Brief Introduction: The high-cold regions in China include the Qinghai Tibetan Plateau, and the alpine regions of Gansu, Inner Mongolia and Xinjiang, with a total area of about 2.9 million square kilometers. Due to the complexity of topography and geomorphology, the worldwide researches more and more focus on the surface processes of the Qinghai Tibetan Plateau and its adjacent areas. The High-cold Region Observation and Research Network for Land Surface Processes & Environment of China (HORN) has gradually formed. It integrates 17 stations of Chinese Academy of Sciences, for long term observations and researches of land surface processes, including glaciers, permafrost, lades, alpine ecosystem in the high-cold regions of China. It provides a platform support for integrated researches of earth system, through condensation of scientific problems, integration of monitoring resources, improvement of observation capability and level, long-term continuous monitoring of surface processes and environmental changes in cold regions. It also provides data support for revealing the law of climate change and water resources formation and transformation in the headwaters of big rivers, exploring the changes of ecosystem structure and service function, grasping the mechanism of natural disasters such as ice and snow freezing and thawing, and promoting the sustainable development of regional economy and society, etc. A network integrated center is set up to organize research and carry out the specific implementation of network construction. It consists of an office, an observation technology service group and a data integration management group. The participating units of HORN should sign construction/research contracts in order to implement contract-based management, perform all tasks in the contracts and accept the examination and acceptance of the network organization. The network construction should give priority to scientific research, coordinated development, relatively balanced allocation of infrastructure and observation instruments, and free sharing of data within the network. For the principle of sharing and opening, the observatories of the network are open to the whole country. The network cooperates with relevant units through consultation, agreement or contract according to specific tasks and costs; the original observation data are gradually shared based on the principle of first the network, then the department and then the society. The network carries out planned and coordinated cooperation with foreign scientific research institutions and universities, which can improve the level of network observation and expand the content of observation through the cooperation. The HORN is managed by the Chinese Academy of Sciences in the allocation of funds and resources.
Number of Datasets: 74
1. Data content: air temperature, relative humidity, precipitation, air pressure, wind speed, average total radiation, total net radiation value and daily average water vapor pressure data. 2. Data source and processing method: Observed by American campel high-altitude automatic weather station, air temperature and humidity sensor model HMP155A; wind speed and wind direction model: 05103-45; net radiometer: CNR 4 Net Radiometer four component; atmospheric pressure sensor: CS106; Rain gauge: TE525MM. The automatic weather station automatically collects data every 10 minutes, and collects daily statistical data to obtain daily average weather data. 3. Data quality description: Data is automatically acquired continuously. 4. Data application results and prospects: The weather station is located in the middle of the glacier, and the meteorological data can provide data guarantee for simulating the response of oceanic glacier changes to global climate change in the context of future climate change.
2020-06-01 999 10 View Details
The data set covers 599 meteorological stations in five Central Asian countries, including the following elements: * daily maximum temperature, * daily minimum temperature, * observed temperature, * Precipitation (i.e. rain, melting snow), covering the following dates: 1980-1986; 1996-2005; 2010; 2014; 2015 The data comes from ghcn-d, a data set containing global land area daily observation data, which integrates climate records. The data is a direct measurement of surface temperature, without interpolation or model assumptions, and contains many long-term site records. The disadvantage is uneven space coverage. Due to changes in observation time, site location, and the type of thermometer used, the records contain many heterogeneity. For more information about this dataset, see https://www.ncdc.noaa.gov/ghcnd-data-access
2020-05-30 2128 95 View Details
High-frequency continuous GPS observation can effectively monitor the kinematics of crustal deformation. The Qilian Mountains region is an important constraint boundary of the northeastern margin of the Qinghai-Tibet Plateau. The study of this region can provide important implications for the dynamic process of the growth and uplift of the Tibetan Plateau and the internal deformation of the Tibetan Plateau. At the local level, it can be discussed whether there is creepage in the Haiyuan fault and the movement mode of the northeastern margin of the Qinghai-Tibet Plateau. The data comes from 26 fixed stations set up by the research group in the Qilian Mountain area. The site selection requirements are strict, and the high-frequency continuous GPS receiver is Provided by trimble, the data quality is good, the data can be applied not only to geodynamic research, but also to related earth science research such as meteorological precipitation.
2020-05-30 1429 0 View Details
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
2020-05-14 1193 19 View Details
Based on the long-term observation data of each field station in the alpine network and overseas stations in the pan third polar region, a series of data sets of meteorological, hydrological and ecological elements in the pan third polar region are established; the inversion of data products such as meteorological elements, lake water quantity and quality, aboveground vegetation biomass, glacial and frozen soil changes are completed through enhanced observation and sample site verification in key regions; based on the IOT Network technology, the development and establishment of multi station network meteorological, hydrological, ecological data management platform, to achieve real-time access to network data and remote control and sharing. In 2018, the hydrological data set of surface process and environmental observation network in China's alpine region mainly collects the daily measured hydrological (runoff, water level, water temperature, etc.) data of Qilianshan station, Southeast Tibet station, Zhufeng station, Yulong Xueshan station, Namucuo station, Ali station, mostag and other seven stations.
2020-05-14 3421 33 View Details
1)Data content (including elements and meanings): surface meteorological observation data product of TP in 1979-2016 2)Data source and processing method: In .tif format, can be opened and analysed in arcgis. 3)Data quality description: daily resolution 4)Data application results and prospects: Based on the long-term observation data of the 17 stations of HORN, establish a series of data series of meteorological, hydrological and ecological elements in the Pan-Earth region; Strengthen observation and sample and sample verification, and complete the inversion of meteorological elements, lake water quantity and water quality, aboveground vegetation biomass, glacier and frozen soil changes; based on Internet of Things technology, develop multi-station networked meteorological, hydrological, The ecological data management platform realizes real-time acquisition and remote control and sharing of networked data.
2020-05-14 3594 301 View Details
The active layer is one of the main characteristics of permafrost. It melts in warm season and freezes in cold season, showing seasonal changes. The amount of water content in the active layer has certain influence on the temperature of the permafrost, thus affecting the stability of the permafrost.The data set is mainly composed of active layer moisture data. The monitoring station is located at 92°E, 34°N, with an elevation of 4600m. The monitoring site is flat, the vegetation type is alpine meadow, and the water probe used by Beilouhe Meteorological Station is CS615. The data set is used to monitor water at 5 depths below the surface, 10 cm, 20 cm, 40 cm, 80 cm and 160cm. The time interval of the data set is 1 day and is 30 minutes.Mean value of data once, data is stable and continuous during monitoring.By combining the data of soil heat flux and frozen soil temperature, the thermal change process and mechanism of active layer can be carried out.
2020-04-23 525 16 View Details
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.
2020-04-23 1037 28 View Details
The active layer is one of the main characteristics of permafrost. It melts in warm season and freezes in cold season, showing seasonal changes. The change of ground temperature of active layer will directly affect the change of temperature of permafrost, thus affecting the stability of permafrost.The monitoring station of this data set is located at 92 °E, 35 ° N, with an elevation of 4,600 M. The monitoring site is flat, the vegetation type is alpine meadow, and the monitoring instrument is DT500 series data acquisition instrument. The monitoring of ground temperature is carried out at 5 depths below the surface, 10 cm, 20 cm, 40 cm, 80 cm and 160cm respectively. The time interval of this data set is 1 day, which is the average value of data once every 30 minutes.Data are stable and continuous during the period.Scientific subjects such as thermal change process and change mechanism of active layer are carried out by combining data of soil heat flux and soil moisture.
2020-04-23 705 19 View Details
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.
2020-03-07 7427 5 View Details
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.
2020-01-10 1945 77 View Details
This data set contains the daily values of water temperature and water level change in Ranwu Lake in Tibet from May 15, 2009, to December 31, 2016. Observation instrument model: an automatic HOBO water level and temperature logger U20-001-01; acquisition time: 30 minutes. The data were collected automatically. The observations and data collection were performed in strict accordance with the instrument operating specifications, and the data have been published in relevant academic journals. Data with obvious errors were removed, and the missing data were replaced by null values. Data collection location: Ranwu Lake, southeast Tibet Middle lake outlet: longitude: 96°46'16"; latitude: 29°29'28"; elevation: 3928 m. Lower Lake outlet: longitude: 96°38'52"; latitude: 29°28'52"; elevation: 3923 m. Laigu upper Lake: longitude: 94°49'49"; latitude: 29°18'07"; elevation: 4025 m. This data contains fileds as follows: Field 1: Site Number Data type: Alphanumeric characters (50) Field 2: Time Data type: Date type Field 3: Water temperature, °C Data type: Double-precision floating-point format Field 4: Relative water level, cm Data type: Double-precision floating-point format
2020-01-10 1425 36 View Details
This is the sounding observation data set measured by the sounding instrument. It is released by Ali Station, Institute of Tibetan Plateau Research, Chinese Academy of Sciences. The observation time is separately at 12:00, 16:00, 20:00 September 2, 2017, at 16:00, 20:00 September 3, 2017, at 8:00, 12:00, 16:00, 20:00, September 4,2017, at 0:00, 4 :00, 8:00, 12:00, 16:00, 20 :00 September 5, 2017, at 0:00, 4 :00, 8:00, September 6,2017. The original data accuracy is as follows. The data accurate to the integer position are logarithmic pressure, relative humidity, altitude, horizontal wind direction, azimuth, and elevation. The data accurate to one decimal place are temperature, air pressure, dew-point temperature, horizontal wind speed, and longitude. And the data accurate to two decimal places are meridional wind velocity, zonal wind velocity, vapor-to-liquid ratio and latitude. Quality control includes eliminating the missing data and the empty data. The data is stored as an excel file.
2019-11-18 1870 13 View Details
This data set includes the temperature, precipitation, relative humidity, wind speed, wind direction and other daily values in the observation point of Kongque River Source. The data is observed from July 2, 2012 to September 15, 2017. 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.
2019-11-18 2437 20 View Details
This data set includes the temperature, relative humidity, and other daily values at the end of the observation point of the terminus of Naimona’nyi Glacier The data is observed from July 3, 2011 to September 15, 2017. It is measured by automatic meteorological station (Onset Company) and a piece of data is recorded every 60minutes. 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.
2019-11-17 1343 16 View Details
As the “water tower of Asia”, Tibetan Plateau (TP) are the resource of major rivers in Asia. Black carbon (BC) aerosol emitted from surrounding regions can be transported to the inner TP by atmospheric circulation and consequently deposited in snow, which can significantly influence precipitation and mass balance of glaciers. Five Aethalometers are used to mornitoring black carbon concentration at 5 stations on the Tibetan Plateau. It can provide basic dataset to study the effects of BC to the environment and climate over the Tibetan Plateau, as well as the pollutants transport.
2019-10-27 1806 19 View Details
This data set includes the biomass and photosynthesis observational data of the highland spring barley experimental plot at the Lhasa Farm Experimental Station and the meteorological data observationally obtained at the Damxung Grass Experimental Station. The time range is 2006-2009. Biomass observation method: The sampling area of each sample is 25 cm*25 cm. Photosynthetic data observation: The instrument is a LiCor-6400. The biomass data are manually entered according to the record book. The photosynthetic data are automatically recorded by the instrument. The average wind speed, prevailing wind direction, temperature, atmospheric pressure and relative humidity in the daily values of meteorological data are averaged over half-hour data. The precipitation and total radiation data are automatically recorded by the observation system. The observation process of biomass data is in strict accordance with the agronomic method, and it can be applied to the estimation of agricultural productivity. In the process of photosynthetic data observation, the operation of the instrument and the selection of the observation object are strictly in accordance with professional requirements and can be used in photosynthetic parameter simulations estimating plant leaf and productivity. The Tibetan Plateau farmland ecosystem observation data includes: 1) aboveground biomass; 2) CO2 response photosynthetic data; 3) light-response photosynthetic data; and 4) daily meteorological data in Damxung Monitoring Point. Data collection locations: Lhasa Agricultural Ecology Experimental Station, Chinese Academy of Sciences, Longitude: 91°20’, Latitude: 29°41’, Altitude: 3688 m and Damxung Alpine Meadow Carbon Flux Observation Station, Longitude: 91°05′, Latitude: 30°25′, Altitude: 4333 m.
2019-09-15 1397 19 View Details
This data set includes carbon flux data and soil moisture data obtained from the Swamp Meadow Carbon Flux Station in Dangxiong. The temporal coverage is from 2009 to 2010. The temporal resolution of carbon flux data is 4 hours, and it records data from 00:00 to 20:00; the temporal resolution of the soil moisture data is 1 day. All data were automatically recorded by the vorticity-related observing instruments and manually checked. The observation and collection of the data were performed in strict accordance with the instrument operating specifications. During the data observation process, the operation of the instrument and the selection of the observation object were strictly in accordance with professional requirements. The data were collected at Dangxiong Wetland Carbon Flux Observatory of Lhasa Agro-ecological Station of Chinese Academy of Sciences, longitude: 91°07’; latitude: 30°50’; and altitude: 4333 m. The data set can be used in simulations of plant leaf photosynthetic parameter and evaluations of productivity to study the water and carbon processes of wetland ecosystems and their responses to climate change.
2019-09-15 1557 30 View Details
This data set includes biomass survey data observed from the carbon flux station in the Guoluo Army Ranch in Qinghai from 2005 to 2009. Carbon flux data observation method: vorticity-related observation instruments were used for automatic recording; biomass observation method: harvest method, weighing in a 60-degree oven for 48 hours. The carbon flux data were automatically recorded by the instruments and manually checked. Observations and data collection were carried out in strict accordance with the instrument operating specifications and were published in relevant academic journals. During the data observation process, the operation of the instrument and the selection of the observational objects were in strict accordance with professional requirements, and the data could be applied to plant leaf photosynthetic parameter simulation and production estimation. 1) Biological observational data of the Guoluo meadow ecosystem: Date, site number, vegetation type, plot number, aboveground biomass (g/m²), underground biomass (g/m²), total biomass (g/m²) 2) Carbon flux observational data of the Guoluo meadow ecosystem: Site number, date, vegetation type, soil type, water vapor flux (w/m²), carbon flux (mg/m²·S) The fixed point observation data are of high precision.
2019-09-15 1626 41 View Details
This data set contains data on the concentrations of persistent organic pollutants (POPs) and total suspended particulate (TSP) in the atmosphere at a station in southeastern Tibet (Lulang). The samples were collected using an atmospheric active sampler equipped with a tandem fibreglass membrane-polyurethane foam sampling head. The gaseous POPs and TSPs were collected. The sampling period for each sample was 2 weeks. The types of observed POPs include organochlorine pesticides (OCPs), polychorinated biphenyls (PCBs), and polycyclic aromatic hydrocarbons (PAHs). Only gaseous concentrations were detected for OCPs and PCBs, while both gaseous concentrations and particulate concentrations were detected for PAHs. All of the data contained in the data set are measurement data. The samples were collected in the field at the Integrated Observation and Research Station of the Alpine Environment in Southeast Tibet. The sampler was an atmospheric flow active sampler equipped with a tandem fibreglass membrane-polyurethane foam sampling head, in which the fibreglass membrane was used to collect TSPs and the polyurethane foam was used to adsorb gaseous pollutants in the atmosphere. During the sampling period, the sampler was run every other day for approximately 24 hours each time, and each sample was collected for 2 weeks. The atmospheric volume collected for each sample was 500-700 cubic metres. Both gaseous and particulate POP samples were prepared and analysed in the Key Laboratory of Tibetan Environment Changes and Land Surface Processes, CAS. The sample preparation steps included Soxhlet extraction, silica-alumina column purification, removal of macromolecular impurities by a GPC column, concentration to a defined volume, etc. The analytical test instrument was a gas chromatography/ion trap mass spectrometer (Finnigan-TRACE GC/PolarisQ) produced by Thermo Fisher Scientific. The column used to separate OCPs and PCBs was a CP-Sil 8CB capillary column (50 m × 0.25 mm × 0.25 μm), and the column used to separate PAHs was a DB-5MS capillary column (60 m x 0.25 mm x 0.25 μm). The total suspended particulate concentration in the atmosphere was determined by the gravimetric method, and the accuracy of the weighing balance was 1/100,000 g. The field samples were subjected to strict quality control with laboratory blanks and field blanks. The detection limit of a given compound was 3 times the standard deviation of the concentration of the corresponding compound in the field blank; if the compound was not detected in the field blank, the detection limit of the method was determined by the lowest concentration of the working curve. For a sample, concentrations above the detection limit of the method are corrected by subtracting the detection limit; concentrations below the detection limit of the method but higher than 1/2 times the detection limit are corrected by subtracting half the method detection limit; and concentrations below 1/2 times the detection limit are considered undetected. The recovery rate of PAH laboratory samples was between 65-120%, and that of OCPs was between 70-130%; the sample concentrations were not corrected by the recovery rate. In the table, undetected data are marked as BDL; data marked in black italics are data corrected by subtracting 1/2 the method detection limit.
2019-09-15 1091 6 View Details