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: 65

  • Observation dataset of the hydrologic station on the Rongbu River glacier of mount everest (2010)

    Observation dataset of the hydrologic station on the Rongbu River glacier of mount everest (2010)

    This is the flow data set observed in 2010 by the glacier hydrological station in the upper reaches of the Rongbu River on Mount Everest, Tibet. The measured section position is 28º22'03''N, 86º56'53' 'E, with an altitude of 4290 meters. It is measured by an LS20B propeller-type current meter by the one-point method. All the data were observed and collected in strict accordance with the Equipment Operating Specifications.

    2019-09-14 334 8 View Details

  • Dataset of concentrations of atmospheric and water POPs in Nam Co (2012-2014)

    Dataset of concentrations of atmospheric and water POPs in Nam Co (2012-2014)

    This data set is the concentrations of atmospheric and water POPs in Nam Co, including time series of gas phase OCP, PCBs, PAHs and particulate PAHs in the atmosphere; dissolve and particulate POPs in water. An active air sampler (AAS) was deployed on the roof of Nam Co Monitoring and Research Station for Multisphere Interactions (NCMORS) and the air monitoring was conducted for two consecutive years from September 2012 to September 2014. The flow rate of AAS was 60 L min-1 and the air samples were collected every 2 weeks with a volume of approximately 600 m3 for each sample. The air stream passes first through glass fiber filters (GFFs 0.7 μm, Whatman) to collect the total suspended particulates (TSP) and then through polyurethane foam (PUF, 7.5×6 cm diameter) to retain the POPs in gas phase. Fifteen sites around the Nam Co Lake (surface lake water, 0–1 m depth) were selected to obtain the spatial distribution of POPs in lake water. The water samples (200 L) were filtered with GFFs to obtain the total suspended particulate matter (SPM), and then pumped through an XAD-2 resin column to collect the dissolved phase compounds. All the samples were analyzed at Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Chinese Academy of Sciences. The samples were Soxhlet-extracted, purified on an aluminium/silica column (i.d. 8 mm), a gel permeation chromatography (GPC) column subsequently, and were detected on a gas chromatograph with an ion-trap mass spectrometer (GC-MS, Finnigan Trace GC/PolarisQ) operating under MS–MS mode. A CP-Sil 8CB capillary column (50 m ×0.25 mm, film thickness 0.25 μm) was used for OCPs and PCBs and a DB-5MS column (60 m ×0.25mm, film thickness 0.25 μm) was used for PAHs. Field blanks and procedural blanks were prepared. The recoveries ranged from 64% to 112% for OCPs, and 65% to 92% forPAHs. The reported concentrations were not corrected for recoveries.

    2019-09-15 141 1 View Details

  • Monthly standard weather station dataset in Sanjiangyuan (1957-2015)

    Monthly standard weather station dataset in Sanjiangyuan (1957-2015)

    Monthly meteorological data of Sanjiangyuan includes 32 national standard meteorological stations. There are 26 variables: average local pressure, extreme maximum local pressure, date of extreme maximum local pressure, extreme minimum local pressure, date of extreme minimum local pressure, average temperature, extreme maximum temperature, date of extreme maximum temperature, extreme minimum temperature and date of extreme minimum temperature, average temperature anomaly, average maximum temperature, average minimum temperature, sunshine hours, percentage of sunshine, average relative humidity, minimum relative humidity, date of occurrence of minimum relative humidity, precipitation, days of daily precipitation >=0.1mm, maximum daily precipitation, date of maximum daily precipitation, percentage of precipitation anomaly, average wind speed, maximum wind speed, date of maximum wind speed, maximum wind speed, wind direction of maximum wind speed, wind direction of maximum wind speed and occurrence date of maximum wind speed. The data format is txt, named by the site ID, and each file has 26 columns. The names and units of each column are explained in the SURF_CLI_CHN_MUL_MON_readme.txt file. site_id lat lon elv name_cn 52754 37.33 100.13 8301.50 Gangcha 52833 36.92 98.48 7950.00 Wulan 52836 36.30 98.10 3191.10 Dulan 52856 36.27 100.62 2835.00 Qiapuqia 52866 36.72 101.75 2295.20 Xining 52868 36.03 101.43 2237.10 Guizhou 52908 35.22 93.08 4612.20 Wudaoliang 52943 35.58 99.98 3323.20 Xinghai 52955 35.58 100.75 8120.00 Guinan 52974 35.52 102.02 2491.40 Tongren 56004 34.22 92.43 4533.10 Togton He 56018 32.90 95.30 4066.40 Zaduo 56021 34.13 95.78 4175.00 Qumalai 56029 33.02 97.02 3681.20 Yushu 56033 34.92 98.22 4272.30 Maduo 56034 33.80 97.13 4415.40 Qingshui River 56038 32.98 98.10 9200.00 Shiqu 56043 34.47 100.25 3719.00 Guoluo 56046 33.75 99.65 3967.50 Dari 56065 34.73 101.60 8500.00 Henan 56067 33.43 101.48 3628.50 Jiuzhi 56074 34.00 102.08 3471.40 Maqu 56080 35.00 102.90 2910.00 Hezuo 56106 31.88 93.78 4022.80 Suo County 56116 31.42 95.60 3873.10 Dingqing 56125 32.20 96.48 3643.70 Nangqian 56128 31.22 96.60 3810.00 Leiwuqi 56137 31.15 97.17 3306.00 Changdu 56151 32.93 100.75 8530.00 Banma 56152 32.28 100.33 8893.90 Seda

    2019-05-28 660 25 View Details

  • Yulong snow mountain glacier No.1, 4 506 m altitude the daily average meteorological observation dataset (2014-2018)

    Yulong snow mountain glacier No.1, 4 506 m altitude the daily average meteorological observation dataset (2014-2018)

    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.

    2019-11-12 116 2 View Details

  • 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.

    2019-09-12 541 21 View Details

  • Hydrological dataset of China alpine region surface process and environmental observation network (2018)

    Hydrological dataset of China alpine region surface process and environmental observation network (2018)

    "1)Data content (including elements and meanings): hydrological data set of 7 rivers of HORN in Pan-Third pole 2)Data source and processing method: 7 rivers of HORN, field observation Excel format 3)Data quality description: site day 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.

    2019-09-13 638 29 View Details

  • 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.

    2019-09-12 385 19 View Details

  • Geocryological regionalization and classification map of the frozen soil in China (1:10,000,000) (2000)

    Geocryological regionalization and classification map of the frozen soil in China (1:10,000,000) (2000)

    These data are digitized for the Geocryological Regionalization and Classification Map of the Frozen Soil in China (1:10 million) (Guoqing Qiu et al., 2000; Youwu Zhou et al., 2000), adopting a geocryological regionalization and classification dual series system. The geocryological regionalization system and classification system are used on the same map to reflect the commonality and individuality of the formation and distribution of frozen soil at each level. The geocryological regionalization system consists of three regions of frozen soil: (1) the frozen soil region of eastern China; (2) the frozen soil region of northwestern China; and (3) the frozen soil region of southwestern China (Tibetan Plateau). Based on the three large regions, 16 regions and several subregions are further divided. In the division of the geocryological boundary in the frozen soil area, the boundary between major regions I and III mainly consults the results of Bingyuan Li (1987). The boundary between major regions II and III is the northern boundary of the Tibetan Plateau, which is the Kunlun Mountains-Altun Mountains-Northern Qilian Mountains and the piedmont line. The boundary between major regions I and II is in the area of Helan Mountain-Langshan Mountain. The boundary of the secondary region is divided by the geomorphological conditions in regions II and III. However, in region I, it is mainly divided by the ratio of the annual temperature range A to the annual mean temperature T, and the frozen depths of various regions are taken into consideration. The classification system is divided into 8 types based on the continuity of frozen soil, the time of existence of frozen soil and the seasonal frozen depth. The various classifications of boundaries are mainly taken from the "Map of Snow, Ice and Frozen Ground in China" (1:4 million) (Yafeng Shi et al., 1988) and consult some new materials, whereas the seasonal frozen soil boundary is mainly based on the weather station data. The definitions of each classification are as follows: (1) Large permafrost: the continuous coefficient is 90%-70%; (2) Large-island permafrost: the continuous coefficient is 70%-30%; (3) Sparse island-shaped permafrost: the continuous coefficient is <30%; (4) Permafrost in the mountains; (5) Medium-season seasonal frozen soil: the maximum seasonal frozen depth that can be reached is >1 m; (6) Shallow seasonal frozen soil: the maximum seasonal frozen depth that can be reached is <1 m; (7) Short-term frozen soil: less than one month of storage time; and (8) Nonfrozen soil. According to the data, China's permafrost areas sum to approximately 2.19 × 106 km², accounting for 22.83% of China's territory. Among those areas, the mountain permafrost is found over 0.42×106 km2, which is 4.39% of the territory of China. The seasonal frozen soil area is approximately 4.76×106 km², accounting for 49.6% of China's territory, and the instantaneous frozen soil area is approximately 1.86×106 km², i.e., 19.33% of China's territory. For more information, please see the references (Youwu Zhou et al., 2000).

    2019-09-11 17015 135 View Details

  • 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.

    2019-09-12 318 10 View Details

  • Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (an observation system of meteorological elements gradient of Alpine meadow and grassland ecosystem superstation, 2018)

    Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (an observation system of meteorological elements gradient of Alpine meadow and grassland ecosystem superstation, 2018)

    This dataset includes data recorded by the Qinghai Lake integrated observatory network obtained from an observation system of Meteorological elements gradient of the Alpine meadow and grassland ecosystem Superstation from August 31 to December 24, 2018. The site (98°35′41.62″E, 37°42′11.47″N) was located in the alpine meadow and alpine grassland ecosystem, near the SuGe Road in Tianjun County, Qinghai Province. The elevation is 3718m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP155; 3, 5, 10, 15, 20, 30, and 40 m, towards north), wind speed and direction profile (windsonic; 3, 5, 10, 15, 20, 30, and 40 m, towards north), air pressure (PTB110; 3 m), rain gauge (TE525M; 10m of the platform in west by north of tower), four-component radiometer (CNR4; 6m, towards south), two infrared temperature sensors (SI-111; 6 m, towards south, vertically downward), photosynthetically active radiation (PQS1; 6 m, towards south, each with one vertically downward and one vertically upward, soil heat flux (HFP01; 3 duplicates below the vegetation; -0.06 m), soil temperature profile (109; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m), soil moisture profile (CS616; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m). The observations included the following: air temperature and humidity (Ta_3 m, Ta_5 m, Ta_10 m, Ta_15 m, Ta_20 m, Ta_30 m, and Ta_40 m; RH_3 m, RH_5 m, RH_10 m, RH_15 m, RH_20 m, RH_30 m, and RH_40 m) (℃ and %, respectively), wind speed (Ws_3 m, Ws_5 m, Ws_10 m, Ws_15 m, Ws_20 m, Ws_30 m, and Ws_40 m) (m/s), wind direction (WD_3 m, WD_5 m, WD_10 m, WD_15 m, WD_20 m, WD_30m, and WD_40 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_1 and IRT_2) (℃), soil heat flux (Gs_1, Gs_2, and Gs_3) (W/m^2), soil temperature (Ts_5cm、Ts_10cm、Ts_20cm、Ts_40cm、Ts_80cm、Ts_120cm、Ts_200cm、Ts_300cm、Ts_400cm) (℃), soil moisture (Ms_5cm、Ms_10cm、Ms_20cm、Ms_40cm、Ms_80cm、Ms_120cm、Ms_200cm、Ms_300cm、Ms_400cm) (%, volumetric water content), photosynthetically active radiation of upward and downward (PAR_D_up and PAR_D_down) (μmol/ (s m-2)). 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 missing data were denoted by -6999. (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: 2018/8/31 10:30. Moreover, suspicious data were marked in red.

    2019-09-15 407 36 View Details

  • Data on the concentrations of persistent organic pollutants and total suspended particulate in the atmosphere at a station in Southeast Tibet (2008-2011)

    Data on the concentrations of persistent organic pollutants and total suspended particulate in the atmosphere at a station in Southeast Tibet (2008-2011)

    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.

    2019-09-15 323 4 View Details

  • 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

    2019-09-13 563 21 View Details

  • The concentration dataset of persistent organic pollutants in the atmosphere, lake water and fish bodies in Namco (2012-2014)

    The concentration dataset of persistent organic pollutants in the atmosphere, lake water and fish bodies in Namco (2012-2014)

    The concentration data set of persistent organic pollutants in the atmosphere, lake water and fish bodies in Namco from 2012 to 2014 includes concentration time series of atmospheric gaseous organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs), atmospheric gaseous polycyclic aromatic hydrocarbons (PAHs), atmospheric particulate PAHs, dissolved persistent organic pollutants (POPs) in lake water, POPs in suspended particles of lake water and POPs in bodies of Gymnocypris namensis. The contents of the data set are all measured data. (1) The atmospheric samples were collected from the Integrated Observation and Research Station of Multisphere in Namco by the atmospheric active sampler. The flow rate of the sampler is 60 L min-1, which collects data every other day. One sample is generated every half month, and the sampling volume is approximately 600 m³. Each sample includes a glass fiber filter (GFF, 0.45 μm, Whatman) that adsorbs particulate POPs and a polyurethane foam (PUF, 7.5 x 6 cm) that collects gaseous POPs. (2) Fifteen sampling points were selected along Namco to collect surface lake water samples at a water depth of 0-1 m and with a volume of 200 L. The total suspended particulates are obtained by filtering the water samples with a 0.7 μm GFF membrane, and then the dissolved POPs in the water are collected using a solid phase extraction column packed with XAD-2. (3) Gymnocypris namensis is the most widely distributed fish in Namco. A total of 35 samples of different sizes were collected, and the concentration of POPs in the back muscle samples was analyzed. Each medium sample was prepared and analyzed by the Key Laboratory of Tibetan Environment Changes and Land Surface Processes of CAS. The sample preparation steps include Soxhlet extraction, silica-alumina column purification, removal of macromolecular impurities by a GPC column, concentration and constant volume. The analytical test instrument was a gas chromatography-mass spectrometer (GC-MS, Finnigan-Trace GC/PolarisQ) manufactured by American Thermoelectric Corporation. The column separating OCPs and PCBs was a CP-Sil 8CB capillary column (50 m × 0.25 mm × 0.25 μm), and the column separating PAHs was a DB-5MS capillary column (60 m × 0.25 mm × 0.25 μm). Sampling and laboratory analysis procedures followed strict quality control measures with lab blanks and field blanks. The detection limit of the compound is the average of the concentration of the corresponding compound in the field blank plus 3 times the standard deviation; if the compound is not detected in the field blank, the signal-to-noise ratio, 10 times the lowest concentration of the working curve, will be considered as the detection limit. Data below the detection limit are considered undetected and labeled as BDL; data marked in italics are detected by 1/2 times the detection limit. The recovery of PAHs is between 65% and 92%, the recovery of OCPs is between 64% and 112%, and the sample concentration is not corrected using recovery.

    2019-09-14 444 3 View Details

  • 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.

    2019-09-12 389 3 View Details

  • Central Asian meteorological station observation dataset (2017-2018)

    Central Asian meteorological station observation dataset (2017-2018)

    Central Asian meteorological station observation data set includes field observation data of temperature, precipitation, wind direction and speed, relative humidity, air pressure, radiation, soil heat flux, sunshine time and soil temperature at 10 field weather stations in central Asia. The 10 field stations cover different ecosystem types such as farmland, forest, grassland, desert, desert, wetland, plateau and mountain. The original meteorological data collected by the ground meteorological observation stations in this data set are obtained after format conversion after screening and auditing. The data quality is good. Various types of climate in the Middle East, fragile ecological environment, the frequent meteorological disasters, the establishment of the data set for long-term ecological environment monitoring, disaster prevention and mitigation in central Asia, central Asia, climate change and ecological environment in the areas of study provides data support, ecological environment monitoring in central Asia has been obtained in the study of the application.

    2019-09-14 404 16 View Details

  • Meteorological observation data of the terminus of Naimona'nyi Glacier (2011-2017)

    Meteorological observation data of the terminus of Naimona'nyi Glacier (2011-2017)

    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.

    2019-11-17 393 1 View Details

  • Atmospheric heat source/sink dataset over the Tibetan Plateau based on satellite and routine meteorological observations (1984-2015)

    Atmospheric heat source/sink dataset over the Tibetan Plateau based on satellite and routine meteorological observations (1984-2015)

    The Tibetan Plateau (TP), acting as a large elevated land surface and atmospheric heat source during spring and summer, has a substantial impact on regional and global weather and climate. To explore the multi-scale temporal variation in the thermal forcing effect of the TP,The data set of atmospheric heat source/sink in Tibetan Plateau was prepared as a quantitative analysis tool for calculating heat budget of gas column. the atmospheric heat source/sink dataset consists of three variables: surface sensible heat flux SH, latent heat release LH and net radiation flux RC. here we calculated the surface sensible heat and latent heat release based on 6-h routine observations at 80 (32) meteorological stations during the period 1979–2016:air temperature at 1.5 m and surface temperature and wind speed at 10 m are used to calculate surface sensible heat flux,the latent heat release is estimated precipitation data.The satellite datasets used to calculate the net radiation flux were the Global Energy and Water Cycle Experiment surface radiation budget satellite radiation(GEWEX/SRB) and Clouds and Earth’s Radiant Energy Systems/Energy Balanced And Filled (CERES/EBAF). The monthly shortwave and longwave radiation fluxes at the surface and at the top of the atmosphere (TOA) in GEWEX/SRB and CERES/EBAF were utilized to obtain the net radiation flux for the period 1984–2015 via statistical methods。

    2019-09-14 1133 20 View Details

  • Meteorological observation data in an alpine steppe site of Shenzha Station (2015-018)

    Meteorological observation data in an alpine steppe site of Shenzha Station (2015-018)

    (1)This data set provides atmospheric temperature (2 meters above land surface), vapor content, precipitation, press, wind velocity and solar radiation (since 2015). (2)All data were generated using AWS (auto weather station), and been calculated their daily average. (3)All data are presented here are raw data, after being evaluated regarding their quality. (4)This data set could be used in background description for related studies.

    2019-09-13 152 12 View Details

  • The lake level observation data of Lake Namco from the Integrated Observation and Research Station of Multisphere in Namco (2007-2016)

    The lake level observation data of Lake Namco from the Integrated Observation and Research Station of Multisphere in Namco (2007-2016)

    The daily lake level observation data of lake Namco obtained from the Integrated Observation and Research Station of Multisphere in Namco in summers during 2007 to 2016. Every winter, the water gauge is destroyed by the lake ice, and it is reinstalled every summer. Taking the observational data (beginning with 0 cm) of the beginning of every year as a reference, an observational sequence is generated every year. The data set was processed by forming a continuous time series after the raw data were quality-controlled to meet the needs of lake hydrology research. Water level, unit: cm.

    2019-09-15 305 18 View Details

  • 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 15306 87 View Details