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 covers the contents of black carbon and water insoluble organic carbon in precipitation at Namco Station (2013-2017), Lulang Station (2014-2017), Everest Station (2015-2016) and Lhasa Station (2017-2018, This data can be used to evaluate the temporal and spatial changes of the wet deposition rate of water insoluble carbon particles in typical areas of the Tibetan Plateau, and is an important input data for model simulation.
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
Glacial lake inventory from 1977-2017, based on Landsat MSS/TM/ETM+/OLI imagery, uses a semi-automatic water body classification method to distinguish between water body and non-water body information, then extracts the lake boundaries and visually checks and manually edits them by comparison with the original Landsat images. The MSS sensor data was used in 1977 with a resolution of 60 m. Image data used after 1987 had a resolution of 30 m.The relationship between glacial meltwater and glacial lake recharge was determined from RGI 6.0 and Google Earth.
KHADKA Nitesh , ZHANG Guoqing
Carbon particles are an important radiative forcing factor in the atmosphere. Their concentration and composition vary greatly in time and space, especially in remote areas. This data set reports the total suspended particulate matter (TSP), total carbon (TC) and water insoluble particulate carbon (IPC) of PM2.5 at two stations in the remote area of the eastern Qinghai Tibet Plateau (Hongyuan) Δ 14C and δ 13C, the area is affected by severe air pollution from southwest China. The contribution rates of TC fossil fuels in TSP and PM2.5 samples are 18.91 ± 7.22% and 23.13 ± 12.52% respectively, which are far lower than those in Southwest China, indicating the importance of non fossil contributions from local sources. TC in TSP samples at study site δ 13C is 27.06 ± 0.96 ‰, which is between long-distance transport sources (such as the southwest region) and local biomass combustion emissions. This data supplements the database of carbon aerosols in the east of the Tibetan Plateau.
LI Chaoliu
The data files include the extent of the Poqui watershed and multiple periods of glacial lake cataloguing. The glacial lake extent in 1964, was obtained using manual outlining methods based on geo-corrected KH-4 data; the glacial lake extent during 1976-2017, based on Landsat MSS/TM/ETM+/OLI imagery, used a semi-automatic water body classification method to distinguish between water body and non-water body information, and then extracted lake boundaries, and visually checked and manually edited by comparison with the original Landsat images.The relationship between glacial meltwater and glacial lake recharge was determined from RGI 6.0 glacier catalogues and Google Earth.
ZHANG Guoqing
The global annual lake ice phenological dataset includes the freeze-up date, break-up date for 74,245 lakes in the northern hemisphere. The dataset is divided into three parts: 1) current data, obtained from MODIS productions through a DLRM model (with parameters provided), covering the period of 2001 to 2020; 2) historical and 3) future simulation data, obtained from the temperature-based lake-specific models, for the periods of 1861-2005 and 2006-2099, respectively. The historical and future simulations were only performed for 30,063 lakes that meet the model conditions and are presented in the dataset.
WANG Xinchi
This dataset contains the flux measurements from the Huailai station eddy covariance system (EC) from April 13 to December 31 in 2021. The site (115.7923° E, 40.3574° N) was located in the maize surface, near Donghuayuan town of Huailai city in Hebei Province. The elevation is 480 m. The EC was installed at a height of 3.5 m, and the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (CSAT3&EC150) was 0 m. The raw data acquired at 10 Hz were processed using the Eddypro post-processing software, including the spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. The observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC) (class1-9). In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data collected before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 10% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day, and the missing data were replaced with -6999. Suspicious data were marked in red. There were lots of negative values of H2O density in winter where filling by -6999. The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m3), CO2 mass density (CO2, mg/m3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m2), latent heat flux (LE, W/m2), carbon dioxide flux (Fc, mg/ (m2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xls format. Detailed information can be found in the suggested references. For more information, please refer to Guo et al. (2020) (for sites information), Liu et al. (2013) for data processing) in the Citation section.
LIU Shaomin, XIAO Qing, XU Ziwei, BAI Junhua
This dataset contains the flux measurements from the large aperture scintillometer (LAS) at Huailai station. There were two types of LASs: German BLS450 and zzLAS. The observation periods were from January 1 to December 31, 2021. The site ( (north: 115.7825° E, 40.3522° N; south: 115.7880° E, 40.3491° N) was located in the Donghuahuan town of Huailai city, Hebei Province. The elevation is 480 m. The underlying surface between the two towers contains mainly maize. The effective height of the LASs was 14 m; the path length was 1870 m. Data were sampled at 1 min intervals. Raw data acquired at 1 min intervals were processed and quality-controlled. The data were subsequently averaged over 30 min periods. The main quality control steps were as follows. (1) The data were rejected when Cn2 was beyond the saturated criterion. (2) Data were rejected when the demodulation signal was small. (3) Data were rejected within 1 h of precipitation. (4) Data were rejected at night when weak turbulence occurred (u* was less than 0.1 m/s). The sensible heat flux was iteratively calculated by combining with meteorological data and based on Monin-Obukhov similarity theory. There were several instructions for the released data. (1) The data were primarily obtained from BLS450 measurements; missing flux measurements from the BLS450 were filled with measurements from the zzLAS. Missing data were denoted by -6999. (2) The dataset contained the following variables: data/time (yyyy-mm-dd hh:mm:ss), the structural parameter of the air refractive index (Cn2, m-2/3), and the sensible heat flux (H_LAS, W/m^2). (3) In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xls format. Moreover, suspicious data were marked in red. For more information, please refer to Guo et al. (2020) (for sites information), Liu et al. (2013) (for data processing) in the Citation section.
LIU Shaomin, XU Ziwei
This dataset obtained from an observation system of Meteorological elements gradient of Huailai station from January 1 to December 31, 2021. The site (115.7923° E, 40.3574° N) was located on a cropland (maize surface) which is near Donghuayuan town of Huailai city, Hebei Province. The elevation is 480 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (3, 5, 10, 15, 20, 30, and 40 m, towards north), wind speed and direction profile (3, 5, 10, 15, 20, 30, and 40 m, towards north), air pressure (in the box), rain gauge (3 m, south of tower), four-component radiometer (4 m, south of tower), two infrared temperature sensors (4 m, south of tower, vertically downward), photosynthetically active radiation (4 m, south of tower, vertically upward), soil heat flux -0.06 m), a TCAV averaging soil thermocouple probe (-0.02, -0.04 m), soil temperature profile (-0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), soil moisture profile (-0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m). The observations included the following: air temperature and humidity (Ta_3 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_10 m, Ws_15 m, Ws_20 m, Ws_30 m) (m/s), wind direction (WD_10 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) (℃), photosynthetically active radiation (PAR) (μmol/ (s m-2)), average soil temperature (TCAV, ℃), soil heat flux (Gs) (W/m^2), soil temperature (Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm, and Ts_160 cm) (℃), soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, and Ms_160 cm) (%, volumetric water content). 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: 2021-6-10 10:30. Moreover, suspicious data were marked in red. For more information, please refer to Guo et al. (2020) (for sites information), Liu et al. (2013) for data processing) in the Citation section.
LIU Shaomin, XIAO Qing, XU Ziwei, BAI Junhua
This dataset includes data obtained from the automatic weather station (AWS) at the observation system of Meteorological elements of Huailai station between January 1 and December 31, 2021. The site (115.7880° E, 40.3491° N) was located on a maize surface, which is near Donghuayuan Town of Huailai city in Hebei Province. The elevation is 480 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (5 m, north), wind speed and direction profile (10 m, north), air pressure (in the box), rain gauge (10 m), four-component radiometer (5 m, south), two infrared temperature sensors (5 m, south, vertically downward), soil heat flux (-0.06 m), soil temperature profile (0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), soil moisture profile (-0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), and a TCAV averaging soil thermocouple probe (-0.02, -0.04 m). The observations included the following: air temperature and humidity (Ta_5 m; RH_5 m) (℃ and %, respectively), wind speed (Ws_10 m) (m/s), wind direction (WD_10 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/m2), infrared temperature (IRT_1 and IRT_2) (℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm, and Ts_160 cm) (℃), soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, and Ms_160 cm) (%, volumetric water content), and average soil temperature (TCAV, ℃). 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: 2021-6-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Guo et al. (2020) (for sites information), Liu et al. (2013) (for data processing) in the Citation section.
LIU Shaomin, XU Ziwei
This dataset contains the flux measurements from the Huailai station eddy covariance system (EC) from January 1 to December 31 in 2021. The site (115.7880° E, 40.3491°N) was located in the maize surface, near Donghuayuan town of Huailai city in Hebei Province. The elevation is 480 m. The EC was installed at a height of 5 m, and the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (CSAT3&Li7500A) was 0.15 m. The raw data acquired at 10 Hz were processed using the Eddypro post-processing software, including the spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. The observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC) (class 1 to 9). In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data collected before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 10% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day, and the missing data were replaced with -6999. The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m3), CO2 mass density (CO2, mg/m3), friction velocity (ustar, m/s), stability (L), sensible heat flux (Hs, W/m2), latent heat flux (LE, W/m2), carbon dioxide flux (Fc, mg/ (m2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xls format. Detailed information can be found in the suggested references. For more information, please refer to Guo et al. (2020) (for sites information), Liu et al. (2013) for data processing) in the Citation section.
LIU Shaomin, XU Ziwei
This data set provides the lake ice phenology of 71 lakes on the Qinghai Tibet Plateau from 2001 to 2020, including the freeze-up start, freeze-up end, break-up start, break-up end, complete freezing duration, and ice cover duration. The data set was extracted from the cloud-gap-filled MODIS daily snow product based on a dynamic changed threshold. Compared with the coarse resolution passive microwave AMSR-E/2 lake ice phenology data set, the average absolute error of the freeze-up start date was 2.33-7.25 days, and the average absolute error of the break-up end date was 1.75-4.67 days. The data can provide a data basis for the relevant research on the response of the Qinghai Tibet Plateau lake system to climate change.
CAI Yu, KE Changqing
1) Data content This data set includes lake evaporation data of Bamco, La'angco in the summer and autumn of 2019-2021 and Longmuco in the summer and autumn of 2020-2021. The meteorological data required for the calculation of evaporation data are obtained from the automatic meteorological station set up at the lake side, with the observation height of 1.5m. Lake location: Bamco (90.59 ° E, 31.29 ° N), La'anco (81.24 ° E, 30.72 ° N), Longmucuo (80.47 ° E, 34.60 ° N). Coordinates of automatic weather stations: Bamco AWS (90.65 ° E, 31.30 ° N), La'anco AWS (81.22 ° E, 30.73 ° N), and Longmucuo AWS (80.43 ° E, 34.59 ° N). Time resolution: 1d Spatial resolution:- Unit: mm 2) Data source and processing method Integral conveying method. The calculation formula is as follows: LH=l_ v ρ_ a c_ E U(q_s-q_a ) E=LH/( ρ l_ v ) LH and E are latent heat and evaporation respectively. The automatic weather station erected near the lake is used for meteorological data, and the observation data used include temperature, wind speed, relative humidity, etc. at 1.5m; Lake surface temperature uses ERA5 land hourly data; The momentum roughness, moisture roughness and thermal roughness are obtained by back calculation from the data obtained by the eddy correlation instrument erected by Bamco and Laoncho. 3) Data quality description The evaporation data of Bamco Lake in 2020 obtained by calculation are compared with the evaporation data from August to October obtained by the eddy correlation instrument installed on the central island of Bamco Lake. Pearson correlation coefficient r=0.57, p=2.842E-8. 4) Data application achievements and prospects Water surface evaporation is an important link in the process of water cycle and an important topic in hydrology research. As the main part of lake water loss, it is also the basic reference data for studying land surface evaporation. The evaporation calculated based on the observation data can be used as the accurate evaporation of lakes on the Qinghai Tibet Plateau, which is an important basis for studying the water balance of lakes. By obtaining the evaporation of three lakes located in different climatic regions, we can better explore the variation law of lake water surface evaporation in different climatic regions.
MA Weiyao , MA Weiqiang*, HE Jianan , XIE Zhipeng , SU Rongmingzhu , HU Wei , MA Yaoming
Meteorological elements of the dataset include the near-surface land-air exchange parameters, such as downward/upward longwave/shortwave radiation flux, momentum flux, sensible heat flux, latent heat flux, etc. In addition, the vertical distributions of 3-dimensional wind, temperature, humidity, and pressure from the surface to the tropopause are also included. Independent evaluations were conducted for the dataset by comparison between the observational data and the most recent ERA5 reanalysis data. The results demonstrate the accuracy and superiority of this dataset against reanalysis data, which provides great potential for future climate change research.
LI Fei, Ma Shupo, ZHU Jinhuan, ZOU Han , LI Peng , ZHOU Libo
The Tibetan Plateau Subregional Dynamical Downscaling Dataset-Standard Year (TPSDD-Standard) is a high spatial-temporal resolution gridded dataset for the study of land-air exchange processes and lower atmospheric structure over the entire Tibetan Plateau, taking into account the climatic characteristics of each subregion of the Tibetan Plateau. Based on the 500 hPa multi-year average of the geopotential height field over the Tibetan Plateau, the year (2014) with the largest pattern correlation coefficient with this geopotential height field is selected as the standard year, which means that it can roughly reflect the multi-year average status of the atmosphere over the Tibetan Plateau. The temporal resolution of this data is 1 hour and the spatial resolution is 5 km. Meteorological elements of the dataset include near-surface land-air exchange parameters such as downward/upward long-wave/short-wave radiation fluxes, sensible heat fluxes, latent heat fluxes, etc. In addition, the 3-dimensional vertical distribution of wind, temperature, humidity, and pressure from the surface to the top of the troposphere is also included. The dataset was independently evaluated by comparing the observed data with the latest ERA5 reanalysis data. The results demonstrate the accuracy and superiority of the dataset, which offers great potential for future climate change studies.
LI Fei, Ma Shupo, ZHU Jinhuan, ZHOU Libo , LI Peng , ZOU Han
The extraction of glacier surface movement is of great significance in the study of glacier dynamics and material balance changes. In view of the shortcomings of the current application of autonomous remote sensing satellite data in glacier movement monitoring in China, the SAR data covering typical glaciers in alpine areas of the Qinghai Tibet Plateau from 2019 to 2020 obtained under the GF-3 satellite FSI mode was used to obtain the glacier surface velocity distribution in the study area with the help of a parallel offset tracking algorithm. With its good spatial resolution, GF-3 image has significant advantages in extracting glacier movement with small scale and slow movement, and can better reflect the details and differences of glacier movement. This study is helpful to analyze the movement law and spatio-temporal evolution characteristics of glaciers in the Qinghai Tibet Plateau under the background of climate change.
YAN Shiyong
Numerical test: The climate model used is the regional climate model RegCM4.1. RegCM4.1 developed by the Italian Research Center for Theoretical Physics (ICTP). In the test of regional model simulation, the horizontal resolution of the atmospheric model is 50 km and the vertical direction is 18 layers; Online coupling sand dust module. Sea surface temperature The sea surface temperature interpolated by OISST is used. The test includes two groups: the Middle Paleocene topographic test (MP,~60Ma BP, test name 60ma_regcm4.1_xxx. nc) and the Late Oligocene (LO,~25Ma BP, test name 25ma_regcM4.1_xxx. nc) The MP regional terrain modification test removed the northern part of the plateau and approximately replaced the terrain distribution of Asian land during the 60Ma period. BP regional terrain modification test only removed the terrain of Pamirs Plateau, approximately replacing the terrain distribution of Asian land during the 25Ma period. The sand and dust source areas of the two tests have not changed, and the sand and dust circulation process has been opened online. Output time: All tests were integrated for 22 years, using the average results of the last 20 years of each test. The data can be used to explain the difference of drought evolution in different regions around the plateau.
SUN Hui
The Antarctic McMurdo Dry Valleys ice velocity product is based on the Antarctic Ice Sheet Velocity and Mapping Project (AIV) data product, which is post-processed with advanced algorithms and numerical tools. The product is mapped using Sentinel-1/2/Landsat data and provides uniform, high-resolution (60m) ice velocity results for McMurdo Dry Valleys, covering the period from 2015 to 2020.
JIANG Liming JIANG Liming JIANG Liming
The data source of this data set is the European Space Agency (ESA) multispectral satellite Sentinel-2. It includes the annual mean data of CDOM and DOC of Qinghai Tibet Plateau lakes in 2017. Method of use: Based on the CDOM data of the measured sample points, the image reflectance information is extracted, the best prediction variable is selected through Pearson correlation analysis, and a multiple stepwise regression CDOM prediction model is constructed to obtain the CDOM results of the Qinghai Tibet Plateau water body. Because CDOM has a good correlation with DOC, DOC prediction results are calculated by CDOM. Adjustment R of the CDOM model of the final Qinghai Tibet Plateau ² Up to 0.81.
SONG Kaishan
Numerical experiments: The climate model used is the fast air sea coupling model (FAMOUS) jointly developed by the British Meteorological Office and British universities The horizontal resolution of the atmospheric model in the FAMOUS model is 5 ° × 7.5 °, 11 layers in vertical direction; The horizontal resolution of the ocean model is 2.5 ° × 3.75 °, 20 layers in vertical direction The atmosphere and ocean are coupled once a day without flux adjustment The tests included the Middle Paleocene (MP,~60Ma BP, test name flat_60ma_1xCO2_sea_3d_ * * 100yr_mean. nc) and the Late Oligocene (LO,~25Ma BP, test name orog_25ma_1xCO2_sea_3d_ * * 100yr_mean. nc) The sea land distribution data is mainly taken from the global coastline basic data set (abbreviated as Gplates, website: http://www.gplates.org/ ）Considering that the initial uplift of Cenozoic terrains such as the Qinghai Tibet Plateau started at about 50~55 Ma (Searle et al., 1987), the global terrain height was set to 0 in the MP test to omit the role of plateau terrain. At 25 Ma, Greenland (Zachos et al., 2001) and the Qinghai Tibet Plateau (for example, Wang et al., 2014; Ding et al., 2014; Rowley and Currie, 2006; DeCells et al., 2007; Polisar et al., 2009) were revised The change of ancient latitude is also considered when reconstructing the ancient topography of the Qinghai Tibet Plateau (Besse et al., 1984; Chatterjee et al., 2013; Wei et al., 2013) At the same time, referring to the change of Cenozoic atmospheric CO2 (Beerling and Royer, 2011), the atmospheric CO2 concentration in the two periods of experiments was 280 ppmv (1 ppmv=1 mg L – 1) before the industrial revolution For simplicity, all land vegetation and soil properties are set to globally uniform values, that is, various land surface properties on each land grid point except Antarctica are assigned to the global average value of non glacial land surface before the industrial revolution, which is also convenient for highlighting the impact of land sea distribution and topographic changes In addition, since we mainly discuss the average climate state and its change in the characteristic geological period on the scale of millions of years, we can omit the influence of orbital forcing, that is, the Earth's orbital parameters are set to their modern values in all experiments Output time: All tests were integrated for 1000 years, using the average results of the last 100 years of each test. This data is helpful to explore the formation and evolution mechanism of the Cenozoic monsoon and drought.
LIU Xiaodong
The global reach-level 3-hourly river flood reanalysis (GRFR) dataset includes 1) global 0.05 degree, 3-hourly/daily runoff data, 2) 3hourly/daily naturalized river discharge at 2.94 million river reaches, 3) global 3-hourly river flood events from 1980 to 2019, 4) underlying hydrography MERIT-Basins. Grounded on recent breakthroughs in global runoff hydrology, river modeling, high-resolution hydrography, and climate reanalysis, the 3-hourly river discharge record globally for 2.94 million river reaches during the 40-yr period of 1980–2019 was developed. The underlying modeling chain consists of the VIC land surface model (0.05°, 3-hourly) that is well calibrated and bias-corrected and the RAPID routing model (2.94 million river and catchment vectors), with precipitation input from MSWEP and other meteorological fields downscaled from ERA5. Flood events (above 2-yr return) and their characteristics (number, spatial distribution, and seasonality) were extracted and studied. Validations against 3-hourly flow records from 6,000+ gauges in CONUS and daily records from 14,000+ gauges globally show good modeling performance across all flow ranges, good skills in reconstructing flood events (high extremes), and the benefit of (and need for) sub-daily modeling. The GRFR database represents a pioneering effort on global reach-level flood reanalysis and may offer new opportunities for global flood studies in terms of baseline data and potential research pathways. Also, it can better help river-observing satellite missions to develop their discharge algorithms.
YANG Yuan , PAN Ming , LIN Peirong
Natural runoff simulation data products of 2.94 million river sections in the world, unit: m3/s. This data is based on the simulation of VIC hydrological process model and RAPID vector river network concentration model. The spatial resolution of the land surface hydrological process model is 0.25 °, and the river network data in the vector concentration model is extracted based on the 90-m MERIT Hydro hydrological correction terrain data product. The runoff generation part is calibrated based on the runoff characteristic values obtained by machine learning, and the grid scale runoff generation deviation correction is carried out based on the multi quantile runoff characteristic values. The data products are verified by 14000 runoff observation stations around the world, and have better verification accuracy.
LIN Peirong , PAN Ming , YANG Yuan
This data is the simulation of Antarctic sea ice density data from 2020 to 2100 under the medium emission scenario (ssp245) of the 6th International Coupled Model Comparison Program (CMIP6). The 25 mode data of CMIP6 were uniformly interpolated and then aggregated averaged. The size of sea ice density data is 0-1, the data time range is from January 2020 to December 2100, the time resolution is month, the spatial range is south of 45 ° S, and the spatial resolution is 1 ° × 1°。 This data provides the status and evolution of Antarctic sea ice under the medium emission scenario, and can provide reference for future changes in Antarctica.
LI Shuanglin, WANG Hui
Based on ESA's CCI-LC Maps data, we mapped the agricultural landscape of Central Asia, including Kazakhstan, Turkmenistan, Tajikistan, Kyrgyzstan, and Uzbekistan, for sustainable agricultural development in the five Central Asian countries, and classified the existing agricultural land into six categories: rainfed cropland, rainfed cropland (herbaceous cover), rainfed cropland (forest cover), irrigated cropland, cropland (>50%)/natural vegetation (<50%), and cropland (<50%)/natural vegetation (>50%). 50%)/natural vegetation (<50%) and arable land (<50%)/natural vegetation (>50%). The data year is 2020 and the spatial resolution of the data is 300m × 300m, i.e., about 0.003° × 0.003°. The dataset can provide basic data support for future land resource development and utilization and agricultural development of the five Central Asian countries.
ZHANG Junjun , JIANG Xiaohui
Facing the sustainable agricultural development of the five Central Asian countries, with the goal of land resources, in order to explore the land resources evaluation in Central Asia under the climate change in the past 20 years and the land resources situation in Central Asia under the climate change in the next 30 years, we collected the land resources evaluation elements in Central Asia, including: soil elements (soil salinization degree, soil texture, soil organic matter content, soil pH value, soil total nitrogen), terrain elements (elevation, slope) Climatic elements (rainfall, temperature, solar radiation). Topographic elements and soil elements are based on 2020. Climate elements include 2000, 2010, 2020, and the average precipitation and temperature in 2030 and 2050 under the future SSP5-8.5 scenarios estimated by the ESM1 climate model in CMIP6, with a spatial resolution of 0.01 ° × 0.01°。 The data set can provide basic data support for the future development and utilization of land resources and agricultural development of the five Central Asian countries.
ZHANG Junjun , JIANG Xiaohui
Soil moisture (SM) plays a vital role in regulating the water and energy exchange between land surfaces and the atmosphere and is declared an essential climate variable by the Global Climate Observing System (GCOS). Vegetation optical depth (VOD) is a crucial parameter describing vegetation attenuation properties in microwave radiative transfer equation, and it has been proven to be a promising ecological indicator for studying plant hydraulics, carbon stocks, and vegetation phenology. A long-term SM and polarization-, frequency-dependent VODs (C/X/Ku) product was derived from the inter-calibrated AMSR-E/2 multi-frequency brightness temperature, using the multi-channel collaborative algorithm (MCCA). The MCCA comprehensively considers the physical relationship between multiple microwave channels and could simultaneously retrieve frequency- and polarization-dependent VODs and SM. The new MCCA AMSR-E/2 SM dataset was validated over 25 dense soil moisture networks from the International Soil Moisture Network (ISMN) and United States Department of Agriculture (USDA) watersheds. The results showed that MCCA performs best in terms of ubRMSE among the current publicly available SM datasets related to AMSR-E/2. In addition, polarization-, frequency-dependent VODs from MCCA may provide new insights for better understanding the water fluxes in plant physiology.
HU Lu, ZHAO Tianjie, JU Weimin , PENG Zhiqing , YAO Panpan, SHI Jiancheng
This dataset includes the concentration and distribution data of poly- and perfluoroalkyl substances (PFAS) in the Yarlung Tsangpo River and three major rivers in Hengduan Mountain region. The samples were collected in 2020 and 2021 from 83 locations in four major rivers, including the Yarlung Tsangpo, Nu, Lancang and Jinsha Rivers. The water samples were prepared by solid phase extraction, purification, concentration steps, and then determined by HPLC (ThermoFisher Scientific, USA) coupled to a TSQ Quantiva triple quadrupole mass spectrometer. The target compounds included 10 perfluorinated carboxylic acids (PFCAs) and 3 perfluorinated sulfonic acids (PFSAs). Specifically, perfluorobutanoic acid (PFBA), perfluoropentanoic acid (PFPeA), perfluorohexanoic acid (PFHxA), perfluoroheptanoic acid (PFHpA), perfluorooctanoic acid (PFOA),perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluoroundecanoic acid (PFUnDA), perfluorododecanoic acid (PFDoA) and perfluorotridecanoic acid (PFTrA), perfluorobutanesulfonic acid (PFBS), perfluorohexanesulfonic acid (PFHxS), and perfluorooctanesulfonic acid (PFOS). In the process of sample pretreatment, isotope labeled recovery standards were added, and the sample recovery was calculated to be between 53% and 96%. Conventional water quality test parameters include temperature, dissolved oxygen, pH, conductivity, salinity, and dissolved organic carbon. The accuracy of the parameters were 0.1℃, 0.01mg/L, 0.01, 0.1μS/cm, 0.01ppt and 0.01mg/L, respectively. Among them, the dissolved organic carbon was measured by TOC analyzer, and the other water quality parameters were measured by YSI ProPlus portable multi-parameter water quality instrument. This dataset can provide a scientific basis for mapping the spatial distribution of organic pollution over the Tibetan Plateau and assessing the water quality safety of water towers in Asia.
REN Jiao , WANG Xiaoping
The basic data of hydrometeorology, land use and DEM were collected through the National Meteorological Information Center, the Hydrological Yearbook, the China Statistical Yearbook and the Institute of Geographic Sciences and Resources of the Chinese Academy of Sciences. The distributed time-varying gain hydrological model with independent intellectual property rights is used for modeling, and the Qinghai Tibet Plateau is divided into 10937 sub basins with a threshold of 100 square kilometers. In Heihe River, Yarlung Zangbo River, the source of Yangtze River, the source of Yellow River, Yalong River, Minjiang River and Lancang River basins, 14 flow stations were selected to observe the daily flow data to develop and verify the model. The daily scale Naxi efficiency coefficient is above 0.7, and the correlation coefficient is above 0.8. The precipitation and temperature data output from 13 models and 4 scenarios provided by CMIP6 are used to post process the future precipitation and temperature data. The post processed precipitation and temperature driven hydrological model simulates the water cycle process from 2046 to 2065, and gives the possible future spatial and temporal distribution of 0.1 degree daily scale runoff across the Qinghai Tibet Plateau.
YE Aizhong
Based on the CMIP6 model data (see Table 1 for the model list), the distribution and thickness of frozen soil in the Qinghai Tibet Plateau and the circum Arctic region, as well as the terrestrial ecosystem carbon flux (total primary productivity GPP and ecosystem carbon source sink NEP) data in the frozen soil area under different climate change scenarios (including SSP126, SSP245 and SSP585) in the historical period (1990-2014) and the future (2046-2065) are estimated, with a spatial resolution of 1 ° × 1°。 Among them, the distribution of frozen soil is estimated under the future climate warming scenario by using the spatial constraint method (Chadburn et al., 2017), based on the probability of frozen soil occurrence under different temperature gradients at the current stage, and combined with the future temperature change simulated by the Earth system model. For the change of active layer thickness, the sensitivity of active layer thickness to temperature change estimated by remote sensing at this stage is used to constrain the change of active layer thickness simulated by the Earth System Model, so as to correct the error of the model in simulating the thickness of frozen soil active layer. The future permafrost carbon flux is the multi model ensemble average of the Earth system model simulation results. The simulation results show that the permafrost in the Qinghai Tibet Plateau will be significantly degraded under the future climate change scenario. With the future temperature rise, the continuous permafrost regions will be shown as carbon sources, but the temperature rise will promote the growth of vegetation, and the carbon sink capacity in the discontinuous permafrost regions will be enhanced. Similar to the Qinghai Tibet Plateau, the permafrost around the Arctic will also be generally degraded in the future, and the future climate warming will promote the growth of vegetation in the Arctic, thus enhancing regional carbon sinks.
WANG Tao, LIU Dan , WEI Jianjun
Wind speed data is widely used in many sciences, management, and policy fields to assess renewable energy potential, address wind hazards, investigate biological phenomena, and explore climate change/variability, among other applications. The challenge is obtaining complete and accurate wind datasets, as observations are limited in distribution. Global-scale weather stations suffer from spatial and temporal discontinuities that limit their utility. While reanalysis products and climate model simulations achieve data continuity, they often fail to reproduce significant wind speed trends because few of them assimilate in-situ wind observations on land. Data interpolation helps fill gaps, but the high variability of wind speed data, combined with a low distribution of observations worldwide, prevents standard statistical interpolation methods such as kriging or principal component analysis from being accurate for areas with sparse data. As a result, wind speed data has been the bottleneck in related studies. Here, based on the partial convolutional neural network, we reconstructed the global near-surface wind speed data during 1973-2021 by assimilating simulation outputs from 34 climate models and the HadISD dataset, which the Met Office Hadley Center creates. Our dataset has a spatial resolution of 1.25°×2.5° and containers observed wind speed trends.
ZHOU Lihong , ZENG Zhenzhong , JIANG Xin
Three different data sources are used, including maps of the early Republic of China in 1920s, digital topographic maps in 1960 and Landsat MSS/TM/ETM+/OLI images from 1970 to 2020. In 1920s, the maps were scanned, geometrically corrected and georeferenced. In the 1960s, 1:250000 topographic maps were used. All maps are georeferenced by Albers Equivalent Conical Projection, and the root mean square (RMS) error is less than 1.5 pixels. For the early maps, visual interpretation and manual digitization were chosen to vectorize the lake boundaries. Since 1990, the semi-automatic water body classification method has been used to distinguish water body and non water body information from Landsat images, and then the lake boundary has been extracted, and visual inspection and manual editing have been carried out by comparing with the original Landsat images.
ZHANG Guoqing, RAN Youhua
Based on the 33rd Antarctic Scientific Expedition in China, the data set of temporal and spatial distribution of metal element concentrations in snow and ice obtained on the section from Zhongshan Station to Dome A in East Antarctica mainly includes: 1. A shallow ice core obtained 202 km away from Zhongshan Station. The ice core covers the period from 1990 to 2017 with a resolution of years, including metal element iron, hydrogen and oxygen isotopes and other data. 2. Collect a sample every 10km along the Zhongshan Station Dome A section in East Antarctica. The metal elements include rare earth elements, barium and other elements. The data can be used to study the pollution and contribution of natural sources and human activities to Antarctic snow and ice.
Du Zhiheng
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
Based on the data of GF-1 and GF-2 in China, the freeze-thaw disaster distribution data of Qinghai Tibet project corridor is produced by using the deep learning classification method and manual visual interpretation and correction. The geographical range of the data is 40km along the Xidatan Anduo section of Qinghai Tibet highway. The data include the distribution data of thermokast lakes and the distribution data of thermal melting landslides. The dataset can provide data basis for the research of freeze-thaw disaster and engineering disaster prevention and reduction in Qinghai Tibet engineering corridor. The spatial distribution of freezing and thawing disasters within 40km along the Xidatan-Anduo section of Qinghai Tibet highway is self-made based on the domestic GF-2 image data. Firstly, the deep learning method is used to extract the mud flow terrace block from GF-2 data; Then, ArcGIS is used for manual editing.
NIU Fujun, LUO Jing
This data is generated based on meteorological observation data, hydrological station data, combined with various assimilation data and remote sensing data, through the preparation of the Qinghai Tibet Plateau multi-level hydrological model system WEB-DHM (distributed hydrological model based on water and energy balance) coupling snow, glacier and frozen soil physical processes. The time resolution is monthly, the spatial resolution is 5km, and the original data format is ASCII text format, Data types include grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation in the month). If the asc cannot be opened normally in arcmap, please top the first 5 lines of the asc file.
WANG Lei, CHAI Chenhao
There are 396 temperature-sensitive proxy data for the past millennium over the Northern Hemisphere, including 370 tree rings, 15 ice cores, 9 lake sediments and 2 historical documents; This data is derived from the global temperature proxy dataset released by PAGES2k Consortum in 2017; During the process of temperature assimilation in the past millennium (1000-2000 AD) in the Northern Hemisphere, the data were further screened, and only the data with annual resolution were retained; The proxy data contained in the dataset have passed strict quality inspection and temperature signal verification; The data set can be used to reconstruct the temperature of the Northern Hemisphere at the hemispherical and regional scales for the past millennium.
FANG Miao
This data is a 5km monthly hydrological data set, including grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation), simulated and output through the WEB-DHM distributed hydrological model of the Indus River basin, with temperature, precipitation, barometric pressure, etc. as input data.
WANG Lei, LIU Hu
The ground-based observation dataset of aerosol optical properties over the Tibetan Plateau was obtained by continuous observation with a Cimel 318 sunphotometer, involving two stations: Qomolangma Station and Nam Co Station. These products have taken the process of cloud detection. The data cover the period from January 1, 2021 to December 31, 2021, and the time resolution is daily. The sunphotometer has eight observation channels from visible light to near infrared, and the central wavelengths are 340, 380, 440, 500, 670, 870, 940 and 1120 nm, respectively. The field of view angle of the instrument is 1.2°, and the sun tracking accuracy is 0.1°. Six bands of aerosol optical thickness can be obtained from direct solar radiation, and the accuracy is estimated to be 0.01-0.02. Finally, AERONET unified inversion algorithm was used to obtain the aerosol optical thickness, Ångström index, aerosol particle size distribution, single scattering albedo, phase function, complex refraction index and asymmetry factor.
CONG Zhiyuan
210Bi (t1/2=5.01 d) is theoretically a radionuclide for tracing the particle cycle over a timescale of hours to days. However, it has been rarely investigated in marine environments due to its very short half-life and low activity. Here, 210Bi and 210Pb were examined in the water column on the shelf/slope of the northern South China Sea (SCS), as well as their atmospheric deposition. In rainwater, the 210Bi/210Pb ratio averaged 0.54±0.28, indicating the influence of atmospheric deposition on the disequilibrium between 210Bi and 210Pb in surface seawater. On the shelf, 210Bi/210Pb averaged 0.73±0.10 in the euphotic zone and 1.25±0.10 below, supporting a quick removal of 210Bi from the euphotic zone and regeneration in the twilight zone. On the slope, deficits in 210Bi (210Bi/210Pb of 0.81±0.07) were also observed in the productive low euphotic zone. The concurrence of 210Bi deficits and higher particulate organic carbon (POC) concentrations implied that POC largely dominates the deficit and excess of 210Bi. Based on a simple model, the removal fluxes of 210Bi at the euphotic base were 728±73 dpm m-2 d-1 and 216±89 dpm m-2 d-1 on the shelf and slope. The residence time of particulate 210Bi was 14±2 d. The 210Bi-derived export flux of POC was 1.7±0.7 mmol-C m-2 d-1 out of the euphotic zone over the slope. These results lay the foundation for 210Bi/210Pb to quantify the sinking and remineralization of particulate organic matter in coastal seas.
YANG Weifeng
Both a decrease of sea ice and an increase of surface meltwater, which may induce ice-flow speedup and frontal collapse, have a significant impact on the stability of the floating ice shelf in Greenland. However, detailed dynamic precursors and drivers prior to a fast-calving process remain unclear due to sparse remote sensing observations. Here, we present a comprehensive investigation on hydrological and kinematic precursors before the calving event on 26 July 2017 of Petermann Glacier in northern Greenland, by jointly using remote sensing observations at high-temporal resolution and an ice-flow model. Time series of ice-flow velocity fields during July 2017 were retrieved with Sentinel-2 observations with a sub-weekly sampling interval. The ice-flow speed quickly reached 30 m/d on 26 July (the day before the calving), which is roughly 10 times quicker than the mean glacier velocity.
JIANG Liming
Glaciers are sensitive to climate change. With global warming, the melting of glaciers continues to accelerate all over the world. Surging glaciers are glaciers with intermittent and periodic acceleration, which is a sensitive indicator of climate change. Based on Landsat and Sentinel satellite images from 1980s to 2020, the study area images were obtained by filtering, stitching, and cropping. Among them, the L1GS level images collected by Landsat TM sensor were geo-registered using a second-order polynomial, and the error of the geo- registered images was less than one pixel. After image template matching with an orientation correlation algorithm, this data set provides the surface ice flow velocity of a typical surging glacier in the Greenland ice sheet, Sortebræ Glacier in different period from 1980s to 2020. It is expected to contribute to the research on the surging process of Sortebræ Glacier and the discussion on the mechanism of glacier surging in the context of global warming.
QIAO Gang , SUN Zixiang , YUAN Xiaohan
Water is one of the most direct mediums through which people perceive the effects of climate change. The flow regimes that people rely on are influenced by large-scale climate change, and identifying changes to these regimes and determining their causes requires reliable, spatiotemporally continuous runoff records. China is climate vulnerable due to its remarkable topographic gradients, monsoon climate, and rapid economic development. Climate change has increased the urgency of understanding, regulating, and forecasting China’s freshwater flows. Yet, available global and regional runoff data in China are produced from sparse, poor-quality gauged station data that have been acquired over different time scales. Our research presents a new long-term, high-quality natural runoff dataset, named the China Natural Runoff Dataset version 1.0 (CNRD v1.0) for driving hydrological and climate studies over China. It will also contribute to the global runoff database. CNRD v1.0 provides daily, monthly, and annual 0.25-degree natural runoff estimates for the period of 1 January 1961 to 31 December 2018 over China. CNRD v1.0 is generated using the Variable Infiltration Capacity macroscale hydrological model, which was used to fill in gaps or construct time series of comparable lengths. To control the model performance and thus our dataset quality, the model’s sensitive parameters are automatically calibrated using an adaptive surrogate modeling‐based optimization algorithm based on monthly natural or near-natural streamflow data from 200 hydrological gauge stations—more than in previous studies—with low fractions of missing data. Another important quality control adopted for this dataset was the use of a multiscale parameter regionalization technique to estimate model parameters for ungauged basins. Overall, the results show well-calibrated parameters for most gauged catchments, and the skill scores, the Nash–Sutcliffe model efficiency coefficient (NSE) present high values for all catchments, with an average of 0.83 and 0.80 for calibration and validation modes, respectively. The multiscale parameter regionalization technique offered the best regionalization solution (median NSE = 0.76 for the calibration period and 0.72 for the validation period. The results overall show well-calibrated and regionalized parameters for the hydrological model thus for the long-term runoff reconstruction. By the cell-to-cell comparisons between the CNRD v1.0 with the two global runoff datasets, ISIMIP and GRUN, we found that our datasets show more continuous transitions in runoff dis¬tribution compared to ISIMIP and GRUN across China, and perform well in representing the geographic distribution of China’s water resources across complex terrain and climate regions.
MIAO Chiyuan, GOU Jiaojiao
Data content: money supply (2012-2021) and assets and liabilities of financial institutions (2007-2020) Data source and processing method: The original data of the third pole (China) banks and currencies from 2015 to 2021 were obtained from the official website of the World Bank and Sina.com, and the data set of the third pole (China) banks and currencies from 2012 to 2021 was obtained through data sorting, screening and cleaning. The data started from 2012 to 2021 in Microsoft Excel (xls) format. Data quality description: excellent Data application achievements and prospects: provide effective reference as socio-economic data
FU Wenxue
Data content: price index_ Consumer Price Index (CPI) (2009-2022) Data source and processing method: The original data of the third pole (China) price index economy from 2015 to 2022 were obtained from the official website of the World Bank and Sina.com, and the economic data set of the third pole (China) price index from 2009 to 2022 was obtained through data collation, screening and cleaning. The data started from 2009 to 2022 in Microsoft Excel (xls) format. Data quality description: excellent Data application achievements and prospects: provide effective reference as socio-economic data
FU Wenxue
Data content: annual statistics of gross domestic product (GDP) (1991-2021), domestic assets and liabilities data (2011-2020) and domestic input and output data (2012-2018) Data source and processing method: The original macroeconomic data of the third pole (China) from 2015 to 2021 were obtained from the official website of the World Bank and Sina.com, and the macroeconomic data set of the third pole (China) from 1991 to 2021 was obtained through data sorting, screening and cleaning. The data was stored in Microsoft Excel (xls) format. Data quality description: excellent Data application achievements and prospects: provide effective reference as socio-economic data
FU Wenxue
Data content: foreign economy and trade_ Total import and export of goods (1991-2021) Data source and processing method: The original data of foreign trade and investment of the third pole (China region) from 2015 to 2021 were obtained from the official website of the World Bank and Sina.com, and the data set of foreign trade and investment of the third pole (China region) from 1991 to 2021 was obtained through data sorting, screening and cleaning. The data started from 1991 to 2021 in Microsoft Excel (xls) format. Data quality description: excellent Data application achievements and prospects: provide effective reference as socio-economic data
FU Wenxue
This phenological data is based on the MOD13A2 data of the Qinghai Tibet Plateau from 2000 to 2015 (with a temporal resolution of 16 days and a spatial resolution of 1km). The NDVI curve is fitted using the segmented Gaussian function in the TIMESAT software. The spring phenology, autumn phenology and the length of the growth season are extracted using the dynamic threshold method. The thresholds of spring phenology and autumn phenology are set to 0.2 and 0.7 respectively. The phenological data were masked. Among them, the mask rules are: 1) The maximum value of NDVI must be met between June and September; 2) The average value of NDVI from June to September shall not be less than 0.2; 3) The average NDVI in winter shall not exceed 0.3.
ZU Jiaxing , ZHANG Yangjian
This data set is the global vegetation productivity data, including total primary productivity (GPP), net primary productivity (NPP) and net ecosystem productivity (NEP). It is simulated by BCC-ESM1 model in Phase 6 of the Coupling Model Comparison Plan (CMIP6) under the historical scenario. The data time range is 1850-2014, the time resolution is month, and the spatial resolution is about 2.8125 °. Analog Data Details Visible Link https://www.wdc-climate.de/ui/cmip6?input=CMIP6.CMIP.BCC.BCC -ESM1。
ZHENG Zhoutao
According to the characteristics of terrain data related to different glacier regions, the elevation data of glacier regions are extracted using the established glacier elevation extraction method. The technical route mainly includes:, Using multi-source elevation difference correction method, DEMs registration and elevation correlation deviation correction are realized through Matlab programming, and finally the glacier elevation change from 1970 to 2000 is calculated; (2) Extracting glacier elevation change based on ICEsat data: First, convert GLA14 binary format data into ASCII text data using IDL Readers tool provided by NSIDC, then conduct saturation correction and post-processing of slope and cloud error elimination through Matlab programming, and use multi-source elevation difference correction method to achieve ICEsat and SRTM data registration and elevation related deviation correction, Finally, the annual change trend regression fitting method is used to obtain the elevation change of glaciers from 2003 to 2009; (3) According to two different types of glacier terrain data, the glacier elevation change is extracted.
ZHOU Jianmin
According to the characteristics of terrain data related to different glacier regions, the elevation data of glacier regions are extracted using the established glacier elevation extraction method. The technical route mainly includes:, Using multi-source elevation difference correction method, DEMs registration and elevation correlation deviation correction are realized through Matlab programming, and finally the glacier elevation change from 1970 to 2000 is calculated; (2) Extracting glacier elevation change based on ICEsat data: First, convert GLA14 binary format data into ASCII text data using IDL Readers tool provided by NSIDC, then conduct saturation correction and post-processing of slope and cloud error elimination through Matlab programming, and use multi-source elevation difference correction method to achieve ICEsat and SRTM data registration and elevation related deviation correction, Finally, the annual change trend regression fitting method is used to obtain the elevation change of glaciers from 2003 to 2009; (3) According to two different types of glacier terrain data, the glacier elevation change is extracted.
ZHOU Jianmin
The feedback of the biosphere to the atmosphere is one of the core contents of global change research. When the atmospheric CO2 concentration rises, the behavior of the terrestrial ecosystem is the main uncertainty factor to predict this feedback effect. Elevated CO2 concentration (eCO2) can directly stimulate plant growth and ecosystem C absorption by increasing carboxylation and inhibiting photorespiration rate. Through the impact of CO2 fertilization effect (CFE) on photosynthesis and carbon sequestration, the terrestrial ecosystem can buffer the surge of atmospheric CO2 concentration, thereby slowing down climate change. In order to study the impact of CO2 enrichment on vegetation productivity, CO2 enrichment experiments were conducted at Naqu Grassland Station (31 ° 38 ′ 31 ″ N, 92 ° 00 ′ 54 ″ E, 4600m above sea level) in the north of the Qinghai Tibet Plateau. The test is designed in zones, with CO2 as the main treatment factor and N as the secondary treatment factor; A total of four experimental treatments span two CO2 concentration levels [ambient CO2 (aCO2), increased CO2 (eCO2):+100ppm]. Considering the low vegetation height and windy weather in the study area, octagonal open top chambers (OTCs) are used to control the carbon dioxide concentration, rather than the free FACE system. The design height of OTC is 2.5 meters, the length of each side is 1.5 meters, and each OTC occupies 7.7 square meters.
ZHANG Yangjian
This data set is the daily vorticity related flux observation data of Naqu flux station (31.64 ° N 92.01 ° E, 4598 m a.s.l.), including ecosystem net ecosystem productivity (NEP), total primary productivity (GPP) and ecosystem respiration (ER) data. The main steps of data pre-processing include wild point removal (± 3 σ）、 Coordinate axis rotation (3D wind rotation), Webb Pearman Leuning correction, outlier elimination, carbon flux interpolation and decomposition, etc. Missing data are interpolated through the nonlinear empirical formula between CO2 flux value (Fc) and environmental factors.
ZHANG Yangjian
Vegetation survey data is essential for the study of ecosystem structure and function. The Qinghai Tibet Plateau contains a vast grassland ecosystem, mainly including alpine meadow, alpine grassland, and alpine desertification grassland. Due to the unique geographical location and high altitude anoxic environmental conditions, the community survey data in the northern Tibetan Plateau is relatively scarce. This data set includes the aboveground biomass and coverage data of 47 sampling points on the northern Tibet transect in 2019, and the sampling time is from July to August. The sample size is 50cm × 50cm, dry weight of the plant is weighed after drying. This data set can be used for spatial analysis of productivity and calibration of models.
ZHANG Yangjian, ZHU Juntao
This dataset is the daily vorticity related flux observation data of Naqu flux station (31.64 ° N 92.01 ° E, 4598 m a.s.l.), including net ecosystem productivity (NEP), total primary productivity (GPP), ecosystem respiration (ER), evapotranspiration, latent heat, sensible heat, air temperature, relative humidity, wind speed, soil temperature, soil moisture and other data. The main steps of data pre-processing include wild point removal (± 3 σ）、 Coordinate axis rotation (3D wind rotation), Webb Pearman Leuning correction, outlier elimination, carbon flux interpolation and decomposition, etc. Missing data are interpolated through the nonlinear empirical formula between CO2 flux value (Fc) and environmental factors.
ZHANG Yangjian
This dataset is global respiration data, including autotrophic respiration (ra) and heterotrophic respiration (rh). It is simulated by TaiESM1 model in Phase 6 of the Coupling Model Comparison Plan (CMIP6) under historical scenarios. The data time range is 1850-2014, the time resolution is month, and the spatial resolution is about 0.9 ° x1.25 °. Analog Data Details Visible Link https://www.wdc-climate.de/ui/cmip6?input=CMIP6.CMIP.AS -RCEC.TaiESM1.historical。
Program for Climate Model Diagnosis and Intercomparison (PCMDI)
CMIP6 is the sixth climate model comparison plan organized by the World Climate Research Program (WCRP). Original data from https://www.wcrp-climate.org/wgcm-cmip/wgcm-cmip6 。 This dataset contains four SSP scenarios of Scenario MIP in CMIP6. (1) SSP126: Upgrade of RCP2.6 scenario based on SSP1 (low forcing scenario) (radiation forcing will reach 2.6W/m2 in 2100). (2) SSP245: Upgrade of RCP4.5 scenario based on SSP2 (moderate forcing scenario) (radiation forcing will reach 4.5 W/m2 in 2100). (3) SSP370: New RCP7.0 emission path based on SSP3 (medium forcing scenario) (radiation forcing will reach 7.0 W/m2 in 2100). (4) SSP585: Upgrade the RCP8.5 scenario based on SSP5 (high forcing scenario) (SSP585 is the only SSP scenario that can make the radiation forcing reach 8.5 W/m2 in 2100). Using GRU data to correct the post-processing deviation of the original CMIP data, the post-processing data set of monthly precipitation (pr) and temperature (tas) estimates from 2046-2065 was obtained, with a reference period of 1985-2014.
YE Aizhong
The data set of ecological adjustment value of Arctic permafrost change from 1982 to 2015, with the time resolution of 1982, 2015 and the change rate of two phases, covers the entire Arctic tundra area, with the spatial resolution of 8km. Based on multi-source remote sensing, simulation, statistics and measured data, and combined with GIS and ecological methods, it quantifies the adjustment service value of Arctic permafrost to the ecosystem, The unit price refers to the correlation (0.35) between the active layer thickness and NDVI changes after excluding precipitation and snow water equivalent, and the grassland ecosystem service value (the unit price of tundra ecosystem service is based on 1/3 of the grassland ecosystem service value).
WANG Shijin
The data include three files on the spatial variation of surface elevation of endorheic glaciers in the Tibetan Plateau from 1975-2000 (100m), the mean elevation change values of glaciers in each sub-basin of the endorheic region from 1975-2020, and the basin boundaries and zoning. The glacier surface elevation changes from 1975-2000 were obtained based on 32 pairs of KH-9 data and NASADEM, where the results for the Muzetag and Puruogangri areas were obtained from Zhou et al. (2018) and Bhattacharya et al. (2021) respectively The average elevation change results for each 5-year period from 1995-2020 for the respective basins were obtained based on data published by Huggonet et al. (2021), and here it is assumed that the glacier thickness changes from 1995-2000 are similar to those from 2000-2005. Due to the limitation of KH-9 data quality and the glacier characteristics in the instream area, there are many null areas, and it is recommended to combine the zoning and calculate the change results for each elevation zone first, and then project them to each sub-basin.
CHEN Wenfeng, ZHANG Guoqing
This data set is a global surface evapotranspiration product based on the PEW model. The PEW model is a water energy based surface energy balance model based on the assumption of equal proportion. Its principle is to couple the water heat balance framework based on the assumption of equal proportion on the Priestley Taylor (PT) evapotranspiration algorithm. PEW model can consider the influence of water balance constraint and energy budget process at the same time, which makes the simulation accuracy of PEW model improved compared with previous models to a certain extent. The input data of PEW include the meteorological and soil moisture changes of ERA5 land dataset. The time span of this dataset is from 1982 to 2018. The time resolution is month by month and the spatial resolution is 0.1 °. This data set can provide a basis for studying the long-term water cycle and climate change.
FU Jianyu , WANG Weiguang
As a powerful heat source, the Tibetan Plateau (TP) affects the onset, advance and retreat of the Asian monsoon, and the interaction between the westerly belt and the monsoon belt. In order to study the variation of TP thermal effect and its influence on the surrounding climate, the basic data related to TP heat source are needed. This data set is composed of monthly basic heat source data of the TP and its surrounding areas calculated from reanalysis data, and its horizontal range covers 40°E-180° and 20°S-80°N. The spatial resolution is 2.5 ° x2.5 °, and the datasets mainly included ERA5 and NCEP/NCAR reanalysis data.
LI Qingquan
The active layer thickness in the Wudaoliang permafrost region of the Qinghai Tibet Plateau is retrieved based on the seasonal deformation obtained by SBAS-InSAR technology and ERA5-Land spatio-temporal multi-layer soil moisture data corrected by variational mode decomposition method. The time range of the is 2017-2020, and the spatial resolution is 1km. This data can be used to study the change of the active layer thickness in the permafrost region of the Qinghai Tibet Plateau and analyze its interaction with climate change, water cycle and energy cycle. It is significance to understand the permafrost degradation, environment evolution and the impact of permafrost degradation on ecology and climate.
LU Ping , HAO Tong , LI Rongxing
The triple pole aerosol type data product is an aerosol type result obtained through a series of data pre-processing, quality control, statistical analysis and comparative analysis processes by comprehensively using MEERA 2 assimilation data and active satellite CALIPSO products. The key of the aerosol type fusion algorithm is to judge the aerosol type of CALIPSO. During the data fusion of aerosol type, the final aerosol type data (12 types in total) and quality control results in the three polar regions are obtained according to the types and quality control of CALIPSO aerosol types and referring to MERRA 2 aerosol types. The data product fully considers the vertical and spatial distribution of aerosols, and has a high spatial resolution (0.625 ° × 0.5 °) and time resolution (month).
ZHAO Chuanfeng
Pine Island Glacier, Swett Glacier, etc. are distributed in the basins of the Antarctic Ice Sheet 21 and 22, which is one of the areas with the most severe melting in the Southwest Antarctica. This dataset first uses Cryosat-2 data (August 2010 to October 2018) to establish a plane equation in each regular grid, taking into account terrain items, seasonal fluctuations, backscattering coefficients, wave front width, lifting rails and other factors, and calculates the elevation change of ice cover surface in the grid through least square regression. In addition, we used ICESat-2 data (October 2018 to December 2020) to calculate the surface elevation change during the two periods by obtaining the elevation difference at the intersection of satellite lifting orbits in each regular grid. The spatial resolution of surface elevation change data in two periods is 5km × 5km, the file format is GeoTIFF, the projection coordinate is polar stereo projection (EPSG 3031), and it is named by the name of the satellite altimetry data used. The data can be opened using ArcMap, QGIS and other software. The results show that the average elevation change rate of the region from 2010 to 2018 is -0.34 ± 0.08m/yr, which belongs to the area with severe melting. The annual average elevation change rate from October 2018 to November 2020 is -0.38 ± 0.06m/yr, which is in an intensified state compared with CryoSat-2 calculation results.
YANG Bojin , HUANG Huabing , LIANG Shuang , LI Xinwu
Data content: Industrial added value of national economy (monthly) (2010-2021) Data source and processing method: obtain the original data of the third pole (China) industrial economy in 2010-2021 from the official website of the World Bank and Sina.com, and obtain the industrial economy data set in 2010-2021 (China) through data sorting, screening and cleaning. The data starts from 2010 to 2021 in Microsoft Excel (xls) format. Data quality description: excellent Data application achievements and prospects: provide effective reference as social, industrial and economic data
FU Wenxue
The data set includes the implied water resources and land resource flows among 11 cities and counties in the Heihe River basin, including Ganzhou, Sunan, Minle, Linze, Gaotai, Shandan, Suzhou, Jinta, Jiayuguan and Ejina. Table 1 includes the transfer volume of virtual water resources and virtual land resources among multiple regions. Table 2 includes the virtual water resources export volume of each regional sub sector and the virtual water resources import volume of each regional sub sector. Table 3 includes the export volume of virtual land resources of each regional sub sector and the import volume of virtual land resources of each regional sub sector. Based on the input-output tables of 11 cities and counties in the Heihe River Basin, we investigate the consumption, loss and flow of water and land resources in each economic sector, construct a coupled water-land resource accounting statement, and calculate the virtual water resources and virtual land resources flow by sector in each region based on the input-output analysis method. The water consumption and land use data of each region and sector are obtained from official statistical yearbook data.
CHEN Bin
Freeze-thaw index is an important sensitive indicator of climate change, and is also widely used in the study of frozen soil changes. The research on the spatial distribution characteristics and time variation trend of freezing and thawing index in the global scope can provide a basis for the global frozen soil environment assessment, engineering construction and coping with climate change. This data set is based on the daily temperature observation data of more than 14000 stations covering the global land from 1973 to 2021 to calculate the air freezing index (FI) and air melting index (TI). The freezing/thawing index is the cumulative value of the daily average temperature below/above 0 ℃ during the freezing/thawing period. Considering that the index calculation should cover the whole freezing/thawing period and ensure the continuity of the calculation period, the northern hemisphere takes July 1 of that year to June 30 of the next year as a freezing period, and takes January 1 to December 30 of that year as a melting period, while the southern hemisphere has the opposite freezing/thawing period. The stations with missing survey years were not filled, which, on the one hand, avoided the uncertainty error caused by interpolation on the results, and on the other hand, retained the authenticity and accuracy of the data as much as possible. The study of global freeze-thaw index can effectively and comprehensively understand the near surface heat state, and can provide important support for exploring the changes of freeze-thaw state.
PENG Xiaoqing, CHEN Cong , MU Cuicui
Simulation results of land use and cover in the upper, middle and lower reaches of the Heihe River basin(HRB) under the Basic, Ecology and Rapid Economic Development scenarios, time frame: 2015-2030, spatial resolution: 1km. Upper HRB land use data simulation, spatial resolution is 1km; Middle HRB land use data simulation, spatial resolution is 1km; Downstream HRB land use data simulation, spatial resolution is 1km. The spatial resolution of land use data in the downstream area of the HRB is 1 km. The land use data in the Economic scenario focuses on rapid economic development and rapid expansion of land for construction, while forest and grassland protection is neglected. The data were obtained based on historical land use data using DLS model simulations.
WU Feng
The 0.1 º aerosol optical thickness dataset (also known as the "Poles AOD Collection 1.0" aerosol optical thickness (AOD) dataset) in the polar regions from 2000 to 2020 was produced by combining Merra-2 mode data and MODIS satellite sensor AOD. The data covers the period from 2000 to 2020, with a daily time resolution, covering the "tri polar" (Antarctic, Arctic and Qinghai Tibet Plateau) region, and a spatial resolution of 0.1 degree. The verification of the measured stations shows that the relative deviation of the data is within 35%, which can effectively improve the coverage and accuracy of AOD in the polar region.
GUANG Jie GUANG Jie
This data set is the data set of water balance (precipitation, evapotranspiration, runoff, liquid soil moisture) and energy balance (short wave radiation, sensible heat, latent heat and surface soil temperature) for the source of the Yellow River and the Qilian Mountains over the past 40 years. The initial data source is ERA5 Land monthly average data, which is accumulated/averaged to the annual scale through time aggregation. The time range of the data is 1981-2020, the spatial range is 88.5 ° E – 104.5 ° E, 32 ° N – 43 ° N, and the spatial resolution is 0.1 °. The data set can be further used to study the ecological hydrological processes in the source area of the Yellow River and the Qilian Mountains, and provide scientific basis for the optimal allocation of the "mountains, rivers, forests, fields, lakes and grasses" system.
ZHENG Donghai
The data set includes basic temperature, humidity and pressure wind meteorological elements, black carbon concentration, scattering coefficient, particle size spectrum data and chemical composition analysis. Automatic weather station can measure temperature, relative humidity, air pressure, wind direction, wind speed and accumulated precipitation. AE-33 black carbon meter (hereinafter referred to as AE-33) can online measure the concentration of black carbon aerosol in the 370nm, 470nm, 520nm, 590nm, 660nm, 880nm and 950nm bands of TSP (total suspended particulate matter) in the atmosphere, and the mass absorption cross sections used are 18.47, 14.54, 13.14, 11.58, 10.35, 7.77 and 7.19 m2/g respectively. The official observation period is from June 12, 2021 to August 31, 2021, with a time resolution of 1 minute. The table data has been processed subsequently and is hourly data. The Integrated Nephelometer can measure the scattering coefficient of PM2.5 in the atmosphere at 450nm, 550nm and 700nm on line. The official observation period is from June 12, 2021 to August 31, 2021, with a time resolution of 10 seconds. The table data has been processed subsequently and is hourly data. Aerodynamic Particle Size Spectrometer (hereinafter referred to as APS) can measure 0.5-20 in the atmosphere online μ The number concentration particle size distribution spectrum of particles within m (aerodynamic diameter) particle size range has 50 particle size channels. The official observation period is from June 12, 2021 to August 31, 2021, with a time resolution of 5 minutes. The table data has been processed subsequently and is hourly data. The scanning electromobility particle size spectrometer (SMPS) can measure the particle size distribution of 13.6-514 nm (Stokes diameter) in the atmosphere online; TSI 3752 Condensed Nucleus Particle Counter (CPC) is used to measure the number and concentration of particles. The official observation period is from June 29, 2021 to August 31, 2021, with a time resolution of 5 minutes. The table data has been processed subsequently and is hourly data. The domestic medium flow sampler was used to collect the 90mm diameter quartz filter membrane, water soaked quartz filter membrane and Teflon filter membrane of TSP particle size section. The samples can be used for the analysis of chemical components such as elemental carbon, organic carbon, water-soluble ions and metal elements. The sampling period is from June 23, 2021 to August 29, 2021. The sampling starts at 11:00 a.m. and takes 71 hours each time.
TIAN Pengfei, HUANG Jianping, ZHANG Lei, SHI Jinsen
The Tibetan Plateau (TP) is the largest glacier enrichment area in the middle and low latitudes except the South Arctic and Greenland. The solid water body glaciers and liquid water bodies lakes and rivers together form the Asian Water Tower. The thermal and dynamic effects of the TP and their variability are one of the main driving forces for the TP to affect the Asian monsoon and global atmospheric circulation anomalies. To study the thermal properties of the TP itself and its feedback effect, it is necessary to use the results of climate model experiments to carry out the 100-year historical examination of the TP and its surrounding areas and the future 100-year pre