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: 71
This dataset contains the annual variation of runoff from the major hydrological stations in the Yarlung Zangbo River (annual average runoff volume, annual extremum ratio, coefficient of variation, etc.). It can be used to study the hydrological characteristics of the Yarlung Zangbo River. The original data are the national hydrological station data, and the quality requirements are the same as the national standards. Spatial Coverage: 4 hydrological stations in the main streams of the Yarlung Zangbo River basin, which are Lazi, Nugesha, Yangcun and Nuxia. This data sheet has five fields. Field 1: Station Name Field 2: Annual average runoff volume Field 3: Annual Extreme Ratio Field 4: Coefficient of variation Field 5: Data Series Length
2019-09-12 1140 55 View Details
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: %
2019-09-12 627 13 View Details
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.
2019-09-12 715 15 View Details
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 1060 22 View Details
The water level observation data set of lakes on the Tibetan Plateau contains the daily variations of water levels for three lakes: Zhari Namco, Bamco and Dawaco. The lake water level was obtained by a HOBO water level gauge (U20-001-01) installed on the lakeshore, then corrected using the barometer installed on the shore or pressure data of nearby weather stations, and then the real water level changes were obtained. The accuracy was less than 0.5 cm. The items of this data set are as follows: Daily variation data of water level in Zhari Namco from 2009 to 2014; Daily variation data of water level in Bamco from 2013 to 2014; Daily variation data of water level in Dawaco from 2013 to 2014. Water level, unit: m.
2019-09-11 1003 42 View Details
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 17887 143 View Details
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.
2019-09-11 686 10 View Details
This data set contains the temperature anomaly series for each quarter and month of the years from January, 1951 to December, 2006 on the Tibetan Plateau. Based on the “China Homogenized Historical Temperature Data Set (1951–2004) Version 1.0” and the daily average temperature data from 2005 to 2006, the monthly average temperature of 123 sites on the Tibetan Plateau and its neighboring areas were gridded using the Climate Anomaly Method (CAM). Further, the average monthly temperature anomaly sequences from 1951 to 2006 were established using the area weighting factor method. To maximize the use of the observation data, the method using the data at a nearby reference station to correct the short series of the climatic standard values of the air temperature data is emphatically discussed. Reference: Yu Ren, Xueqin Zhang, Lili Peng. Construction and Analysis of Mean Air Temperature Anomaly Series for the Qinghai-Xizang Plateau during 1951-2006. Plateau Meteorology, 2010. The “China Homogenized Historical Temperature Data Set (1951–2004) Version 1.0” and the daily average temperature data from 2005 to 2006 meet the relevant national standards. There are five fields in the monthly temperature anomaly data table. Field 1: Year Field 2: Month Field 3: Number of grids Number of grids included in the calculation Field 4: Number of sites Number of sites included in the calculation Field 5: Monthly Temperature Anomaly Unit °C There are five fields in the year and quarter temperature anomaly data table. Field 1: Year Field 2: Quarter Field 3: Number of grids Number of grids included in the calculation Field 4: Number of sites Explanation: Number of sites included in the calculation Field 5: Temperature anomaly °C In the quarter field: 1. If it is null, it is the annual temperature anomaly 2. DJF: Winter (Last December to this February) temperature anomaly °C 3. MAM: Spring (March-May) temperature anomaly °C 4. JJA: Summer (June-August) temperature anomaly °C 5. SON: Fall (September-November) temperature anomaly °C Data accuracy: the monthly average temperature anomaly to the third decimal places, the annual and quarterly average temperature anomaly to the second decimal places.
2019-09-11 572 19 View Details
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.
2019-09-11 601 6 View Details
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
2019-09-11 724 13 View Details
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
2019-04-18 702 19 View Details