The Tibet-Obs established in 2008 consists of three regional-scale soil moisture (SM) monitoring networks, i.e. the Maqu, Naqu, and Ngari (including Ali and Shiquanhe) networks. This surface SM dataset includes the original 15-min in situ measurements collected at a depth of 5 cm by multiple SM monitoring sites of all the networks, and the spatially upscaled SM records produced for the Maqu and Shiquanhe networks.
0 2022-04-15
In 2018, the Second Tibetan Plateau Scientific Expedition and Research Programme tasked a research team to conduct an "Investigation of the water vapor channel of the Yarlung Zangbo Grand Canyon" in the southeastern Tibetan Plateau. This team subsequently established a three-dimensional comprehensive observation system of land-air interaction, water vapor transport, cloud cover, and rainfall activity along different altitude from south to north along the YGC canyon. Motuo meteorological station is an integrated observation base of a variety of large observation equipment. The whole comprehensive observation network includes 2 cloud radars, 2 micro rain radars, seven sets of eddy covariance flux sites for measuring land-air interaction, 3 sets of microwave radiometers , 6 sets of GPS water vapor observatories, 2 sets of automatic weather stations and 19 sets of rainfall buckets.
0 2022-04-15
The data set contains nearly 15 years of eddy covariance data from an alpine steppe ecosystem on the central Tibetan Plateau.The data was processed following standardized quality control methods to allow for comparability between the different years of our record and with other data sets. To ensure meaningful estimates of ecosystem atmosphere exchange, careful application of the following correction procedures and analyses was necessary: (1) Due to the remote location, continuous maintenance of the eddy covariance (EC) system was not always possible, so that cleaning and calibration of the sensors was performed irregularly. Furthermore, the high proportion of bare soil and high wind speeds led to accumulation of dirt in the measurement path of the infrared gas analyzer (IRGA). The installation of the sensor in such a challenging environment resulted in a considerable drift in CO2 and H2O gas density measurements. If not accounted for, this concentration bias may distort the estimation of the carbon uptake. We applied a modified drift correction procedure following Fratini et al. (2014) which, instead of a linear interpolation between calibration dates, uses the CO2 concentration measurements from the Mt. Waliguan atmospheric observatory as reference time series. (2) We applied rigorous quality filtering of the calculated fluxes to retain only fluxes which represent actual physical processes. (3) During the long measurement period, there were several buildings constructed in the near vicinity of the EC system. We investigated the influence of these obstacles on the turbulent flow regime to identify fluxes with uncertain land cover contribution and exclude them from subsequent computations. (4) We calculated the de-facto standard correction for instrument surface heating during cold conditions (hereafter called sensor self heating correction) following Burba et al. (2008) and a revision of the original method following Frank and Massman (2020). (5)Subsequently, we applied the traditional and widely used gap filling procedure following Reichstein et al. (2005) to provide a more complete overview of the annual net ecosystem CO2 exchange.(6) We estimated the flux uncertainty by calculating the random flux error (RE) following Finkelstein and Sims (2001) and by using the standard deviation of the fluxes used for gap filling(NEE_fsd) as a measure for spatial and temporal variation.
0 2022-04-15
Data set contains tree age of trees growing at different glacier moraines in the central Himalayas. The data were obtained using tree ring samples. Cores samples were collected (almost near to the ground level to estimate the minimum age of the related moraine) using an increment borer. Samples were processed by using standard dendrochronological techniques.
0 2022-04-15
We use waveform cross-correlation to analyze the recordings of eight earthquakes (2009-2018) beneath the Indian Ocean at stations from the Chinese Digital Seismic Network. We obtain 929 high quality residual traveltime differences between the phases ScS and S (Differential traveltimes.dat). We interpret variations of δt up to 10 seconds as due to horizontal shear-velocity variations in D” beneath northern India, Nepal, and southwestern China. The shear velocity can vary by as much as 7% over distances shorter than 300 km. Our observations provide additional observational evidence that compositional heterogeneity and possibly melt contribute to the seismic structure of the lower mantle characterized by long-term subduction and mantle downwelling.
0 2022-04-15
The land cover dataset of Pan third pole major cities contains 14 cities (Urumqi, Xining, Lanzhou, Dhaka, Kathmandu, Lucknow, Delhi, Lahore, Islamabad, Kabul, Dushanbe, Tashkent, Bishkek and Almaty) in 2000 / 2010 / 2017, the spatial resolution of this dataset is 30 m. It includes vegetation, cultivated land, artificial surface, water body and others. Based on globeland30, mcd12q1 and globcover2009, the consistent regions were identified and retained. The inconsistent regions were reclassified by deep learning method, and the final classification results were obtained by fusing the above regions. The data has been verified by visual interpretation. The data are applied to the study of construction land dynamics and anthropogenic influence in Pan-Third Pole cities. Data type: grid. Projection mode: UTM projection.
0 2022-04-15
This data comes from the result of teleseismic data, mainly including the velocity and radial anisotropic structures beneath western Tibet. In the process of processing, bandwidth filtering is adopted, and the filtering range is 0.05-2 Hz. Due to the use of teleseismic data, the cross-correlation method is used in the acquisition process to "align" the waveform. The data quality is good, because the extracted data are all from the earthquakes with magnitude greater than 5.0 located in the global seismic catalog, and each event has an obvious take-off point. The data can be used by other seismologists to reconstruct and analyze the underground structures in this area.
0 2022-04-15
This is a dataset of treeline shift rates including 143 alpine treeline sites in the Northern Hemisphere. It gives the following information for each treeline site: treeline form, study site, latitude, longitude, reference, tree species, elevation, study period and annual mean elevational shift rate (m/yr).
3562 2020-07-30
Data content: Standard ring-width chronology derived from Wilson juniper shrub around the northern shore of the Nam Co Lake; May-June SZI (Standardized Moisture Anomaly Index) drought reconstruction for the Nam Co region. Time span: 1605 to 2010. Temporal resolution: Yearly. Application and prospects: Hydroclimate study on the south-central Tibetan Plateau.
0 2022-04-15
The sand drift potential (DP, in vector units (VU)) is calculated by DPi=∑U^2 [U-Ut]*fu where i represents 16 directions: N, NNE, NE, NEE, E, EES, ES, ESS, S, SSW, WS, WWS, W, WWN, NW and NNW; U is the effective sand-moving wind speed at the standard height of 10 m; Ut is the threshold wind velocity, i.e., the minimum wind velocity at the standard height to cause sand particle rolling; and fu is the fraction of time when the wind speed is higher than Ut. The 2 m s-1 bin is adopted in the effective sand-moving wind (sand-moving wind >6 m s-1 at the height of 10 m) directions, corresponding to the mean wind speeds of 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33 and 34 m s-1, to sum all the above results to obtain the final DP in the wind direction. The divisor used in calculating the frequency of effective sand-moving winds from different directions is the total hour number of Julian years (8760 hours for common years or 8784 hours for leap years). The wind speed and wind direction data from 2000 to 2008 were hourly estimates of 10 m u-component of wind and 10 m v-component wind with a horizontal resolution of 0.25°×0.25° generated with the fifth generation of ECMWF atmospheric ReAnalysis of the global climate (ERA5).
0 2022-04-15
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