This dataset is derived from the paper: Ding, J., Wang, T., Piao, S., Smith, P., Zhang, G., Yan, Z., Ren, S., Liu, D., Wang, S., Chen, S., Dai, F., He, J., Li, Y., Liu, Y., Mao, J., Arain, A., Tian, H., Shi, X., Yang, Y., Zeng, N., & Zhao, L. (2019). The paleoclimatic footprint in the soil carbon stock of the Tibetan permafrost region. Nature Communications, 10(1), 4195. doi:10.1038/s41467-019-12214-5. This data contains R code and a new estimate of Tibetan soil carbon pool to 3 m depth, at a 0.1° spatial resolution. Previous assessments of the Tibetan soil carbon pools have relied on a collection of predictors based only on modern climate and remote sensing-based vegetation features. Here, researchers have merged modern climate and remote sensing-based methods common in previous estimates, with paleoclimate, landform and soil geochemical properties in multiple machine learning algorithms, to make a new estimate of the permafrost soil carbon pool to 3 m depth over the Tibetan Plateau, and find that the stock (38.9-34.2 Pg C) is triple that predicted by ecosystem models (11.5 ± 4.2 Pg C), which use pre-industrial climate to initialize the soil carbon pool. This study provides evidence that illustrates, for the first time, the bias caused by the lack of paleoclimate information in ecosystem models. The data contains the following fields: Longitude (°E) Latitude (°N) SOCD (0-30cm) (kg C m-2) SOCD (0-300cm) (kg C m-2) GridArea (k㎡) 3mCstcok (10^6 kg C)
The data set contains the off-line sampling data of medium flow aerosols from Shiquanhe national climate station (32 ° 30'n, 80 ° 05'e, altitude 4278.6 m) in Ali Region. The measuring instrument is Laoying 2030 medium flow sampler. The quartz filter membrane samples of PM2.5, PM10 and TSP with a diameter of 90 mm are collected. The samples will be used for chemical components such as elemental carbon, organic carbon, water-soluble ions and metal elements analysis. The sampling period is from July 7, 2019 to August 2, 2019, starting at 09:00 every day, with a total of 81 samples for 23 hours each time. The data is stored in Excel file.
The data set contains the scattering coefficients of PM2.5 (particles less than 2.5 μ m) at 450nm, 550nm and 700nm at Shiquanhe national climate station (32 ° 30'n, 80 ° 05'e, altitude 4278.6 m). The measuring instrument is tsi-3563 integral turbidimeter, the observation period is from July 8, 2019 to August 2, 2019, and the time resolution is 10 seconds. It can be used to study the dependence of PM2.5 scattering coefficient on the wavelength of incident light, which can reflect the particle size distribution of PM2.5.
The data set contains the scattering and absorption coefficients of PM2.5 (particles with particle size less than 2.5 μ m) in the atmosphere of Shiquanhe national reference climate station (32 ° 30'n, 80 ° 05'e, altitude 4278.6 m) in Ali Region. The measurement instrument is photoacoustic extinctiomer (pax), the observation period is from July 13, 2019 to August 2, 2019, and the time resolution is 1 minute. The data set can be used to study the scattering and absorption characteristics of PM2.5 over the Tibetan Plateau.
The data set contains the mass concentration of PM2.5 (particulate matter less than 2.5 μ m) in the atmosphere of Shiquanhe national reference climate station (32 ° 30'n, 80 ° 05'e, altitude 4278.6 m). The measuring instrument is RP 1400A vibrating balance micro balance (TEOM). The observation period is from July 8, 2019 to August 2, 2019, and the time resolution is 1 minute. The data is stored in TXT format.
The data set contains the number concentration and size distribution spectrum of particles in the atmosphere of Shiquanhe national climate station (32 ° 30'n, 80 ° 05'e, elevation 4278.6 m) in Ali Region. The instrument is tsi-3321 aerodynamic particle size spectrometer (APS), with 52 particle size channels. The observation period is from July 7, 2019 to August 2, 2019, and the time resolution is 5 minutes. The size distribution spectra of aerosol volume concentration and mass concentration can be obtained by using the data, aerosol spherical hypothesis and aerosol density, and then the characteristics of aerosol particle size distribution in the northwest of Qinghai Tibet Plateau can be studied.
This dataset is collected from the paper: Chen, J.*#, Huang, Y.*#, Brachi, B.*#, Yun, Q.*#, Zhang, W., Lu, W., Li, H., Li, W., Sun, X., Wang, G., He, J., Zhou, Z., Chen, K., Ji, Y., Shi, M., Sun, W., Yang, Y.*, Zhang, R.#, Abbott, R. J.*, & Sun, H.* (2019). Genome-wide analysis of Cushion willow provides insights into alpine plant divergence in a biodiversity hotspot. Nature Communications, 10(1), 5230. doi:10.1038/s41467-019-13128-y. This data contains the genome assembly of alpine species Salix brachista on the Tibetan Plateau, it contains DNA, RNA, Protein files in Fasta format and the annotation file in gff format. Assembly Level: Draft genome in chromosome level Genome Representation: Full Genome Reference Genome: yes Assembly method: SMARTdenovo 1.0; CANU 1.3 Sequencing & coverage: PacBio 125.0; Illumina Hiseq X Ten 43.0; Oxford Nanopore Technologies 74.0 Statistics of Genome Assembly: Genome size (bp): 339,587,529 GC content: 34.15% Chromosomes sequence No.: 19 Organellas sequence No.: 2 Genome sequence No.: 30 Maximum genome sequence length (bp): 39,688,537 Minimum genome sequence length (bp): 57,080 Average genome sequence length (bp): 11,319,584 Genome sequence N50 (bp): 17,922,059 Genome sequence N90 (bp): 13,388,179 Annotation of Whole Genome Assembly: Protein：30,209 tRNA：784 rRNA：118 ncRNA：671 Please see attachments for more details of annotation. The tables in the Supplementary Information of this article can also be found in this dataset. The table list is represented in attachments. The accession no. of genome assembly is GWHAAZH00000000 (https://bigd.big.ac.cn/gwh/Assembly/663/show).
1) This data includes the basic meteorological data of Kathmandu center for research and education,CAS-TU in 2019; the parameters are: temperature ℃, relative humidity%, atmospheric pressure kPa, precipitation mm, radiation w / m2, wind speed M / s. Table 2 is a description of the weather station, including the geographical location and underlying surface. 2) Data sources and processing methods: the data are from the hourly data of Kathmandu science and education center, Chinese Academy of Sciences, daily average of temperature, air pressure, radiation and wind speed, and daily sum of rainfall. 3) Data quality description: among these parameters, the quality of air pressure data is poor, and there are many missing data due to instrument failure from June to August in 2019 4) Compared with the data of different regions in South Asia, the meteorological data can be used for postgraduates and scientists with atmospheric science, hydrology, climatology, physical geography and ecology.