The surface PM2.5 concentration data of Tibet Plateau is named by date (YYYYMMDD). Each NC file contains one day's data, which is composed of PM2.5 concentration, longitude, latitude, and time information of the area (the corresponding variables in the data are named with PM2.5, lon, lat, time). The data inversion relies on the reanalysis data MERRA-2 released by NASA and the AOD product of Multi-angle Imaging SpectroRadiometer (MISR). MERRA-2 is mainly based on NASA GMAO Earth system model version 5 (GEOS 5). The algorithm is able to assimilate all the in-situ and re- motely-sensed atmospheric data. This dataset mainly focuses on the aerosol field of MERRA-2. This is the first multi-decadal reanalysis within which meteorological and aerosol observations are jointly assimilated into a global assimilation system. MISR views Earth with cameras pointed in 9 different directions， which can help us know the amount of sunlight that is scattered in different directions under natural conditions. The main data products used in this data algorithm are MERRA-2 aerosol analysis product (M2T1NXAER) and MISR Level 3 version 4 global aerosol products (MIL3DAEN_4). Firstly, the ratio of PM2.5 to AOD in each grid was calculated by using the aerosol information provided by MERRA-2. Second, the PM2.5 concentration of the grid was calculated by multiplying the AOD of MISR by the ratio. The mean prediction error of PM2.5 concentration obtained by this method is within 20 μg/m3. The corresponding PM2.5 products can be used for the assessment of particulate pollution in the Tibet Plateau.
The data of aerosol optical depth were daily collected at Qomolangma Station for Atmospheric and Environmental Observation and Research with An automatic sun/sky scanning radiometer (Cimel 318), over the period from Jan. to Dec. The data were measured at 2020. 340, 380, 440, 500, 675, 870 and 1020 nm channel with uncertainty of 0.01 - 0.02.
In order to describe the distribution pattern of genetic diversity of the main domesticated animals in the Qinghai Tibet Plateau and its surrounding areas, clarify their genetic background, and establish the corresponding genetic resource database, the undergraduate team collected local animals in Dali, Yunnan, Shangri La, Mangkang, Luqu, Chayu, Changdu, Hetian and Yili regions from 2018 to 2019 The blood or tissue samples of the animals were collected, and the corresponding individual photos were taken at the same time. Each folder contains a set of photos of local domestic animals and a sample information sheet. Photos are stored in JPG format. The information table records the basic sample information such as species, species, detailed sampling place, sample type, collection time, collector and storage method, and stores them in the form of Excel.
YIN Tingting, PENG Minsheng
(1) This is a literature-based eddy covariance carbon exchange dataset on the Tibetan Plateau, including air temperature, soil temperature, precipitation, ecosystem productivity and other parameters. (2) The data set is based on the field measured data of vorticity, and adopts the internationally recognized standard processing method of vorticity related data. The basic process includes: outlier elimination coordinate rotation WPL correction storage item calculation precipitation synchronization data elimination threshold elimination outlier elimination U * correction missing data interpolation flux decomposition and statistics. This data set also contains the model simulation data calibrated based on the vorticity correlation data set. (3) the data set has been under data quality control, and the data missing rate is 37.3%, and the missing data has been supplemented by interpolation. (4) The data set has scientific value for understanding carbon sink function of alpine wetland, and can also be used for correction and verification of mechanism model.
A comprehensive understanding of the permafrost changes in the Qinghai Tibet Plateau, including the changes of annual mean ground temperature (Magt) and active layer thickness (ALT), is of great significance to the implementation of the permafrost change project caused by climate change. Based on the CMFD reanalysis data from 2000 to 2015, meteorological observation data of China Meteorological Administration, 1 km digital elevation model, geo spatial environment prediction factors, glacier and ice lake data, drilling data and so on, this paper uses statistics and machine learning (ML) method to simulate the current changes of permafrost flux and magnetic flux in Qinghai Tibet Plateau The range data of mean ground temperature (Magt) and active layer thickness (ALT) from 2000 to 2015 and 2061 to 2080 under rcp2.6, rcp4.5 and rcp8.5 concentration scenarios were obtained, with the resolution of 0.1 * 0.1 degree. The simulation results show that the combination of statistics and ML method needs less parameters and input variables to simulate the thermal state of frozen soil, which can effectively understand the response of frozen soil on the Qinghai Tibet Plateau to climate change.
Ni Jie, WU Tonghua WU Tonghua WU Tonghua
The data set is the body size data of a core BST04H from Bosten Lake over the past 2,000 years, including the body size of individual Pediastrum coenobia and the statistical data of the body size of Pediastrum in samples (average, median, maximum). The body size of Pediastrum is measured under a 400-times optical microscope. After statistical analysis of the measured data, the average, median, and maximum of the body size of Pediastrum in samples are obtained. Based on all of the measurements for each stage, we calculated Pediastrum body size probability distribution curves for the five climatic stages (Roman Warm Period, Dark Age Cold Period, Medieval Warm Period, Little Ice Age, Current Warm Period). This data set will help us to understand the relationships between Pediastrum and temperature in paleoenvironment studies.
DNA was extracted from teeth or phalanx. Firstly, we conducted 2 hours UVirradiation on the samples, and removed a layer of surface using a sterile dentistry trill, then again irradiated with 1 hour UV-light on the samples. We drilled out ~80 mg of bone powder for every sample with the sterile dentistry trill, and only do 2 samples at one time (include following procedures until performing sequencing; samples from different archaeological sites were never handled together) to avoid potential individual cross-contamination. Using the 80 mg bone powder, we performed DNA extraction following the silica suspension protocol from an early report (Rohland and Hofreiter 2007), which was modified afterwards (Allentoft, et al. 2015) for customizing recovering of more shorter DNA fragments, that finally resulting a total of 100 μl aliquots for each sample. In brief, the bone powder was digested over night with proteinase K in 0.5M EDTA plus 10% N-Laurylsarcosyl suspension, then the released DNA was absorbed in solution which includes PB buffer, 5M sodium acetate, 5M sodium chloride and SiO2 suspension, and followed by three times of purification using 80% ethyl alcohol. Finally, after airing, the DNA was eluted with 100 μl EB buffer. Next, to perform preliminary aDNA preservation situation screening, using 20μl DNA aliquots of each sample, we built the double strand library (DSL) with no Uracil- DNA-Glycosylase (UDG) treatment under a single indexing with commercial kit (cat no: E7370) from New England Biolabs (Ipswich, MA) following the manufacturer’s guidelines, as previously reported (Meyer and Kircher 2010) that includes end prep, adaptor ligation, purification, PCR amplification and size selection steps. PCRs were conducted in a final volume of 50 μl using AmpliTaq Gold 360 DNA Polymerase (AmpliTaq Gold, Life Technologies Applied Biosystems) which is able to well amplify across uracils, preserve the DNA damage pattern that induced by deamination, which indicating of authentic aDNA (Krause, et al. 2010). We performed all the sequencing (also the following captured library sequencing) on the Illumina HiSeq X Ten (PE-150) platform ( https://www.illumina.com.cn/systems/sequencing-platforms/hiseq-x.html ). The calculated appraise indexes of aDNA quality and preservation are shown in Table S1. Lastly, we rebuilt the DSLs with 3 hours UDG treatment using the remaining DNA extraction aliquots, which could largely remove uracil residues from DNA fragmental end to leave abasic sites, and cuts the DNA at the 5´ and 3´ sides of the abasic sites with enzyme endonuclease VIII (Endo VIII). For these libraries, we performed the mtDNA capture using myBaits® Mito-Target Capture Kits as previous report (Enk, et al. 2014). Briefly, we used the biotinylated RNA “baits” that are transcribed from the human genomic DNA to perform the capture in solution overnight at 65°C, then mixed in streptavidin-coated magnetic beads and sequestered the targets with a magnetic stand. The PCRs for both pre-capture and post-capture are performed using KAPA HiFi Hot start Polymerase (KAPA BIOSYSTEMS).
Hanging coffin burial is a kind of burial custom in which the coffin is placed on the cliff, cave and crevice. Hanging coffin burials are widely distributed in the Yangtze River Valley and the south of China, as well as in Southeast Asia and even the Pacific Islands. With the natural weathering and man-made destruction, there are fewer and fewer such relics. As a kind of peculiar and ancient archaeological cultural remains and funeral custom, hanging coffin culture has been widely concerned by archaeologists. Dating method: the wood samples on the hanging coffin were sent to beta analytical testing laboratory in Miami, USA for C14 determination. Methods: 4 in house NEC accelerator mass spectrometers (AMS) and 4 thermo IRMSS under strict chain of custom and quality control using ISO / IEC 17025:2005 testing accreditation pjla accreditation protocols Results: the dating results show that the earliest hanging coffin burial site is located in Wuyishan area of Fujian Province, 3600 years ago, which is equivalent to the Shang and Zhou dynasties in China. Wuyishan area in Fujian Province is considered to be the birthplace of the hanging coffin burial custom, which later spread to other areas in South China, Southeast Asia and the Pacific Islands. Located in the Jinsha River Valley of South Sichuan and Northeast Yunnan, the hanging coffin burial is the latest cultural remains of hanging coffin burial in mainland China (late Ming Dynasty), and also the West pole of the distribution of hanging coffin burial sites in China. There is a hanging coffin group in the mountainous area of Northwest Thailand, 2100-1200 years ago.
The complete mitochondrial DNA sequences of 41 human remains from 13 hanging coffin sites 2500-660 years ago in Weixin and Yanjin, Zhaotong, Yunnan, Huacun, Baise, Guangxi and bangmapa, Thailand were analyzed by using the ancient DNA analysis technique. They found that the maternal genetic diversity of the hanging coffin people in Northwest Yunnan was very high, while the genetic diversity of the hanging coffin people in northern Thailand was relatively low. This result is consistent with the view that the hanging coffin burial custom originated in southern China and spread southward to Southeast Asia. In addition, a small number of matrilineal lineages were shared among the hanging coffin people in different regions of Asia, indicating that there is a very close relationship between different hanging coffin people. Combining the results of genetic analysis with the evidences of archaeology, physical anthropology, folklore and history, they speculated that the hanging coffin burial custom originated in the Baiyue ethnic group in the southeast coastal areas of China (such as Wuyishan area) about 3600 years ago, and they are the ancestors of the Dai ethnic group with many ethnic groups. After that, the custom of hanging coffin was widely spread in South China by means of people migration and flow. However, about 2000 years ago (the earliest time of hanging coffin burial in Thailand), a very small number of inheritors of hanging coffin burial spread the custom to some aboriginal groups in Southeast Asia, such as northern Thailand, by means of cultural diffusion. This study only makes a preliminary discussion from the perspective of maternal genetic lineage. For the hanging coffin culture which has spread for more than 3000 years in South China, Southeast Asia and the vast area of the Pacific Islands, the origin and development of its culture and the history of its inheritors may be more complex. In the future, more representative samples of human remains buried in a hanging coffin will be used, from the perspective of genomic DNA and paternal Y-DNA, combined with interdisciplinary research, which will provide more systematic evidence support for a more comprehensive display of the historical and cultural features of the hanging coffin burial custom.
Grassland actual net primary production (NPPa) was calculated by CASA model. CASA model was calculated with the combination of satellite-observed NDVI and climate (e.g. temperature, precipitation and radiation) as the driving factors, and other factors, such as land-use change and human harvest from plant material, were reflected by the changes of NDVI. CASA NPP was determined by two variables, absorbed photosynthetically active radiation’ (APAR) and the light-use efficiency (LUE). Grassland potential net primary production (NPPp) was calculated by TEM model. TEM is one of process-based ecosystem model, which was driven by spatially referenced information on vegetation type, climate, elevation, soils, and water availability to calculate the monthly carbon and nitrogen fluxes and pool sizes of terrestrial ecosystems. TEM can be only applied in mature and undisturbed ecosystem without take the effects of land use into consideration due to it was used to make equilibrium predications. Grassland potential aboveground biomass (AGBp) was estimated by random forest (RF) algorithm, using 345 AGB observation data in fenced grasslands and their corresponding climate data, soil data, and topographical data.
NIU Ben, ZHANG Xianzhou
1) Data content: this data is the chromatin open group data of umbilical cord endothelial cells of Plateau Tibetan and plain Han people generated during the implementation of the project, including 5 cases of Plateau Tibetan umbilical cord endothelial cell chromatin open group data and 5 cases of plain Han umbilical cord endothelial cell chromatin open group data. The amount of chromatin open group data of each cell is > 15g sequencing depth, which can be used to study the high-risk factors The chromatin opening pattern and gene expression regulation pattern of the original Tibetan population and the plain Han population in high altitude hypoxia environment. 2) Data sources and processing methods: Based on our own data, we used the 150 BP pair end sequencing method of Illumina x-ten. 3) Data quality: > 15g data volume, q30 > 90%. 4) Data application achievements and prospects: the data are used to verify the open mode of cell chromatin and gene expression change mode of high altitude hypoxia adaptation genes under hypoxia environment.
This dataset is the daily temopral resolution land surface albedo product over Qilian Mountain Area in 2019, with a spatial resolution of 500m. The BRDF / albedo model coupled with topographic effects is used to retrieve the parameters from MODIS land surface reflectance, where the prior knowledge is introduced for quality control. MODIS surface reflectance data is downloaded from the official website, and the daily resolution BRDF is composited with a period of 5 days, and albedo is estimated. The validation results shows it meets the accuracy requirements of albedo application. Compared with similar products, it has more advantages in capturing rapidly changing surface features, and has better temporal and spatial continuity. It can effectively support the study of radiation balance and environmental change in Qilian mountain area.
WEN Jianguang, TANG Yong, YOU Dongqin
File name:YYYYMMswalbedo_basins.tif (YYYY: year, MM: month) Monthly albedo in February 1982 Data version number: v1.0 Data reading mode: it can be opened by envi, ArcGIS and other software Projection + proj = longlat + datum = WGS84 + no_ defs Data format: GeoTIFF, 1790 rows x 1120 columns The valid range of albedo: (0,1) Band Description: 1-3 band, black sky albedo of AVHRR red light, AVHRR near infrared band and short wave band; 4-6 band, white sky albedo of AVHRR red light, AVHRR near infrared band and short wave band Fill value: 0
WEN Jianguang, YOU Dongqin, TANG Yong, WU Shanlong, ZHONG Bo
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.
Data content: soil moisture data of the Aral Sea basin from 2015 to 2018. Data sources and processing methods: from the National Aeronautics and Space Administration of the United States, the daily soil moisture data are added to get the sum of eight days of soil, and then divided by the number of days to get the average value of eight days of rainfall. Data quality: the spatial resolution is 0.25 ° x 0.25 ° and the temporal resolution is 8 days. The value of each pixel is the average value of soil moisture in 8 days. Results and prospects of data application: under the background of climate change, it can be used to analyze the correlation between meteorological elements and vegetation characteristics, and can also be combined with other meteorological data to analyze the regional distribution of a certain vegetation type.
Data content: precipitation data of the Aral Sea basin from 2015 to 2018. Data sources and processing methods: from the new generation of global precipitation measurement (GPM) of NASA, the daily rainfall can be obtained by adding the three-hour rainfall data, and then the eight day rainfall can be obtained. Data quality: the spatial resolution is 0.1 ° x 0.1 ° and the temporal resolution is 8 days. The value of each pixel is the sum of rainfall in 8 days. Data application results: under the background of climate change, it can be used to analyze the correlation between meteorological elements and vegetation characteristics.
Data content: evapotranspiration data set of the Aral Sea basin from 2015 to 2018. Data sources and processing methods: Based on IDL platform, SEBS algorithm and MODIS data of NASA were used to calculate the evapotranspiration results of the Aral Sea basin from 2015 to 2018. Data quality: spatial resolution is 1000m × 1000m, temporal resolution is 8 days. Results and prospects of data application: in the context of climate change, it can be used to analyze the correlation between meteorological elements and vegetation characteristics, and can also be combined with other vegetation data and ecological data to analyze land degradation.
Data content: data set of planting structure in the Aral Sea Basin in 2019. Data sources and processing methods: 2019 is divided into three time periods, and the sentry-2 data with the least cloud cover and the highest quality in each time period is spliced into a complete map to obtain the remote sensing image of sentry-2 in the third phase of the Aral Sea basin. The NDVI values of the three images are calculated, and then combined with the cultivated land data and field sampling data, the random forest algorithm is used to classify them, and finally the planting structure type of each plot is obtained. Data quality: spatial resolution is 10m × 10m, temporal resolution is year, kappa coefficient is 0.8. Data application results: it can be used for crop yield estimation and water resource utilization efficiency calculation.
Data content: cultivated land data of Aral Sea basin. Data sources and processing methods: the original satellite images are from Google Earth of the United States. In order to obtain cloud free images with high resolution, Google Earth integrates the data of different years by splicing, so the time span of the downloaded image data is 2016-2019. Using machine recognition method to predict the land boundary, the boundary is transformed into vector data, and then the results are superimposed with Google image, and the error information is manually checked one by one to get the cultivated land data of the Aral Sea basin. The wgs-1984 coordinate system was used for the final results. Data quality: the spatial resolution is 0.45M × 0.45M, and the accuracy is 90.32%. Data application results: in the context of climate change, it can be combined with meteorological elements and vegetation characteristics to analyze land degradation; it can be combined with vegetation characteristics and sampling points to analyze planting structure, and it can also be combined with meteorological data and statistical data to calculate water resource utilization efficiency and food yield.
Data content: albedo data of the Aral Sea basin from 2015 to 2018. Data source and processing method: the "BRDF" in mcd43a1 product was extracted from NASA medium resolution imaging spectrometer_ Albedo_ Parameters_ nn. Num_ Parameters_ 01"，“BRDF_ Albedo_ Parameters_ nn. Num_ Parameters_ 02 "and" BRDF "_ Albedo_ Parameters_ nn. Num_ Parameters_ According to the MODIS official algorithm, the daytime albedo and night albedo are calculated and multiplied by the scale factor of 0.001. Data quality: the spatial resolution is 500m × 500m, the temporal resolution is 8 days, and the value of each pixel is the average value of surface albedo in 8 days. Description of the boundary of the Aral Sea Basin: the boundary of the Aral Sea basin is from hydrobases version 1 of WWF. For details, please refer to: https://www.hydrosheds.org/page/hydrobasins Results of data application: as an important parameter, surface evapotranspiration can be retrieved.