Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (Large aperture scintillometer of Daman Superstation, 2021)

This dataset contains the flux measurements from the large aperture scintillometer (LAS) at Daman Superstation in the Heihe integrated observatory network from January 1 to December 31 in 2021. There were two types of LASs at Daman Superstation: BLS900 and RR-RSS460, produced by Germany. The north tower was set up with the BLS900 receiver and the RR-RSS460 transmitter, and the south tower was equipped with the BLS900 transmitter and the RR-RSS460 receiver. The site (north: 100.379° E, 38.861° N; south: 100.369° E, 38.847° N) was located in Daman irrigation district, which is near Zhangye, Gansu Province. The underlying surfaces between the two towers were corn, orchard, and greenhouse. The elevation is 1556 m. The effective height of the LASs was 24.1 m, and the path length was 1854 m. The data were sampled 1 minute at both BLS900 and RR-RSS460. The raw data acquired at 1 min intervals were processed and quality controlled. The data were subsequently averaged over 30 min periods, in which sensible heat flux was iteratively calculated by combining Cn2 with meteorological data according to the Monin-Obukhov similarity theory. The main quality control steps were as follows: (1) The data were rejected when Cn2 exceeded the saturated criterion (BLS900:Cn2>7.25E-14,RR-RSS460:Cn2>7.84 E-14). (2) The data were rejected when the demodulation signal was small (BLS900:Average X Intensity<1000;RR-RSS460:Demod>-20mv). (3) The data were rejected when collected during precipitation. (4) The data were rejected if collected at night when weak turbulence occurred (u* was less than 0.1 m/s). In the iteration process, the universal functions of Thiermann and Grassl (1992) and Andreas (1988) were selected for BLS900 and RR-RSS460, respectively. Detailed can refer to Liu et al. (2011, 2013). Due to instrument adjustment and inadequate power supply, the date of missing data for the large aperture scintillator is: 2021.05.15-2021.06.10. Several instructions were included with the released data. (1) The data were primarily obtained from BLS900 measurements, and missing flux measurements from the BLS900 instrument were substituted with measurements from the RR-RSS460 instrument. The missing data were denoted by -6999. (2) The dataset contained the following variables: Date/time (yyyy/m/d h:mm), the structural parameter of the air refractive index (Cn2, m-2/3), and the sensible heat flux (H, W/m^2). In this dataset, a time of 0:30 corresponds to the average data for the period between 0:00 and 0:30, and the data were stored in *.xlsx format. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) (for data processing) in the Citation section.

0 2022-06-04

Driving data of surface meteorological elements in the eastern Qinghai Tibet Plateau with a horizontal resolution of 3km * 3km and an hour (2010)

Based on the regional environment integrated system model developed by the Key Laboratory of regional climate and environment, Chinese Academy of Sciences, a regional climate model for convective analysis of the Qinghai Tibet Plateau is established. The grid center of the model simulation area is located at (34n, 100e), the horizontal resolution is 3km, and the number of simulation grid points of the model is 465 (longitude) x 375 (latitude). The vertical direction is 27 floors. The air pressure at the top of the model layer is 50 HPA. The buffer zone consists of 15 grids, the integration time is one year in 2010, and the horizontal resolution of the European medium range weather forecast center is 0.25x0 25. The reanalysis data of era5 with a time interval of 6 hours is used as the driving field to generate the driving data of surface meteorological elements on the Qinghai Tibet Plateau in 2010 with a horizontal resolution of 3 km * 3 km and a time interval of 1 hour After dynamic downscaling by using the convection analysis regional climate model of the Qinghai Tibet Plateau, the bottleneck problem of the lack of meteorological data sets with long-time series and high spatial-temporal resolution in the Qinghai Tibet Plateau and other regions is solved, so as to provide a solid and reliable scientific data foundation for the future change of climate and environment and the construction of ecological security barrier in the Qinghai Tibet Plateau.

0 2022-05-31

Monthly meteorological data set with 1km resolution on the Qinghai Tibet Plateau (2018-2019)

The monthly meteorological data set with 1km resolution on the Qinghai Tibet Plateau from 2018 to 2019 is from January 2018 to December 2019. The original data comes from chelsa (climatology at high resolution for the earth's land surface areas). After spatial correction, accuracy verification and cutting, 1km resolution precipitation, wind speed, air temperature and humidity data are obtained. The data can be opened and used by ArcGIS, envi or other geographic information systems and remote sensing software.

0 2022-05-19

Hourly meteorological forcing & land surface state dataset of Tibet Plateau with 10 km spatial resolution (2000-2010)

The near surface atmospheric forcing and surface state dataset of the Tibetan Plateau was yielded by WRF model, time range: 2000-2010, space range: 25-40 °N, 75-105 °E, time resolution: hourly, space resolution: 10 km, grid number: 150 * 300. There are 33 variables in total, including 11 near surface atmospheric variables: temperature at 2m height on the ground, specific humidity at 2m height on the ground, surface pressure, latitudinal component of 10m wind field on the ground, longitudinal component of 10m wind field on the ground, proportion of solid precipitation, cumulative cumulus convective precipitation, cumulative grid precipitation, downward shortwave radiation flux at the surface, downward length at the surface Wave radiation flux, cumulative potential evaporation. There are 19 surface state variables: soil temperature in each layer, soil moisture in each layer, liquid water content in each layer, heat flux of snow phase change, soil bottom temperature, surface runoff, underground runoff, vegetation proportion, surface heat flux, snow water equivalent, actual snow thickness, snow density, water in the canopy, surface temperature, albedo, background albedo, lower boundary Soil temperature, upward heat flux (sensible heat flux) at the surface and upward water flux (sensible heat flux) at the surface. There are three other variables: longitude, latitude and planetary boundary layer height.

0 2022-05-17

Satellite remote sensing precipitation reanalysis dataset over the Qinghai-Tibet Plateau (1998-2018)

This data is precipitation data, which is the monthly precipitation product of tropical rainfall measurement mission TRMM 3b43. It integrates the main area of the Qinghai Tibet Plateau (25 ~ 40 ° n; 25 ~ 40 ° n); The precipitation data of 332 meteorological stations are from the National Meteorological Information Center of China Meteorological Administration. The reanalysis data set is obtained by the station 3 ° interpolation optimization variational correction method. For the monthly sample data from January 1998 to December 2018, the spatial coverage is 25 ~ 40 ° n; 73 ~ 105 ° e, the spatial resolution is 1 ° * 1 °.

0 2022-04-19

AWS data from typical glacier (2019-2020)

Qiangyong glacier: 90.23 °E, 28.88° N, 4898 m asl. The surface is bedrock. The record contains data of 1.5 m temperature, 1.5 m humidity, 2 m wind speed, 2 m wind orientation, surface temperature, etc. Data from the automated weather station was collected using USB equipment at 19:10 on August 6, 2019, with a recording interval of 10 minutes, and data was downloaded on December 20, 2020. There is no missing data but a problem with the wind speed data after 9:30 on July 14, 2020 (most likely due to damage to the wind vane). Jiagang glacier: 88.69°E, 30.82°N, 5362 m asl. The surface is rubble and weeds. The records include 1.5 meters of temperature, 1.5 meters of humidity, 2 meters of wind speed, 2 meters of wind direction, surface temperature, etc. The initial recording time is 15:00 on August 9, 2019, and the recording interval is 1 minute. The power supply is mainly maintained by batteries and solar panels. The automatic weather station has no internal storage. The data is uploaded to the Hobo website via GPRS every hour and downloaded regularly. At 23:34 on January 5, 2020, the 1.5 meter temperature and humidity sensor was abnormal, and the temperature and humidity data were lost. The data acquisition instrument will be retrieved on December 19, 2020 and downloaded to 19:43 on June 23, 2020 and 3:36 on September 25, 2020. Then the temperature and humidity sensors were replaced, and the observations resumed at 12:27 on December 21. The current data consists of three segments (2019.8.9-2020.6.30; 2020.6.23-2020.9.25; 2020.12.19-2020.12.29), Some data are missing after inspection. Some data are duplicated in time due to recording battery voltage, which needs to be checked. The meteorological observation data at the front end of Jiagang mountain glacier are collected by the automatic weather station Hobo rx3004-00-01 of onset company. The model of temperature and humidity probe is s-thb-m002, the model of wind speed and direction sensor is s-wset-b, and the model of ground temperature sensor is s-tmb-m006. The meteorological observation data at the front end of Jianyong glacier are collected by the US onset Hobo u21-usb automatic weather station. The temperature and humidity probe model is s-thb-m002, the wind speed and direction sensor model is s-wset-b, and the ground temperature sensor model is s-tmb-m006.

0 2022-04-18

Spatial distribution data set of annual rainfall of external dynamic factors in Sanjiang Basin (2007-2018 average)

Due to the uneven distribution of meteorological stations in the Sanjiang River Basin, most of them are along the traffic trunk lines, and there are many areas without observation data, it is difficult to obtain accurate spatial distribution characteristics by ordinary spatial interpolation methods. Based on worldclim v2 1 rainfall data in the spatial data set, read the rainfall data in the study area of Sanjiang River basin with MATLAB language, calculate and output the data in GIS format, and use ArcGIS software to realize the spatial distribution data set of average annual rainfall in Sanjiang River Basin from 2007 to 2018. The data set effectively solves the problem of uneven distribution of meteorological stations in Sanjiang Basin due to complex terrain and many mountains and valleys, and can better reflect the long-term average distribution of annual rainfall in Sanjiang Basin from 2007 to 2018. It provides a basis for the external dynamic environmental factors of landslide development in the region.

0 2022-03-23

Time series data set of annual rainfall of external dynamic factors in Sanjiang Basin (2000-2020)

Rainfall is one of the important external dynamic environmental factors affecting the stability of landslides in Sanjiang Basin of Qinghai Tibet Plateau. Collect the monthly rainfall data of 10 meteorological observation stations in the typical area of Sanjiang River Basin in the study area, including Wudaoliang, Tuotuo River, qumalai, Naqu, Yushu, Dingqing, Changdu, Batang, Derong and Lijiang. Process the collected data through screening, elimination and classification calculation, and obtain the time series data set of annual rainfall external dynamic environmental factors in key areas of the study area from 2000 to 2020. Through this data set, It can reflect the change law and trend of annual rainfall in key areas of Sanjiang Basin from 2000 to 2020, and understand the change of rainfall, the external dynamic factor affecting the landslide on the Qinghai Tibet Plateau.

0 2022-03-22

Comprehensive observation data set of cloud precipitation process in Liupan Mountain (2021)

The data set is a sub data set of the comprehensive observation data set of cloud precipitation process, which is derived from the comprehensive investigation and test carried out in Liupanshan area during 2021. Liupanshan scientific research is carried out in Dawan station, Jingyuan station, Liupanshan station, Longde station, etc. Dawan station is mainly equipped with cfl-06 wind profile radar, ht101 cloud radar, mrr-2 micro rain radar, dsg5 raindrop spectrometer, three-dimensional anemometer, C12 laser cloud altimeter. Jingyuan station is mainly equipped with qfw-6000 microwave radiometer, hmb-kps cloud radar, dsg5 raindrop spectrometer Cl51 laser cloud altimeter. Liupanshan station is mainly equipped with ht101 cloud radar, mrr-2 micro rain radar, Ott laser raindrop spectrometer, cloud condensation nodule (CCN) counter, three-dimensional anemometer, FM120 droplet spectrometer and C12 laser cloud altimeter. Longde station is mainly equipped with rpg-hatpro-g4 microwave radiometer, cfl-06 wind profile radar, ht101 Cloud Radar, mrr-2 micro rain radar Ott laser raindrop spectrometer, C12 laser cloud altimeter. Meanwhile automatic weather station, iron tower (Shangpu), X-band all solid-state dual polarization Doppler Weather Radar (Pengyang County), gradient station and other observations were done. It can be used to study the impact of the eastward movement of the plateau system on the downstream, and to reveal the impact of the atmospheric boundary layer and free atmospheric exchange process on aerosols, clouds Fog and precipitation and their interaction.

0 2022-02-11

Comprehensive observation data set of cloud precipitation process in Sanjiang source (2021)

The data set is a sub data set of the comprehensive observation data set of cloud precipitation process, which is derived from the comprehensive investigation and test carried out in Sanjiangyuan area during 2021. The scientific research of Sanjiangyuan mainly focuses on Advanced Air King aircraft observation. The airborne observation system includes aerosol, cloud particle spectrometer and imager observation. The observation elements include precipitation particle concentration and image of IP probe, cloud particle concentration and image of CIP probe, cloud and aerosol particle data of CAS probe and Hotwire_ LWC probe liquid water data, CAPS Summary aerosol, cloud and precipitation comprehensive data, AIMMS probe conventional meteorological elements, PCASP -100 probe aerosol particle data. Ground observation includes raindrop spectrometer, microwave radiometer and X-band radar. Raindrop spectrometer mainly observes equivalent volume diameter and particle falling speed. Microwave radiometer mainly observes temperature, humidity, water vapor and liquid water. And X-band radar mainly observes intensity, velocity and spectral width. It can provide data support for the study of the impact of westerly monsoon synergy on the cloud precipitation process of Sanjiang source.

0 2022-02-10