The China Meteorological Forcing Dataset (CMFD) is a high spatial-temporal resolution gridded near-surface meteorological dataset that was developed specifically for studies of land surface processes in China. The dataset was made through fusion of remote sensing products, reanalysis dataset and in-situ observation data at weather stations. Its record starts from January 1979 and keeps extending (currently up to December 2018) with a temporal resolution of three hours and a spatial resolution of 0.1°. Seven near-surface meteorological elements are provided in CMFD, including 2-meter air temperature, surface pressure, specific humidity, 10-meter wind speed, downward shortwave radiation, downward longwave radiation and precipitation rate.
YANG Kun, HE Jie, WENJUN TANG , LU Hui, QIN Jun , CHEN Yingying, LI Xin
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 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
CMADS V1.1(The China Meteorological Assimilation Driving Datasets for the SWAT model Version 1.1) Version of the data set introduced the STMAS assimilation algorithm. It was constructed using multiple technologies and scientific methods, including loop nesting of data, projection of resampling models, and bilinear interpolation. The CMADS series of datasets can be used to drive various hydrological models, such as SWAT, the Variable Infiltration Capacity (VIC) model, and the Storm Water Management model (SWMM). It also allows users to conveniently extract a wide range of meteorological elements for detailed climatic analyses. Data sources for the CMADS series include nearly 40,000 regional automatic stations under China’s 2,421 national automatic and business assessment centres. This ensures that the CMADS datasets have wide applicability within the country, and that data accuracy was vastly improved. The CMADS series of datasets has undergone finishing and correction to match the specific format of input and driving data of SWAT models. This reduces the volume of complex work that model builders have to deal with. An index table of the various elements encompassing all of East Asia was also established for SWAT models. This allows the models to utilize the datasets directly, thus eliminating the need for any format conversion or calculations using weather generators. Consequently, significant improvements to the modelling speed and output accuracy of SWAT models were achieved. Most of the source data in the CMADS datasets are derived from CLDAS in China and other reanalysis data in the world. The integration of air temperature (2m), air pressure, humidity, and wind speed data (10m) was mainly achieved through the LAPS/STMAS system. Precipitation data were stitched using CMORPH’s global precipitation products and the National Meteorological Information Center’s data of China (which is based on CMORPH’s integrated precipitation products). The latter contains daily precipitation records observed at 2,400 national meteorological stations and the CMORPH satellite’s inversion precipitation products.The inversion algorithm for incoming solar radiation at the ground surface makes use of the discrete longitudinal method by Stamnes et al.(1988)to calculate radiation transmission. The resolutions for CMADS V1.0, V1.1, V1.2, and V1.3 were 1/3°, 1/4°, 1/8°, and 1/16°, respectively. In CMADS V1.0 (at a spatial resolution of 1/3°), East Asia was spatially divided into 195 × 300 grid points containing 58,500 stations. Despite being at the same spatial resolution as CMADS V1.0, CMADS V1.1 contains more data, with 260 × 400 grid points containing 104,000 stations. For both versions, the stations’ daily data include average solar radiation, average temperature (2m), average pressure, maximum and minimum temperature (2m), specific humidity, cumulative precipitation, and average wind speed (10m). The CMADS comprises other variables for any hydrological model(under 'For-other-model' folder): Daily Average Temperature (2m), Daily Maximum Temperature (2m), Daily Minimum Temperature (2m), Daily cumulative precipitation (20-20h), Daily average Relative Humidity, Daily average Specific Humidity, Daily average Solar Radiation, Daily average Wind (10m), and Daily average Atmospheric Pressure. Introduction to metadata of CMADS CMADS storage path description:(CMADS was divided into two datesets) 1.CMADS-V1.0 For-swat --specifically driving the SWAT model 2.CMADS-V1.0 For-other-model --specifically driving the other hydrological model(VIC,SWMM,etc.) CMADS-- For-swat-2009 folder contain:(Station and Fork ) 1).Station Relative-Humidity-58500 Daily average relative humidity(fraction) Precipitation-58500 Daily accumulated 24-hour precipitation(mm) Solar radiation-58500 Daily average solar radiation(MJ/m2) Tmperature-58500 Daily maximum and minimum 2m temperature(℃) Wind-58500 Daily average 10m wind speed(m/s) Where R, P, S, T, W+ dimensional grid number - the number of longitude grid is the station in the above five folders respectively.(Where R,P,S,T,W respective Daily average relative humidity,Daily cumulative precipitation(24h),Daily mean solar radiation(MJ/m2),Daily maximum and minimum temperature(℃) and Daily mean wind speed (m/s)) respectively.Data format is (.dbf) 2).Fork (Station index table over East Asia) PCPFORK.txt (Precipitation index table) RHFORK.txt (Relative humidity index table) SORFORK.txt (Solar radiation index table) TMPFORK.txt (Temperature index table) WINDFORK.txt (Wind speed index) CMADS-- For-swat-2012 folder contain:(Station and Fork ) Storage structure is consistency with For-swat- 2009 .However, all the data in this directory are only available in TXT format and can be readed by SWAT2012. 3) For-other-model (Includes all weather input data required by the any hydrologic model (daily).) Atmospheric-Pressure-txt Daily average atmospheric pressure(hPa) Average-Temperature-txt Daily average 2m temperature(℃) Maximum-Temperature-txt Daily maximum 2m temperature(℃) Minimum-Temperature-txt Daily minimum 2m temperature(℃) Precipitation-txt Daily accumulated 24-hour precipitation (mm) Relative-Humidity-txt Daily average relative humidity(fraction) Solar-Radiation-txt Daily average solar radiation(MJ/m2) Specific-Humidity-txt Daily average Specific Humidity(g/kg) Wind-txt Daily average 10m wind speed(m/s) Data storage information: data set storage format is .dbf and .txt Other data information: Total data:45GB Occupied space: 50GB Time: From year 2008 to year 2014 Time resolution: Daily Geographical scope description: East Asia Longitude: 60° E The most east longitude: 160°E North latitude: 65°N Most southern latitude: 0°N Number of stations: 58500 stations Spatial resolution: 1/3 * 1/3 * grid points Vertical range: None
Meng Xianyong, Wang Hao
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 dataset of automatic meteorological observations was obtained at the A'rou freeze/thaw observation station from Jul. 25, 2008 to Dec. 31, 2009, in Wawangtan pasture (E100°28′/N38°03′, 3032.8), Daban, A'rou. The experimental area, situated in the valley highland of south Babaohe river, an upper stream branch of Heihe river, with a flat and open terrain slightly sloping from southeast to southeast and hills and mountains stretching for 3km is ideal for a horizontal homogeneous underlying surface. Observation items included multilayer (2m and 10m) of the wind speed, the air temperature and air humidity, the air pressure, precipitation, four components of radiation, the multilayer soil temperature (10cm, 20cm, 40cm, 80cm, 120cm and 160cm), soil moisture (10cm, 20cm, 40cm, 80cm, 120cm and 160cm), and soil heat flux (5cm & 15cm). The raw data were level0 and the data after basic processes were level1, in which ambiguous ones were marked; the data after strict quality control were defined as Level2. The data files were named as follows: station+datalevel+AMS+datadate. Level2 or above were strongly recommended to domestic users. As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide.
HU Zeyong, MA Mingguo, Wang Weizhen, HUANG Guanghui, Zhang Zhihui, TAN Junlei
The dataset of automatic meteorological observations was obtained at the Binggou cold region hydrometerological station (N38°04′/E100°13′), south of Qilian county, Qinghai province, from Sep. 25, 2007 to Dec. 31, 2009. The experimental area with paramo and riverbed gravel, situated in the upper stream valley of Heihe river, is ideal for the flat and open terrain and hills and mountains stretching outwards. The items were multilayer (2m and 10m) of the air temperature and air humidity, the wind speed, the air pressure, precipitation, four components of radiation, the multilayer soil temperature (5cm, 10cm, 20cm, 40cm, 80cm and 120cm), soil moisture (5cm, 10cm, 20cm, 40cm, 80cm and 120cm), and soil heat flux (5cm and 15cm). The raw data were level0 and the data after basic processes were level1, in which ambiguous ones were marked; the data after strict quality control were defined as Level2. The data files were named as follows: station+datalevel+AMS+datadate. Level2 or above were strongly recommended to domestic users. The period from Sep. 25, 2007 to Mar. 12, 2008 was the pre-observing duration, during which hourly precipitation data (fragmented) and the soil temperature and soil moisture data were to be obtained. Stylized observations began from Mar. 12, 2008. As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide.
WANG Jian, CHE Tao, MA Mingguo, Wang Weizhen, LI Hongyi, HAO Xiaohua, HUANG Guanghui, Zhang Zhihui, TAN Junlei
The dataset of automatic meteorological observations was obtained at the Yingke oasis station from Nov. 5, 2007 to Oct. 31, 2009. The observation site is located in an irrigation farmland in Yingke (E100°24′37.2″/N38°51′25.7″, 1519.1m), Zhangye city, Gansu province. The experimental area, situated in the middle stream Heihe river basin and with windbreaks space of 500m from east to west and 300m from south to north, is an ideal choice for its flat and open terrain. Observation items were multilayer (2m and 10m) of the wind speed and direction, air temperature and humidity, air pressure, precipitation, four components of radiation; the surface infrared temperature; the multilayer soil temperature (10cm, 20cm, 40cm, 80cm, 120cm and 160cm), the soil moisture (10cm, 20cm, 40cm, 80cm, 120cm and 160cm), and soil heat flux (5cm & 15cm). The raw data were level0 and the data after basic processes were level1, in which ambiguous ones were marked; the data after strict quality control were defined as Level2. The data files were named as follows: station+datalevel+AMS+datadate. Level2 or above were strongly recommended to domestic users. As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide.
MA Mingguo, Wang Weizhen, TAN Junlei, HUANG Guanghui, Zhang Zhihui
The dataset of automatic meteorological observations was obtained at the Dadongshu mountain snow observation station (E100°14′/N38°01′, 4101m) from Oct. 29, 2007 to Oct. 1, 2009. The experimental area with a flat and open terrain was slightly sloping from southeast to northwest. With alpine meadow and stones, and snow in autumn, winter and spring, the landscape was ideal. Observation items were multilayer (2m and 10m) of the wind speed, the air temperature and air humidity, the air pressure, rain and snow gauges, snow depth, four components of radiation, the multilayer soil temperature (5cm, 10cm, 20cm, 40cm, 80cm, and 120cm), soil moisture (5cm, 10cm, 20cm, 40cm, 80cm, and 120cm), and soil heat flux (5cm & 15cm). The raw data were level0 and the data after basic processes were level1, in which ambiguous ones were marked; the data after strict quality control were defined as Level2. The data files were named as follows: station+datalevel+AMS+datadate. Level2 or above were strongly recommended to domestic users. As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide.
WANG Jian, CHE Tao, LI Hongyi, HAO Xiaohua
The dataset of automatic meteorological observations was obtained at the Dayekou Guantan forest station (E100°15′/N38°32′, 2835m), south of Zhangye city, Gansu province, from Oct. 1, 2007 to Dec. 31, 2009. Guantan forest station was dominated by the 15-20m high spruce and the surface was covered by 10cm deep moss. All the vegetation was in good condition. Observation items were the multilayer (2m and 10m) wind speed and direction, the air temperature and moisture, rain and snow gauges, snow depth, photosynthetically active radiation, four components of radiation from two layers (, 1.68m and 19.75 m), stem sap flow, the surface temperature, the multi-layer soil temperature (5cm, 10cm, 20cm, 40cm, 80cm and 120cm),soil moisture (5cm, 10cm, 20cm, 40cm, 80cm and 120cm) and soil heat flux (5cm & 15cm). As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide.
MA Mingguo, Wang Weizhen, TAN Junlei, HUANG Guanghui, Zhang Zhihui
The dataset of automatic meteorological observations was obtained from Jun. 1, 2008 to Dec. 31, 2009 at the Huazhaizi desert station which is located in Anyangtan (E100°19'06.9″/N38°45'54.7″), south of Zhangye city, Gansu province,. The experimental area, situated in the middle stream of Heihe river, with a flat and open terrain and sparse vegetation cover is an ideal desert observing field. Observation items included the multi-layer (2m and 10m) wind speed and direction, the air temperature, precipitation, the four components of radiation, the surface infrared temperature, the multi-layer soil temperature (5cm, 10cm, 20cm, 40cm, 80cm and 160cm), soil moisture (5cm, 10cm, 20cm, 40cm, 80cm and 160cm) and soil heat flux (5cm & 10cm). The raw data were level0 and the data after basic processes were level1; the data after strict quality control were defined as Level2. The data files were named as follows: station+datalevel+AMS+datadate.. As for detailed information, please refer to “Meteorological and Hydrological Flux Data Guide".
LI Xin, XU Ziwei
The dataset of GPS radiosonde observations was obtained at an interval of 2 seconds in the cold region hydrology experimental area in March, 2008 and the arid region hydrology experimental area from May to July, 2008. The items were the air temperature, relative humidity, air pressure, the dew temperature, the water vapor mixing ratio, latitudinal and longitudinal wind speeds, the wind speed and direction. Simultaneous with the satellite/airplane overpass, GPS radiosonde observations were carried out: Binggou watershed on Mar. 14, A'rou on Mar. 15, Binggou watershed on Mar. 15, Biandukou on Mar. 17, Binggou watershed on Mar. 22, Binggou watershed on Mar. 29, and A'rou on Apr. 1 for the upper stream experiments; Linze grassland station on May 30, Yingke oasis on Jun.1, Huazhaizi desert station on Jun. 4, Linze grassland station on Jun. 5, Linze grassland station on Jun. 6, Huazhaizi desert station on Jun. 16, Yingke oasis on Jun. 29, Binggou watershed on Jul. 5, Yingke oasis on Jul. 7, Linze grassland station on Jul. 11, and Yingke oasis at 0, 4:10, 8:09, and 12:09 on Jul. 14 for middle stream experiments.
GU Lianglei, HU Zeyong, LI Maoshan, MA Weiqiang, SUN Fanglei
The dataset of automatic meteorological observations was obtained at the Linze grassland station (E100 °04'/N39°15', 1394m) from Oct. 1, 2007 to Oct. 27, 2008. The landscape is dominated by wetland and saline land. Observation items were multilayer (2m, 4m and 10m) of the wind speed and direction, air temperature and humidity, air pressure, precipitation, four components of radiation, the surface temperature, the soil temperature (5cm, 10cm, 20cm and 40cm), and the multilayer soil temperature (2cm, 5cm and 10cm). The dataset was released at different levels: Level1 were transformed raw data and stored in .csv month by month; Level2 were processed data after correction and quality control. As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide.
HU Zeyong, MA Mingguo, Wang Weizhen, TAN Junlei, HUANG Guanghui, Zhang Zhihui
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
The dataset generated from the radiosonde observations in middle basin of Heihe River during 2012. The instrument type are RS92-SGP (Vaisala inc., Finland) or CF-06-A (Changfeng Micro-Electroinics, CHINA). Radiosondes were released during aerospace experiment, such as CASI/SAI, TASI, WIDAS sensors. Atmospheric parameters: pressure, temperature, relative humidity, wind speed and wind direction are measured or calculated at different altitude. This atmospheric parameter profiles can back up atmospheric correction in remote sensing. It can support meteorology research. Observation Site: 1. Wuxing Village: Latitude: 38°51′11.9″N，Longitude: 100°21′48.8″E，Altitude: 1563 m 2. Gaoya Hydrological Station Latitude: 39°8′7.2″N，Longitude: 100°23′59.0″E，Altitude: 1418 m 3. A’Rou Super Station Latitude: 38°03′17.9″N，Longitude: 100°27′28.1″E，Altitude: 2991 m Observation Instrument Type: RS92-SGP manufacture by Vaisala inc., Finland CF-06-A manufacture by Beijing Changfeng Micro-Electronics Technology Co., LTD, CHINA. Observation Time: Simultaneous observation time from 29 June, 2012 to 29 July, 2012 (UTC+8). Accessory data: Pressure, temperature, relative humidity, wind speed and wind direction profiles data.
TAN Junlei, MA Mingguo, Han Huibang, YU Wenping, Hu Ronghai, Zhao Jing, Wang Yan
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 dataset of sun photometer observations was obtained in Linze grassland station, the reed plot A, the saline plot B, the barley plot E, the observation stationof the Linze grassland foci experimental areaand Jingdu hotel of Zhangye city. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired by CE318 from May 30 to Jun. 11, 2008. And from Jun. 15 to Jul.11, the data of 1640nm, 1020nm, 936nm, 870nm, 670nm, 550nm, 440nm, 380nm and 340nm were acquired. Both measurements were carried out at intervals of 1 minute. Optical depth, rayleigh scattering, aerosol optical depth, the horizontal visibility, air temperature and pressure near land surface, the solar azimuth and zenith could all be further retrieved. Readme file was attached for detail.
LIANG Ji, WANG Xufeng
This data is a simulated output data set of 5km monthly hydrological data obtained by establishing the WEB-DHM distributed hydrological model of the source regions of Yangtze River and Yellow River, using temperature, precipitation and pressure as input data, and GAME-TIBET data as verification data. The dataset includes grid runoff and evaporation (if the evaporation is less than 0, it means deposition; if the runoff is less than 0, it means that the precipitation in the month is less than evaporation). This data is a model based on the WEB-DHM distributed hydrological model, and established by using temperature, and precipitation (from itp-forcing and CMA) as input data, GLASS, MODIA, AVHRR as vegetation data, and SOILGRID and FAO as soil parameters. And by the calibration and verification of runoff，soil temperature and soil humidity, the 5 km monthly grid runoff and evaporation in the source regions of Yangtze River and Yellow River from 1998 to 2017 was obtained. If asc can't open normally in arcmap, please delete the blacks space of the top 5 lines of the asc file.
WANG Lei
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
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
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