Observational datasets of Pan-Third Pole

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: 75

  • Yulong snow mountain glacier No.1, 4800 m altitude the daily average meteorological observation dataset (2014-2018)

    Yulong snow mountain glacier No.1, 4800 m altitude the daily average meteorological observation dataset (2014-2018)

    1.The data content: air temperature, relative humidity, precipitation, air pressure, wind speed, the average daily data of total radiation, the total net radiation 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;Net radiation instrument: CNR four radiometer component;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 set in upper glaciers, meteorological data provide data support for snow - runoff model simulation, and provides data for the glacier dynamics model and simulation.

    2019-09-13 2198 20

  • Observation dataset of forest ecosystems on the eastern margin of the Tibet Plateau (2005-2008)

    Observation dataset of forest ecosystems on the eastern margin of the Tibet Plateau (2005-2008)

    These are the meteorological, soil, vegetation and other data observed by the Gongga Mountain Forest Ecosystem Test Station on the eastern margin of the Tibetan plateau, primarily from 2005 to 2008. Meteorological data: temperature, air pressure, relative humidity, dew point temperature, water pressure, ground temperature, soil temperature (5 cm, 10 cm, 20 cm, and 40 cm), 10-minute average wind, 10-minute maximum wind speed, precipitation, total radiation, net radiation. Tree layer biological observation data: diameter at breast height, tree height, life form Shrub layer biological observation data: tree number, height, coverage, life form, aboveground biomass, underground biomass Herb layer biological observation data: tree (strain) number, average height, coverage, life type, aboveground biomass, underground biomass Leaf area index: tree layer leaf area index, shrub layer leaf area index, grass layer leaf area index Soil organic matter and nutrients: soil organic matter, total nitrogen, total phosphorus, total potassium, nitrate nitrogen, ammonium nitrogen, available nitrogen (alkali-hydrolysable nitrogen), available phosphorus, available potassium, slowly available potassium, PH value in aqueous solution Soil water content: depth, water content

    2019-09-13 3745 267

  • Meteorological observation data from the integrated observation and research station of multiple spheres in Namco (2005-2016)

    Meteorological observation data from the integrated observation and research station of multiple spheres in Namco (2005-2016)

    This data set contains the daily values of temperature, air pressure, relative humidity, wind speed, precipitation, and total radiation observed at the Namco station from 1 October 2005 to 31 December 2016. The data set was processed as a continuous time series after the original data were quality controlled. After the systematic error caused by missing data points and sensor failure was eliminated, the data set reaches the accuracy of raw meteorological observation data required by the National Weather Service and the World Meteorological Organization (WMO). The data can provide information for professionals engaged in scientific research and training related to atmospheric physics, atmospheric environment, climate, glaciers, frozen soils and other disciplines. This data set has mainly been applied in the fields of glaciology, climatology, environmental change, cold zone hydrological processes, frozen soil science, etc. The measured parameters had the following units and accuracies: Air temperature, unit: °C, accuracy: 0.1 °C; air relative humidity, unit: %, accuracy: 0.1%; wind speed, unit: m/s, accuracy: 0.1 m/s; wind direction, unit: °, accuracy: 0.1 °; air pressure, unit: hPa, accuracy: 0.1 hPa; precipitation, unit: mm, accuracy: 0.1 mm; total radiation, unit: W/m2, accuracy: 0.1 W/m2.

    2019-09-12 4185 820

  • The meteorological observation data of the Xiying River on the east section of the Qilian Mountains (2006-2010)

    The meteorological observation data of the Xiying River on the east section of the Qilian Mountains (2006-2010)

    This data set contains meteorological observation data from three meteorological stations in the Shandong section of the Qilian Mountains (Xiying Reservoir [XYSCZ], Forest Protection Station [XYHLZ] and Shangchigou [XYSCG]), including temperature, precipitation, relative humidity, wind speed, main wind direction, total radiation and air pressure, and the temporal resolution is one day. The raw data were observed and collected in strict accordance with the instrument operating specifications. The accuracy of the data meets the requirements of the National Meteorological Administration and the World Meteorological Organization (WMO) for meteorological observation data. The observation system is maintained by professionals 2-3 times a year, during which the sensor is calibrated or replaced and the collected data are downloaded and reorganized. The data are the continuous sequence generated by quality controlling the raw data, and some obvious systematic error data caused by missing points and sensor failure are eliminated.

    2019-09-12 2575 212

  • Qilian Mountains integrated observatory network: Cold and Arid Research Network of Lanzhou university (an observation system of Meteorological elements gradient of Guazhou Station, 2018)

    Qilian Mountains integrated observatory network: Cold and Arid Research Network of Lanzhou university (an observation system of Meteorological elements gradient of Guazhou Station, 2018)

    This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Guazhou Station from September 23 to December 31, 2018. The site (95.673E, 41.405N) was located on a desert in the Liuyuan Guazhou, which is near Jiuquan city, Gansu Province. The elevation is 2016 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (2, 4, 8, 16, 32, and 48 m, towards north), wind speed and direction profile (windsonic; 2, 4, 8, 16, 32, and 48 m, towards north), air pressure (1.5 m), rain gauge (4 m), infrared temperature sensors (4 m, towards south, vertically downward), photosynthetically active radiation (4 m, towards south), soil heat flux (-0.05 m and -0.1m in south of tower), soil soil temperature/ moisture/ electrical conductivity profile -0.05, -0.1m, -0.2m, -0.4m, -0.6m and -0.8m in south of tower), four-component radiometer (4 m, towards south), sunshine duration sensor(4 m, towards south). The observations included the following: air temperature and humidity (Ta_2 m, Ta_4 m, Ta_8 m, Ta_16 m, Ta_32 m, and Ta_48 m; RH_2 m, RH_4 m, RH_8 m, RH_16 m, RH_32 m, and RH_48 m) (℃ and %, respectively), wind speed (Ws_2 m, Ws_4 m, Ws_8 m, Ws_16 m, Ws_32 m, and Ws_48 m) (m/s), wind direction (WD_2 m, WD_4 m, WD_8 m, WD_16 m, WD_32 m, and WD_48 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), infrared temperature (IRT) (℃), photosynthetically active radiation (PAR) (μmol/ (s m^2)), soil heat flux (Gs_0.05m, Gs_0.1m) (W/m^2), soil temperature (Ts_5 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm, and Ts_80 cm) (℃), soil moisture (Ms_5 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm, and Ms_80 cm) (%, volumetric water content),soil water potential (SWP_5cm, SWP_10cm, SWP_20cm, SWP_40cm, SWP_60cm, and SWP_80cm)(kpa), soil conductivity (Ec_5cm, Ec_10cm, Ec_20cm, Ec_40cm, Ec_60cm, and Ec_80cm)(μs/cm), sun time (h). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The soil water potential in the area is so low that it has exceeded the sensor measurements. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2018-6-10 10:30.

    2019-09-12 4514 367

  • Dataset of cloud observations in Arctic Alaska (1999-2009)

    Dataset of cloud observations in Arctic Alaska (1999-2009)

    This data set of cloud observations at a site in Arctic Alaska is based on the fusion of five cloud inversion products that are well known worldwide. The temporal coverage of the data is from 1999 to 2009, the temporal resolution is one hour, and there are 512 layers vertically with a vertical resolution of 45 m. The spatial coverage is one site in Arctic Alaska, with latitude and longitude coordinates of 71°19′22.8′′N, 156°36′32.4′′ W. The remote sensing cloud inversion data products include the following official products: the all-phase cloud characteristic products produced by the Atmospheric Radiation Measurement Program of the US Department of Energy adopting a parametric method for remote sensing inversion, the ice cloud and hybrid cloud feature products obtained from the US NOAA researchers Matt Shupe and Dave Turner based on cooperative remote sensing inversion (optimization method + parametric method), the hybrid cloud feature (optimization method) products produced by Zhien Wang of the University of Wyoming, USA, the ice cloud feature (parametric method) products produced by Min Deng of the University of Wyoming, USA, and the cloud optical thickness products produced by Qilong Min of the State University of New York at Albany adopting remote sensing inversion (optimization method). The variables of the remote sensing products include cloud water effective radius, cloud water content, cloud ice effective radius, cloud ice content, cloud optical thickness, and cloud water column content; the corresponding observed inversion error ranges are approximately 10-30%, 30-60%, 10-30%, 30-60%, 10-30% and 10-20%. The data files are in the NC format, and an NC file is stored every month.

    2019-09-12 4921 247

  • Asian monsoon experiment on the Tibetan Plateau (GAME/Tibet) dataset for global energy water cycle (1997-1998)

    Asian monsoon experiment on the Tibetan Plateau (GAME/Tibet) dataset for global energy water cycle (1997-1998)

    The GAME/Tibet project conducted a short-term pre-intensive observing period (PIOP) at the Amdo station in the summer of 1997. From May to September 1998, five consecutive IOPs were scheduled, with approximately one month per IOP. More than 80 scientific workers from China, Japan and South Korea went to the Tibetan Plateau in batches and carried out arduous and fruitful work. The observation tests and plans were successfully completed. After the completion of the IOP in September, 1998, five automatic weather stations (AWS), one Portable Atmospheric Mosonet (PAM), one boundary layer tower and integrated radiation observatory (Amdo) and nine soil temperature and moisture observation stations have been continuously observed to date and have obtained extremely valuable information for 8 years and 6 months consecutively (starting from June 1997). The experimental area is located in Nagqu, in northern Tibet, and has an area of 150 km × 200 km (Fig. 1), and observation points are also established in D66, Tuotuohe and the Tanggula Mountain Pass (D105) along the Qinghai-Tibet Highway. The following observation stations (sites) are set up on different underlying surfaces including plateau meadows, plateau lakes, and desert steppe. (1) Two multidisciplinary (atmosphere and soil) observation stations, Amdo and NaquFx, have multicomponent radiation observation systems, gradient observation towers, turbulent flux direct measurement systems, soil temperature and moisture gradient observations, radiosonde, ground soil moisture observation networks and multiangle spectrometer observations used as ground truth values for satellite data, etc. (2) There are six automatic weather stations (D66, Tuotuohe, D105, D110, Nagqu and MS3608), each of which has observations of wind, temperature, humidity, pressure, radiation, surface temperature, soil temperature and moisture, precipitation, etc. (3) PAM stations (Portable Automated Meso - net) located approximately 80 km north and south of Nagqu (MS3478 and MS3637) have major projects similar to the two integrated observation stations (Amdo and NaquFx) above and to the wind, temperature and humidity turbulence observations. (4) There are nine soil temperature and moisture observation sites (D66, Tuotuohe, D110, WADD, NODA, Amdo, MS3478, MS3478 and MS3637), each of which has soil temperature measurements of 6 layers and soil moisture measurement of 9 layers. (5) A 3D Doppler Radar Station is located in the south of Nagqu, and there are seven encrypted precipitation gauges in the adjacent (within approximately 100 km) area. The radiation observation system mainly studies the plateau cloud and precipitation system and serves as a ground true value station for the TRMM satellite. The GAME-Tibet project seeks to gain insight into the land-atmosphere interaction on the Tibetan Plateau and its impact on the Asian monsoon system through enhanced observational experiments and long-term monitoring at different spatial scales. After the end of 2000, the GAME/Tibet project joined the “Coordinated Enhanced Observing Period (CEOP)” jointly organized by two international plans, GEWEX (Global Energy and Water Cycle Experiment) and CL IVAR (Climate Change and Forecast). The Asia-Australia Monsoon Project (CAMP) on the Tibetan Plateau of the Global Coordinated Enhanced Observation Program (CEOP) has been started. The data set contains POP data for 1997 and IOP data for 1998. Ⅰ. The POP data of 1997 contain the following. 1. Precipitation Gauge Network (PGN) 2. Radiosonde Observation at Naqu 3. Analysis of Stable Isotope for Water Cycle Studies 4. Doppler radar observation 5. Large-Scale Hydrological Cycle in Tibet (Link to Numaguchi's home page) 6. Portable Automated Mesonet (PAM) [Japanese] 7. Ground Truth Data Collection (GTDC) for Satellite Remote Sensing 8. Tanggula AWS (D105 station in Tibet) 9. Syamboche AWS (GEN/GAME AWS in Nepal) Ⅱ. The IOP data of 1998 contain the following. 1. Anduo (1) PBL Tower, 2) Radiation, 3) Turbulence SMTMS 2. D66 (1) AWS (2) SMTMS (3) GTDC (4) Precipitation 3. Toutouhe (1) AWS (2) SMTMS (3 )GTDC 4. D110 (1) AWS (2) SMTMS (3) GTDC (4) SMTMS 5. MS3608 (1) AWS (2) SMTMS (3) Precipitation 6. D105 (1) Precipitation (2) GTDC 7. MS3478(NPAM) (1) PAM (2) Precipitation 8. MS3637 (1) PAM (2) SMTMS (3) Precipitation 9. NODAA (1) SMTMS (2) Precipitation 10. WADD (1) SMTMS (2) Precipitation (3) Barometricmd 11. AQB (1) Precipitation 12. Dienpa (RS2) (1) Precipitation 13. Zuri (1) Precipitation (2) Barometricmd 14. Juze (1) Precipitation 15. Naqu hydrological station (1) Precipitation 16. MSofNaqu (1) Barometricmd 16. Naquradarsite (1)Radar system (2) Precipitation 17. Syangboche [Nepal] (1) AWS 18. Shiqu-anhe (1) AWS (2) GTDC 19. Seqin-Xiang (1) Barometricmd 20. NODA (1)Barometricmd (2) Precipitation (3) SMTMS 21. NaquHY (1) Barometricmd (2) Precipitation 22. NaquFx(BJ) (1) GTDC(2) PBLmd (3) Precipitation 23. MS3543 (1) Precipitation 24. MNofAmdo (1) Barometricmd 25. Mardi (1) Runoff 26. Gaize (1) AWS (2) GTDC (3) Sonde A CD of the data GAME-Tibet POP/IOP dataset cd (vol. 1) GAME-Tibet POP/IOP dataset cd (vol. 2)

    2019-09-12 19476 134

  • The dataset of atmospheric chemical composition in Namcu and Muztagh Ata (2005-2009)

    The dataset of atmospheric chemical composition in Namcu and Muztagh Ata (2005-2009)

    The data include three data sets of Namcu and Muztagh Ata: an atmospheric aerosol data set of monthly average values of TSP, lithium, sodium and other elements; an atmospheric precipitation chemical data set of monthly average values of soluble sodium ions, potassium ions, magnesium ions, calcium ions and other ions; and a data set of chemical compositions of snow ice in the Zhadang Glacier of Namcu Basin of the concentrations of soluble sodium ions, potassium ions, magnesium ions, calcium ions and other ions in snow pits collected in different months. The data can be used in conducting located observations of atmospheric aerosol element content, precipitation chemistry, and glacier snow ice chemical records in the Namco and Muztagh Ata areas. The samples were processed at the Key Laboratory of Tibetan Environment Changes and Land Surface Processes of CAS using ICS2500 and ICS2000 ion-chromatographic analyzers to determine the concentration of soluble anions and cations in the samples. Data collection and processing: 1. The automatic rain gauges were erected in the typical regions of the Tibetan Plateau (the Namco Basin and the Muztagh Ata Peak area) to collect precipitation samples. The precipitation samples were collected using a SYC-2 type rainfall sampler that comprised a collector, rain sensor and gland drive. The sample collector was provided with a rain collection bucket and a dust collection bucket, and the weather condition was sensed by the rain sensor. The rain collection bucket would be opened when it started to rain, and the gland would be pressed onto the dust collection bucket. Meanwhile, the date and the rain start and end times were automatically recorded. When the rain stopped, the gland automatically flipped to the rain collection bucket to complete a rainfall record. The collected samples were placed in 20 mL clean high-density polyethylene plastic bottles and refrigerated in a -20 °C refrigerator. They were frozen during transportation and storage until right before being analyzed, when they would be taken from the refrigerator and thawed at room temperature (20 °C). They were then processed at the Key Laboratory of Tibetan Environment Changes and Land Surface Processes CAS using ICS2500 and ICS2000 ion-chromatographic analyzers to determine the concentration of soluble anions and cations in the precipitation. 2. The atmospheric aerosol sampler installed at Namco Station was 4 m above the ground and included a vacuum pump, which was powered by solar panels and batteries. The air flux was recorded by an automatic flow meter, and the instantaneous flow rate was approximately 16.7 L/min. The air flux took the meteorological parameter conversion of the Namco area as the standard volume. A Teflon filter with a diameter of 47 mm and a pore size of 0.4 & mu; m was used. The sample interval was 7 days, and the total sample flow rate of each sample was approximately 120-150 m³. Each sample was individually placed in a disposable filter cartridge and stored at low temperature in a refrigerator. Before and after sampling, the filter was placed in a constant temperature (20 ± 5 °C) and constant humidity (40 & plusmn; 2%) environment for 48 hours and weighed with a 1/10000 electronic balance (AUW220D, Shimadu); the difference between the weights before and after was the weight of the aerosol sample on the filter. The collected samples were processed at the Key Laboratory of Tibetan Environment Changes and Land Surface Processes CAS by ICP-MS to determine the concentrations of 18 elements. Strict measures were taken during indoor and outdoor operations to prevent possible contamination. 3. A precleaned plastic shovel was used to collect a sample every 5 cm from the lower part of the snow pit (samples were collected every 10 cm in some snow pits). The samples were dissolved at room temperature, placed in 20 mL clean high-density polyethylene plastic bottles and stored in a refrigerator at -20 °C. The samples were frozen during transportation and storage until they were taken out of the refrigerator before the analysis and melted at room temperature. The samples were processed at the Key Laboratory of Tibetan Environment Changes and Land Surface Processes CAS using ICS2500 and ICS2000 ion-chromatographic analyzers to determine the concentrations of soluble anions and cations in the samples. Clean clothing, disposable masks and plastic gloves should be worn during the manual collection of glacier snow ice chemical samples to prevent contamination. The data set was processed by forming a continuous sequence of monthly mean values after the raw data were quality controlled. It meets the accuracy of routine monitoring research on precipitation, aerosol, snow and ice records in China and the world and is satisfactory for comparative study with relevant climate change records.

    2019-09-12 2801 386

  • The soil temperature and moisture dataset of the Muztagh Ata station (2013-2016)

    The soil temperature and moisture dataset of the Muztagh Ata station (2013-2016)

    This data set contains the daily values of soil temperature and moisture at different depths observed from the Integrated Observation and Research Station of the Westerly Environment in Muztagh Ata from January 1, 2013, to December 31, 2015. The data were collected digitally and automatically by observation instruments. The data set was processed by forming a continuous time sequence after the raw data were quality controlled. Observation and collection of the data were performed in strict accordance with the instrument operating specifications, and the systematic error caused by the missing point data and the sensor failure were eliminated. This table contains 12 fields. Field 1: Station Number Data type: Character (50) Field 2: Time Data type: date type Fields 3 to 7: Soil temperature (different depths) Data type: double precision floating point Unit: °C Fields 8 to 12: Soil moisture (different depths) Data type: double precision floating point Unit: %

    2019-09-12 3055 202

  • Dataset of alpine timberlines in Southern Tibet (2005-2008)

    Dataset of alpine timberlines in Southern Tibet (2005-2008)

    This data set mainly includes meteorological data and soil moisture data collected from 2005 to 2008 at the Sherjila Mountain Alpine Timberline Observation Site of the Integrated Observation and Research Station of the Alpine Environment in Southeast Tibet. The data set of alpine timberline observations in southeast Tibet includes 1) the meteorological data set and 2) the soil moisture data set. The meteorological data set includes wind speed, temperature (1, 3 m), relative humidity (1, 3 m), soil heat flux (-5, -20, -60 cm), soil temperature (-5, -20, -60 cm), air pressure, total radiation, net radiation, photosynthetically active radiation, infrared radiation (660, 730 nm), atmospheric longwave radiation, ground longwave radiation, surface temperature, precipitation, and snow thickness. The soil moisture data set includes vegetation type and soil water content (-5, -20, -60 cm). Instruments used for each variable: Temperature: Air temperature probe, produced in Taiwan, model TRH-S. Relative humidity: Model TRH-S, produced in Taiwan. Wind speed: Anemoscope, produced in Taiwan, model 03102. Barometric Pressure: Barometric pressure sensor, produced in Taiwan, model BP0611A. Atmospheric longwave radiation: Pyrgeometer, produced by the Kipp & Zonen Company of the Netherlands, model CG3. Ground longwave radiation: Pyrgeometer, produced by the Kipp & Zonen Company of the Netherlands, model CG3. Total radiation: Pyranometer, produced by the Kipp & Zonen Company of the Netherlands, model CM3. Net radiation: Net radiometer, produced by the Kipp & Zonen Company of the Netherlands, model NR-Lite. Photosynthetically active radiation: PAR-Sensor, produced by the Kipp & Zonen Company of the Netherlands, model MS-PAR. Infrared radiation: Infrared radiation sensor, produced by the Skye Company of the UK, model SKY110. Rainfall: Rain gauge, produced in Taiwan, model 7852 M. Snow thickness: Ultrasonic snow depth sensor, produced in the United States, model 260-700. Soil temperature: Soil temperature probe, produced by the Onset Company of the United States, model 12-Bit. Soil heat flux: Soil heat flux plate, produced by the Hukseflux Company of the Netherlands, model HFP01. Soil moisture content: Soil moisture sensor, produced by the Onset Company of the United States, model S-SMA-M003. The observations and data acquisition were carried out in strict accordance with the instrument operating specifications. Each instrument was rigorously validated and calibrated by the supplier before installation to ensure the accuracy of the observation data. Data with significant errors were removed when processing the data table.

    2019-09-12 2761 266

  • Observation data of temperature and rainfall in permafrost regions of Qinghai-Tibet Engineering Corridor (1956-2012)

    Observation data of temperature and rainfall in permafrost regions of Qinghai-Tibet Engineering Corridor (1956-2012)

    The data set includes the trends of annual average temperature and rainfall changes at the three meteorological stations in the permafrost section of the Qinghai-Tibet Engineering Corridor over the past 50 years. According to the recorded data, the annual average temperature is experiencing a gradually rising process. The annual average temperature change over the past 56 years in Wudaoliang and Tuotuohe has a good correlation (r2=0.83). In 1957, the average annual temperatures of Wudaoliang and Tuotuohe were -6.6 °C and -5.1 °C, respectively. By 2012, the temperatures of the two stations were -4.6 and -3.1 °C, and the total temperature has risen by approximately 2 °C. The annual average temperature rises by 0.03-0.04 °C. The annual average temperature changes over the past 47 years in Wudaoliang and Anduo also have a good correlation (r2=0.84). In 1966, the average annual temperature in Anduo was -3.0 °C. By 2012, the temperature has risen to -1.8 °C, corresponding to a total temperature rise of approximately 1.2 °C and an annual average temperature rise of 0.02-0.03 °C. The annual average temperature in Wudaoliang and Tuotuohe rose slightly faster than that in Anduo. However, the change in rainfall was more volatile than that of temperature. The correlation between the rainfall change in Wudaoliang and Tuotuohe over the past 56 years is relatively poor (r2=0.60). In 1957, the annual rainfall amounts in Wudaoliang and Tuotuohe were 302 and 309 mm, respectively. By 2012, the annual rainfall amounts at the two stations were 426 and 332 mm. Thus, the rainfall in Wudaoliang had increased by 124 mm, with an annual rainfall increase of approximately 2 mm. In contrast, the annual rainfall in Tuotuohe only increased by 0.4 mm. The correlation between the rainfall change in Wudaoliang and Anduo over the past 47 years is also poor (r2=0.35). In 1966, and 2012, the annual average rainfall amounts in Anduo were 354 and 404 mm. The total increase was approximately 50 mm, and the annual average increase was 1 mm. The annual rainfall in Wudaoliang increased the fastest. The observation data from the three meteorological stations reveal climate changes in the permafrost sections of the Qinghai-Tibet Engineering Corridor. Judging from the overall trend of temperature and rainfall changes, the temperature in the northern and central parts of the corridor has increased rapidly over the past 50 years, exceeding the global average of 0.02 °C/a (IPCC). The rainfall increase in the northern part of the corridor is also obvious, especially the rate of rainfall increase at the Wudaoliang meteorological station. Increases in both temperature and rainfall have a great impact on accelerating the spatial variation in permafrost, and they are the leading cause of permafrost degradation on the Tibetan Plateau.

    2019-09-12 3973 260

  • The stable oxygen isotope data of daily precipitation in Lulang, Nuxia, and Guangzhou (2007-2014)

    The stable oxygen isotope data of daily precipitation in Lulang, Nuxia, and Guangzhou (2007-2014)

    This data set contains stable oxygen isotope data of daily precipitation in Lulang, Nuxia, and Guangzhou from 2007 to 2014. The precipitation data of the Lulang station are obtained via automatic weather station (AWS) rain gauges, and the precipitation data for Guangzhou and Nuxia are the manual records of meteorological or hydrological stations. Project source of the data: the general project of the National Natural Science Foundation of China “Exploring the impact of ENSO on the source of water vapor in the north and south of the ‘third pole' through stable isotope of precipitation and ice core” (41571074). Data processing related information can be found in the following reference: Yang, X, Mary E. Davis, Sunil Acharya, Tandong Yao. Asian Monsoon variations revealed from stable isotopes in precipitation. Climate Dynamics, 2017, doi:10.1007/s00382-017-4011 -4. Data collection sites: Lulang Station of Southeast Tibet, Chinese Academy of Sciences, Longitude: 94.73°E; Latitude: 29.77°N; Altitude: 3330 m. Guangzhou weather station, longitude: 113.32 °E; latitude: 23.13 ° N; altitude: 7 meters. Nuxia hydrological station, longitude: 94.65 °E; latitude: 29.47 ° N; elevation: 2920 m.

    2019-09-11 2580 234

  • The receiver function data of the Southern Station of the ANTILOPE-1 Array (2006-2007)

    The receiver function data of the Southern Station of the ANTILOPE-1 Array (2006-2007)

    The data set mainly includes P-wave and S-wave receiver functions calculated from the waveform data collected at the southern station of the ANTILOPE-1 array, which is located in the western part of the Tibetan Plateau. This array was established by the Antelope Project of the International Lithosphere Exploration Research Program in the Tibetan Plateau. The pulse deconvolution method was applied to the time domain to calculate the receiver function. All of the receiver function data were visually inspected to remove low-quality records that were significantly different from the majority of the receiver functions. The data set was compressed into a zip format file containing two folders: ANTILOPE-1-PRF and ANTILOPE-1-SRF, where PRF and SRF represent the P-wave receiver function and the S-wave receiver function, respectively. All P-wave and S-wave receiver function data were placed in the corresponding folders. The data are mainly used to investigate the lithospheric structure and reveal the deep dynamics of plateau uplift.

    2019-09-11 2021 180

  • The observation dataset of the Muztagh Ata hydrological station (2013-2017)

    The observation dataset of the Muztagh Ata hydrological station (2013-2017)

    The observation data set of the Muztagh Ata hydrological station recorded the water level data of Lake Karakuri and Qiaodumake in the Muztag Ata area, and the ice condition and water quality data of Lake Karakuri (e.g., water temperature, pH, dissolved oxygen, redox potential, and conductivity). The ice condition data were manually measured, including observational data from November 30,2013, to March 26, 2016, which recorded the observational data for each week during December to the next March from 2013 to 2015 (the data collection period sometimes would change due to weather and other reasons); water quality parameter was measured using Hydrolab DS5, including measured data on 2013-07-20, 2014-07-15, 2014-08-28, 2014-09-14, 2015-07-11, and 2015-09-18; water level data were automatically measured by HOBO water level collector, and they included daily measurement records of Lake Karakuri from July 1, 2013, to October 13, 2015, and Qiaodumake from June 3,2013, to September 2, 2015. The data were collected digitally and automatically, and the data set was processed by forming a continuous time sequence after quality controlling the raw data. Observation and collection of the data were performed in strict accordance with the instrument operating specifications. Some obvious error data were removed, and missing data were represented by spaces. Qiaodumake water level collection location: E 75°00.149′, N 38°17.375′, 4130 m Lake Karakuri measuring point location: E 75°02.286′, N 38°26.209′, 3650 m Water level data: Time, Water level, unit: cm Ice condition data: Time, Ice thickness, unit: cm Water quality data: Time, Depth, unit: m Temperature, unit: °C PH, unit: pH Redox potential, unit: mV Photon flux density, unit: μmol/(m2 s) Dissolved oxygen, unit: mg/l

    2019-09-11 2976 220

  • Observation Data from Glacier and Hydrological Stations in the Parlung Zangbo River Basin in Southeastern Tibet (2007-2008)

    Observation Data from Glacier and Hydrological Stations in the Parlung Zangbo River Basin in Southeastern Tibet (2007-2008)

    This data set contains observation data from glacier and hydrological stations in the Parlung Zangbo River Basin in southeastern Tibet. The data include measurements of the runoff from Parlung Glacier No. 4 and 24K Glacier. These monthly mean data therefore represent two different types of glaciers (debris-free and debris-covered glaciers). Observation instruments: Propeller Flow Velocity Meter (LS1206B), HOBO water level data logger. Parlung Glacier No. 4: Longitude: 96°55.19′; Latitude: 29°13.57′; Elevation: 4650 m. 24K Glacier: Longitude: 95°43.81′; Latitude: 29°45.41′; Elevation: 3800 m. The data contains two fields: Field 1: Date Field 2: Runoff, m³/s

    2019-04-18 2897 278