The data set includes carbon isotope data of different regions of the Tibetan Plateau and different environmental (carbon isotope data of black carbon and organic carbon in aerosols from 10 typical stations of the Qinghai Tibet Plateau, carbon isotope data of black carbon and water insoluble organic carbon in 11 snow pits in different years, and carbon isotope data of water-soluble organic carbon in monsoon precipitation from 11 stations of the Qinghai Tibet Plateau and its surrounding areas), All samples were collected at each site, and the content and δ 13C and Δ 14C data, which can be used to accurately assess the contribution proportion of atmospheric carbon aerosols, carbon particles deposited on glaciers and water-soluble organic carbon in precipitation from fossil fuels and biomass fuels.
LI Chaoliu
This data set includes the light absorption data of carbon components in the atmosphere and precipitation at typical stations on the Tibetan Plateau (Ranwu (2018-2021), Namco (2013-2016), Everest (2013-2016), Lulang (2015-2016)). All samples were collected on the spot from various sampling points. The concentrations of black carbon and water-soluble organic carbon, as well as the light absorption data were measured, using the index (MAC value) representing the light absorption capacity, The MAC values of light absorption of water-soluble organic carbon and black carbon are calculated. This data is of great significance for evaluating the radiative forcing of carbon particles in the atmosphere, and is an important basic data input for model simulation.
LI Chaoliu
Based on the monthly precipitation data of 262 rain gauges, WRF and ERA5 precipitation data in the Yarlung Zangbo River basin, the daily precipitation data with a resolution of 10km from 1951 to 2020 in the Yarlung Zangbo River basin and seven sub basins are reconstructed using random forest learning algorithm. This data has been verified by the single point of the station and performs well in terms of annual and seasonal changes. And the data has been reverse evaluated by the hydrological model, which is used to drive the VIC hydrological model to simulate the runoff change of Yajiang River basin and each sub basin, and verified by the measured runoff, MODIS and glacier cataloging data. On the basis of the original first edition, this data has considered the spatial distribution characteristics of precipitation, which can better describe the precipitation characteristics in alpine regions.
SUN He
Near-surface air temperature variability and the reliability of temperature extrapolation within glacierized regions are important issues for hydrological and glaciological studies that remain elusive because of the scarcity of high-elevation observations. Based on air temperature data in 2019 collected from 12 automatic weather stations, 43 temperature loggers and 6 national meteorological stations in six different catchments, this study presents air temperature variability in different glacierized/nonglacierized regions and assesses the robustness of different temperature extrapolations to reduce errors in melt estimation. The results show high spatial variability in temperature lapse rates (LRs) in different climatic contexts, with the steepest LRs located on the cold-dry northwestern Tibetan Plateau and the lowest LRs located on the warm-humid monsoonal-influenced southeastern Tibetan Plateau. Near-surface air temperatures in high-elevation glacierized regions of the western and central Tibetan Plateau are less influenced by katabatic winds and thus can be linearly extrapolated from off-glacier records. In contrast, the local katabatic winds prevailing on the temperate glaciers of the southeastern Tibetan Plateau exert pronounced cooling effects on the ambient air temperature, and thus, on-glacier air temperatures are significantly lower than that in elevation-equivalent nonglacierized regions. Consequently, linear temperature extrapolation from low-elevation nonglacierized stations may lead to as much as 40% overestimation of positive degree days, particularly with respect to large glaciers with a long flowline distances and significant cooling effects. These findings provide noteworthy evidence that the different LRs and relevant cooling effects on high-elevation glaciers under distinct climatic regimes should be carefully accounted for when estimating glacier melting on the Tibetan Plateau.
YANG Wei
Mercury is a global pollutant.The Qinghai-Tibet Plateau is adjacent to South Asia, which currently has the highest atmospheric mercury emissions, and could be affected by long-distance transport.The history of atmospheric mercury transport and deposition can be well reconstructed using ice cores and lake cores. The history of atmospheric mercury deposition since the industrial revolution was reconstructed based on 8 lake cores and 1 ice core from the Tibetan Plateau and the southern slope of the Himalayas.This data set contains 8 lake core data from Namtso, Bangongtso, Linggatso, Guanyong Lake, Tanggula Lake, Gosainkunda Lake, Gokyo Lake and Phewa Lake, and 1 ice core data .The resolution of ice core data is 1 year, lake core data is 2~20 years, and the data include mercury concentration and flux.
KANG Shichang
The data set includes annual mass balance of Naimona’nyi glacier (northern branch) from 2008 to 2018, daily meteorological data at two automatic meteorological stations (AWSs) near the glacier from 2011 to 2018 and monthly air temperature and relative humidity on the glacier from 2018 to 2019. In the end of September or early October for each year , the stake heights and snow-pit features (snow layer density and stratigraphy) are manually measured to derive the annual point mass balance. Then the glacier-wide mass balance was then calculated （Please to see the reference). Two automatic weather stations (AWSs, Campbell company) were installed near the Naimona’nyi Glacier. AWS1, at 5543 m a. s.l., recorded meteorological variables from October 2011 at half hourly resolution, including air temperature (℃), relative humidity (%), and downward shortwave radiation (W m-2) . AWS2 was installed at 5950 m a.s.l. in October 2010 at hourly resolution and recorded wind speed (m/s), air pressure (hPa), precipitation (mm). Data quality: the quality of the original data is better, less missing. Firstly, the abnormal data in the original records are removed, and then the daily values of these parameters are calculated. Two probes (Hobo MX2301) which record air temperature and relative humidity was installed on the glacier at half hour resolution since October 2018. The observed meteorological data was calculated as monthly values. The data is stored in Excel file. It can be used by researchers for studying the changes in climate, hydrology, glaciers, etc.
ZHAO Huabiao
The data set contains the stable oxygen isotope data of ice core from 1864 to 2006. The ice core was obtained from Noijinkansang glacier in the south of Southern Tibetan Plateau, with a length of 55.1 meters. Oxygen isotopes were measured using a MAT-253 mass spectrometer (with an analytical precision of 0.05 ‰) at the Key Laboratory of CAS for Tibetan Environment and Land Surface Processes, China. Data collection location: Noijinkansang glacier (90.2 ° e, 29.04 ° n, altitude: 5950 m)
GAO Jing
This data set contains oxygen isotope data from 1010 to 2005. It is used to study environmental changes in the Xixiabangma area of the Tibetan Plateau. The ice core oxygen isotope is measured by instrument. This data set is obtained from laboratory measurements. The data are obtained immediately after the completion of the instrument or experiment. The samples and data are collected in strict accordance with relevant operating procedures at all stages and comply with the laboratory operating standards. This data contains two fields: Field 1: The time AD. Field 2: The oxygen isotope ‰.
TIAN Lide
This data set comprises the oxygen isotope and geochemical data of two deep-drilled ice cores drilled in the Puruogangri ice sheet (33°55'N, 89°05'E, altitude: 6070 meters) in the central Tibetan Plateau in 2000. The ice core depths are 118.4 and 214.7 meters, respectively. Source of the data: National Centers for Environmental Information (http://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/ice-core) . The data set contains 6 tables, which are the average values of 1 oxygen isotope per meter of the Puruogangri ice core, the 10-year average data of 1 oxygen isotope of the Puruogangri ice core, the average values of 2 oxygen isotope and the soluble aerosol concentrations per meter of the Puruogangri ice core, the 5-year average data of 2 oxygen isotope and aerosol concentrations of Puruogangri ice core, 10-year average data of 2 oxygen isotope and aerosol concentrations of the Puruogangri ice core, and the 100-year average values of 2 oxygen isotopic and aerosol concentrations of the Puruogangri ice core. The information on the fields is as follows: Table 1: the average values of 1 oxygen isotope per meter of the Puruogangri ice core Field: Field Name [Dimensions (Unit of Measure)] Field 1: Depth [m] Field 2: δ18° [‰] Table 2: the 10-year average data of 1 oxygen isotope of the Puruogangri ice core Field: Field Name [Dimensions (Unit of Measure)] Field 1: Start time [Dimensionless] Field 2: End time [Dimensionless] Field 3: δ18° [‰] Table 3: the average values of 2 oxygen isotope and soluble aerosol concentration per meter of the Puruogangri ice core Field: Field Name [Dimensions (Unit of Measure)] Field 1: Depth [m] Field 2: Dust (diameter 0.63-20 um) [particles/mL] Field 3: 18° [‰] Field 4: F- [ppb] Field 5: Cl- [ppb] Field 6: SO42- [ppb] Field 7: NO3- [ppb] Field 8: Na+ [ppb] Field 9: NH4+ [ppb] Field 10: K+ [ppb] Field 11: Mg2+ [ppb] Field 12: Ca2+ [ppb] Table 4: the 5-year average data of 2 oxygen isotope and aerosol concentration of the Puruogangri ice core Field: Field Name [Dimensions (Unit of Measure)] Field 1: Start time [Dimensionless] Field 2: End time [Dimensionless] Field 3: δ18° [‰] Field 4: Accumulation [cm/yr] Field 5: Dust (diameter 0.63-20 um) [particles/mL] Field 6: F- [ppb] Field 7: Cl- [ppb] Field 8: SO42- [ppb] Field 9: NO3- [ppb] Field 10: Na+ [ppb] Field 11: NH4+ [ppb] Field 12: K+ [ppb] Field 13: Mg2+ [ppb] Field 14: Ca2+ [ppb] Table 5: the 10-year average data of 2 oxygen isotope and aerosol concentrations of the Puruogangri ice core Field: Field Name [Dimensions (Unit of Measure)] Field 1: Start time [Dimensionless] Field 2: End time [Dimensionless] Field 3: δ18° [‰] Field 4: Dust (diameter 0.63-20 um) [particles/mL] Field 5: F- [ppb] Field 6: Cl- [ppb] Field 7: SO42- [ppb] Field 8: NO3- [ppb] Field 9: Na+ [ppb] Field 10: NH4+ [ppb] Field 11: K+ [ppb] Field 12: Mg2+ [ppb] Field 13: Ca2+ [ppb] Table 6: the 100-year average values of 2 oxygen isotopic and aerosol concentrations of the Puruogangri ice core Field: Field Name [Dimensions (Unit of Measure)] Field 1: The last year of the interval [Dimensionless] Field 2: δ18° [‰] Field 3: Dust (diameter 0.63-20 um) [particles/mL] Field 4: F- [ppb] Field 5: Cl- [ppb] Field 6: SO42- [ppb] Field 7: NO3- [ppb] Field 8: Na+ [ppb] Field 9: NH4+ [ppb] Field 10: K+ [ppb] Field 11: Mg2+ [ppb] Field 12: Ca2+ [ppb]
National Centers for Environmental Information (NCEI)
This data set contains conventional ice surface meteorological data for Parlung Glacier No. 4 and debris-covered 24K Glacier in Southeast Tibet from June to September 2016. Meteorological observation instrument model: Campbell data logger CR1000; precipitation observation instrument models: T200B weighing rain cylinder for Parlung Glacier No. 4 and RG-3 tipping rain gauge for 24K Glacier. Acquisition time: 60 minutes. The data were collected automatically, and the data set was processed to form a continuous hourly time series after quality controlling the original data. The data collection sites were Parlung Glacier No. 4 (29.252°N; 96.932°E; 4800 m) and the debris-covered 24K glacier in Southeast Tibet (29.766°N; 95.712°E; 3900 m). Data for Parlung Glacier No. 4 at an elevation of 4800 m: Temperature, unit: °C Relative humidity, unit: % Wind speed, unit, m/s Downward shortwave radiation, unit: W/m2 Upward shortwave radiation, unit: W/m2 Downward longwave radiation, unit: W/m2 Upward longwave radiation, unit: W/m2 Precipitation, unit: mm Data for debris-covered 24K Glacier at an elevation of 3900 m (debris thickness: 25 cm): Temperature, unit: °C Relative humidity, unit: % Wind speed, unit, m/s Downward shortwave radiation, unit: W/m2 Upward shortwave radiation, unit: W/m2 Downward longwave radiation, unit: W/m2 Upward longwave radiation, unit: W/m2 Precipitation, unit: mm Temperature with a debris thickness of 5 cm, unit: °C Temperature with a debris thickness of 10 cm, unit: °C Temperature with a debris thickness of 20 cm, unit: °C
YANG Wei
Xiaodongkemadi glacier, located in Tanggula Mountain, is a continental glacier. The glacier is a compound valley glacier formed by the confluence of a southward main glacier (also known as dadongkemadi glacier) and a Southwest Branch glacier (also known as xiaodongkemadi glacier). The daily temperature and humidity observation data of 6 points in xiaodongkemadi, 4 points in Yangbajing and 4 points in hariqin from 2012 to 2015.
XU Baiqing
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