 1, 2014 to December 31, 2017. The observation elements primarily included the wind speed, air temperature, air relative humidity, air pressure, downward shortwave radiation, precipitation, evaporation, latent heat flux and CO2 flux. The precipitation , evaporation and CO2 flux data are daily cumulative values, and the other variables are daily average values. The observed data are generally continuous, but some data are missing due to power supply failure, and the missing data in this dataset are marked as NAN.
HU Zeyong, GU Lianglei, SUN Fanglei, WANG Shujin
CMADS V1.0(The China Meteorological Assimilation Driving Datasets for the SWAT model Version 1.0)Version of the data set introduces the technology of 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, air pressure, humidity, and wind velocity data 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, average pressure, maximum and minimum temperature, specific humidity, cumulative precipitation, and average wind velocity. The CMADS comprises other variables for any hydrological model（under 'For-other-model' folder ）: Daily Average Temperature, Daily Maximum Temperature, Daily Minimum Temperature, Daily cumulative precipitation (20-20h), Daily average Relative Humidity, Daily average Specific Humidity, Daily average Solar Radiation, Daily average Wind, 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 temperature(℃) Wind-58500\ Daily average 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 temperature(℃) Maximum-Temperature-txt\ Daily maximum temperature(℃) Minimum-Temperature-txt\ Daily minimum 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 wind speed(m/s) Data storage information: data set storage format is .dbf and .txt Other data information: Total data: 33.6GB Occupied space: 35.2GB Time: From year 2008 to year 2016 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
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
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 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 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 meteorological data set of Beiluhe station mainly includes 7 meteorological elements such as atmospheric temperature, wind speed, wind direction, humidity, atmospheric pressure, solar radiation and daily rainfall of 2m. The monitoring station of the data set is located at 92 ° E, 35 ° N and 4600m above sea level. The terrain of the monitoring site is flat, and the vegetation type is alpine meadow. The measuring sensors are manufactured by Campell company, of which the measurement of high temperature and humidity is transmitted The sensor model is HMP45C, the wind speed and direction sensor model is 05103, the atmospheric pressure measurement sensor model is ptb-210, the solar radiation sensor model is nr01, the rain gauge sensor model is t-200b, the time interval of this data set is 1 day, which is obtained through the calculation of 30 minute data. During the monitoring period, the data is stable and continuous. Through the analysis of meteorological data, we can recognize Beilu river The change of local climate is not only helpful, but also an indispensable index in the study of frozen soil environment and engineering.
CHEN Ji
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 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
This data is the water level data of 2011-2012, which is observed by water level recorder. From July 14 to September 9, 2011, the observation was recordered every five minutes; from June 4 to July 10, 2012, the observation was recordered every ten minutes. The data content is the temperature and atmospheric pressure inside the hole, and the data is the daily scale data. The data shall be opened with HOBO software.
ZHAO Chuanyan, MA Wenying
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: 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
This dataset contains data for comprehensive monitoring in the small watershed of Sumu Jaran in the Badain Jaran Desert from 2012 to 2013. The small watershed of Sumu Jaran is composed of two lakes, namely North Lake and South Lake of Sumu Jaran. The latitude and longitude range is: 39° 46' 18.24" to 39° 49' 17.25" north latitude, 102° 23' 40.53 " to 102° 26' 59.27" east longitude. The observation instruments are mainly arranged around the South Lake of Sumu Jaran, including scintillator (BLS450), automatic weather station (net radiation, rainfall, wind speed, wind direction, air humidity, pressure, E601 type evaporation dish), soil monitoring station (soil temperature, water content and tension pF-meter) and one groundwater monitoring hole. The data released this time are the monitoring results from September 2012 to December 2013. Post-monitoring data will be released in version 2.0. For the layout, coordinates, and type of the instrument, see the layout of the small watershed monitoring system.pdf, coordinates of the monitoring point.xls, and location and equipment of the monitoring point.tif.
HU Xiaonong, WANG Xusheng
This data set includes daily average data of atmospheric temperature, relative humidity, precipitation, wind speed, wind direction, net radiance, and atmospheric pressure from 1 January 2007 to 31 December 2016 derived from the Integrated Observation and Research Station of the Alpine Environment in Southeast Tibet. The data set has been used by students and researchers in the fields of meteorology, atmospheric environment and ecological research. The units of the various meteorological elements are as follows: temperature °C; precipitation mm; relative humidity %; wind speed m/s; wind direction °; net radiance W/m2; pressure hPa; and particulate matter with aerodynamic diameter less than 2.5 μm μg/m3. All the data are the daily averages calculated from the raw observations. Observations and data collection were carried out in strict accordance with the instrument operating specifications and the guidelines published in relevant academic journals; data with obvious errors were eliminated during processing, and null values were used to represent the missing data. In 2015, due to issues related to the age of the observation probe at the station, only the wind speed data for the last 8 months were retained.
Luo Lun
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