Based on China's daily meteorological elements data set and National Geographic basic data, the extreme precipitation, extreme temperature, drought intensity, drought frequency and other indicators in Hengduan Mountain area were calculated by using rclimdex, nspei and bilinear interpolation methods. The data set includes basic data set of disaster pregnant environment, basic data set of extreme precipitation index, basic data set of extreme temperature index, basic data set of drought intensity and frequency. The data set can provide a basic index system for regional extreme high temperature, precipitation and drought risk assessment.
The dataset contains observed climate data (1/1/2019-12/31/2019) from two automatic meteorological station located in the Qinghai Lake Basin. The niaodao station (36°58′N，99°52′E) is located in Gonghe County, Hainan Prefecture, Qinghai Province, and the wayanshan station (37°44′ N，100°05′ E) is located in Gangcha County, Haibei Prefecture, Qinghai Province. The observed elements include air temperature (℃) and relative humidity (%) at three layers (1m, 5m, and 10m), atmospheric pressure (hPa), and photosynthetically active radiation (W/m2). Both stations use CR1000 to collect climate data and record it every half an hour, the air temperature and humidity were measured by hmp155a, the atmospheric pressure was measured by CS106 and the photosynthetically active radiation was measured by LI200R. Our dataset will support the study of optimizing the ecological security barrier system in the key urbanized areas of the Tibetan Plateau.
CHEN Kelong, CHEN Zhirong
The data includes the daily mean value of stable isotope δ18O in precipitation, the air temperature and precipitation amounts in Bomi in 2008; the precipitation samples are collected by Bomi meteorological station, and the stable isotope of precipitation is measured at the Laboratoire des Sciences du Climat et de l’Environnement, France., The δ18O amounts were measured by equilibration on a MAT-252 mass spectrometer, with an analytical precision of 0.05‰. The air temperatures and precipitation amounts were recorded for each precipitation events at Bomi meteorological stations, through the average of the observed temperature before and after the precipitation event, and through the total precipitation amount for each event. The data study has been published in the Journal of Climate, entitled Precipitation Water Stable Isotopes in the South Tibetan Plateau: Observations and Modeling.
The data set is the daily precipitation stable isotope data (δ 18O, δ D, d-excess) from Satkhira, Barisal and sylhet3 stations in Bangladesh from 2017 to 2018. The data set was collected by Bangladesh Atomic Energy Commission (BAEC) and measured by picarro l2130i wavelength scanning cavity ring down spectrometer in the Key Laboratory of environment and surface processes, Institute of Qinghai Tibet Plateau, Chinese Academy of Sciences. Sampling location and time of three observation points: Satkhira ：2017.03.11-2018.07.16 Barisal：2017.03.05-2018.07.02 Sylhet : 2017.02.20-2018.09.04
Precipitation stable isotopes (2H and 18O) are adequately understood on their climate controls in the Tibetan Plateau, especially the north of Himalayas via about 30 years’ studies. However, knowledge of controls on precipitation stable isotopes in Nepal (the south of Himalayas), is still far from sufficient. This study described the intra-seasonal and annual variations of precipitation stable isotopes at Kathmandu, Nepal from 10 May 2016 to 21 September 2018 and analysed the possible controls on precipitation stable isotopes. All samples are located in Kathmandu, the capital of Nepal (27 degrees north latitude, 85 degrees east longitude), with an average altitude of about 1400 m. Combined with the meteorological data from January 1, 2001 to September 21, 2018, the values of precipitation (P), temperature (T) and relative humidity (RH) are given.
The data are collected from the automatic weather station (AWS, Campbell company) in the moraine area of the 24K glacier in the Southeast Tibet Plateau, Chinese Academy of Sciences. The geographic coordinates are 29.765 ° n, 95.712 ° E and 3950 m above sea level. The data include daily arithmetic mean data of air temperature (℃), relative humidity (%), wind speed (M / s), net radiation (w / m2), water vapor pressure (kPa) and air pressure (mbar). In the original data, an average value was recorded every 30 minutes before October 2018, and then an average value was recorded every 10 minutes. The temperature and humidity are measured by hmp155a temperature and humidity probe. The net radiation probe is nr01, the atmospheric pressure sensor probe is ptb210, and the wind speed sensor is 05103. These probes are 2 m above the ground. Data quality: the data has undergone strict quality control. The original abnormal data of 10 minutes and 30 minutes are removed first, and then the arithmetic mean of each hour is calculated. Finally, the daily value is calculated. If the number of hourly data is less than 24, the data is removed, and the corresponding date data in the data table is empty. In addition to the lack of some parameter data due to the thick snow and low temperature in winter and spring, the data can be used by scientific researchers who study climate, glacier and hydrology through strict quality control.
The data set contains the stable oxygen isotope data of ice core from 1864 to 2006. The ice core was obtained from Noijinkansang glacier in the south of Southern Tibetan Plateau, with a length of 55.1 meters. Oxygen isotopes were measured using a MAT-253 mass spectrometer (with an analytical precision of 0.05 ‰) at the Key Laboratory of CAS for Tibetan Environment and Land Surface Processes, China. Data collection location: Noijinkansang glacier (90.2 ° e, 29.04 ° n, altitude: 5950 m)
The daily values of air temperature, air pressure, relative humidity, wind speed, wind direction, precipitation, radiation, water vapor pressure, etc. observed by the comprehensive observation and research station of the west wind belt of mostag.
This data set includes the daily average values of air temperature, air pressure, relative humidity, wind speed, precipitation, total radiation, p2.5 concentration, short wave radiation, etc. observed by the comprehensive observation and research station of atmosphere and environment of Everest from 2017 to 2018.
This data set includes the daily average data of air temperature, relative humidity, precipitation, wind speed, wind direction, net radiation, air pressure, etc. of Southeast Tibet station from January 1, 2017 to December 31, 2018.
Lun LUO, Liping ZHU
Near surface atmospheric forcing data were produced by using Wether Research and Forecasting (WRF) model over the Heihe River Basin at hourly 0.05 * 0.05 DEG resolution, including the following variables: 2m temperature, surface pressure, water vapor mixing ratio, downward shortwave & upward longwave radiation, 10m wind field and the accumulated precipitation. The forcing data were validated by observational data collected by 15 daily Chinese Meteorological Bureau conventional automatic weather station (CMA), a few of Heihe River eco-hydrological process comprehensive remote sensing observation (WATER and HiWATER) site hourly observations were verified in different time scales, draws the following conclusion: 2m surface temperature, surface pressure and 2m relative humidity are more reliable, especially 2m surface temperature and surface pressure, the average errors are very small and the correlation coefficients are above 0.96; correlation between downward shortwave radiation and WATER site observation data is more than 0.9; The precipitation agreed well with observational data by being verified based on rain and snow precipitation two phases at yearly, monthly, daily time scales . the correlation coefficient between rainfall and the observation data at monthly and yearly time scales were up to 0.94 and 0.84; the correlation between snowfall and observation data at monthly scale reached 0.78, the spatial distribution of snowfall agreed well with the snow fractional coverage rate of MODIS remote sensing product. Verification of liquid and solid precipitation shows that WRF model can be used for downscaling analysis in complex and arid terrain of Heihe River Basin, and the simulated data can meet the requirements of watershed scale hydrological modeling and water resources balance. The data for 2000-2012 was provided in 2013. The data for 2013-2015 was updated in 2016. The data for 2016-2018 was updated in 2019.
This data set is output from WRF model. The data include ‘LU_INDEX’ (land use category), ‘ZNU’(eta values on half (mass) levels), ‘ZNW’(eta values on full (w) levels)，’ZS’(depths of centers of soil layers), ‘DZS’ (thicknesses of soil layers), ‘VAR_SSO’ (variance of subgrid-scale orography), ‘U’(x-wind component), ‘V’(y-wind component),’W’(z-wind component),’T’(perturbation potential temperature (theta-t0)), ‘Q2’ ('QV at 2 M), ‘T2’ (TEMP at 2 M), ‘TH2’ ('POT TEMP at 2 M), ‘PSFC’ (SFC pressure), ‘U10’ (U at 10 M), ‘V10’ (V at 10 M), ‘QVAPOR’ (Water vapor mixing ratio), ‘QLOUD’ (Cloud water mixing ratio),’QRAIN’ (Rain water mixing ratio), ‘QICE’ (Ice mixing ratio), ‘QSNOW’ (Snow mixing ratio), ‘SHDMAX’ (annual max veg fraction), ‘SHDMIN’ (annual min veg fraction), ‘SNOALB’ (annual max snow albedo in fraction), ‘TSLB’ (soil temperature), ‘SMOIS’ (soil moisture), ‘GRDFLX’ (ground heat flux), ‘LAI’ (Leaf area index),’ HGT’ (Terrain Height), ‘TSK’ (surface skin temperature), ‘SWDOWN’ (downward short wave flux at ground surface), ‘GLW’ (downward long wave flux at ground surface), ‘HFX’ (upward heat flux at the surface), ‘QFX’ (upward moisture flux at the surface), ‘LH’ (latent heat flux at the surface), ‘SNOWC’ (flag indicating snow coverage (1 for snow cover)), and so on. The data is in netCDF format with a spatial resolution of 10 km.
In April 2014 and may 2016, 21 Lakes (7 non thermal lakes and 14 thermal lakes) were collected in the source area of the Yellow River (along the Yellow River) respectively. The abundance of hydrogen and oxygen allogens was measured by Delta V advantage dual inlet / hdevice system in inno tech Alberta laboratory in Victoria, Canada. The isotope abundance was expressed in the form of δ (‰) (relative to the average seawater abundance in Vienna) ）Test error: δ 18O: 0.1 ‰, δ D: 1 ‰. The data also includes Lake area and lake basin area extracted from Landsat 2017 image data in Google Earth engine.
The matching data of water and soil resources in the Qinghai Tibet Plateau, the potential evapotranspiration data calculated by Penman formula from the site meteorological data (2008-2016, national meteorological data sharing network), the evapotranspiration under the existing land use according to the influence coefficient of underlying surface, and the rainfall data obtained by interpolation from the site rainfall data in the meteorological data, are used to calculate the evapotranspiration under the existing land use according to the different land types of land use According to the difference, the matching coefficient of water and soil resources is obtained. The difference between the actual rainfall and the water demand under the existing land use conditions reflects the matching of water and soil resources. The larger the value is, the better the matching is. The spatial distribution of the matching of soil and water resources can pave the way for further understanding of the agricultural and animal husbandry resources in the Qinghai Tibet Plateau.
This dataset includes data recorded by the Heihe integrated observatory network obtained from an observation system of Meteorological elements gradient of Daman Superstation from January 1 to December 31, 2018. The site (100.372° E, 38.856° N) was located on a cropland (maize surface) in the Daman irrigation, which is near Zhangye city, Gansu Province. The elevation is 1556 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (AV-14TH;3, 5, 10, 15, 20, 30, and 40 m, towards north), wind speed and direction profile (windsonic; 3, 5, 10, 15, 20, 30, and 40 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 2.5 m, 8 m in west of tower), four-component radiometer (PIR&PSP; 12 m, towards south), two infrared temperature sensors (IRTC3; 12 m, towards south, vertically downward), photosynthetically active radiation (LI190SB; 12 m, towards south, vertically upward; another four photosynthetically active radiation, PQS-1; two above the plants (12 m) and two below the plants (0.3 m), towards south, each with one vertically downward and one vertically upward), soil heat flux (HFP01SC; 3 duplicates with G1 below the vegetation; G2 and G3 between plants, -0.06 m), a TCAV averaging soil thermocouple probe (TCAV; -0.02, -0.04 m), soil temperature profile (AV-10T; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), soil moisture profile (CS616; -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_5 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_5 m, Ws_10 m, Ws_15 m, Ws_20 m, Ws_30 m, and Ws_40 m) (m/s), wind direction (WD_3 m, WD_5 m, WD_10 m, WD_15 m, WD_20 m, WD_30m, and WD_40 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_1, below the vegetation; Gs_2, and Gs_3, between plants) (W/m^2), 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), above the plants photosynthetically active radiation of upward and downward (PAR_U_up and PAR_U_down) (μmol/ (s m-2)), and below the plants photosynthetically active radiation of upward and downward (PAR_D_up and PAR_D_down) (μmol/ (s m-2)). 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 meterological data during September 17 and November 7 and TCAV data after November 7 were wrong because the malfunction of datalogger. 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: 2018-6-10 10:30. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) for data processing) in the Citation section.
LIU Shaomin, XU Ziwei, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
This data set includes the daily values of temperature, air pressure, relative humidity, wind speed, precipitation, total radiation, etc. observed at Namuco station from January 1, 2017 to December 31, 2018.
WANG Junbo, WU Guangjian
The dataset records the Ali Desert Environment Integrated Observation and Research Station, the meteorological dataset for 2017-2018, and the time resolution of the data is days. It includes the following basic meteorological parameters: temperature (1.5 meters from the ground, once every half hour, unit: Celsius), relative humidity (1.5 meters from the ground, half an hour, unit: %), wind speed (1.5 meters from the ground, half an hour) , unit: m / s), wind direction (1.5 meters from the ground, once every half hour, unit: degrees), air pressure (1.5 meters from the ground, once every half hour, unit: hPa), precipitation (24 hours, unit: mm ), water vapor pressure (unit: Kpa), evaporation (unit: mm), downward short-wave radiation (unit: W/m2), upward short-wave radiation (unit: W/m2), downward long-wave radiation (unit: W/m2) ), upward long-wave radiation (unit: W/m2), net radiation (unit: W/m2), surface albedo (unit: %). Data collection location: Observation Field of Ali Desert Environment Comprehensive Observation and Research Station, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Longitude: 79°42'5"; Latitude: 33°23'30"; Altitude: 4264 meters.
Based on the WRF model, using ERA5 reanalysis data as the initial and boundary fields, the high-resolution low-level atmospheric structure and the earth atmosphere exchange data set of the Qinghai Tibet Plateau are preliminarily obtained by the method of dynamic downscaling. The time range of this data set is from August 1 to August 31, 2014, with a time resolution of 1 hour, a horizontal range of 25 °N-40 °N, 70oE-105oE, and a horizontal resolution of 0.05 °. The data format is NetCDF, and one file is output every hour. The file is named after the date. The lower atmospheric structure data includes temperature, relative humidity, water vapor mixing ratio, potential height, meridional wind and latitudinal wind meteorological elements, with 34 isobaric surfaces in the vertical direction; the surface air exchange data set includes the upward / downward short wave radiation, upward / downward long wave radiation, surface sensible heat and flux, 2m air temperature and water vapor mixing ratio, 10m wind, etc. The data set can provide data support for the study of weather process and climate environment in the Tibetan Plateau.
（1）This data set provides atmospheric temperature (2 meters above land surface), vapor content, precipitation, press, wind velocity and solar radiation (since 2015). （2）All data were generated using AWS (auto weather station), and been calculated their daily average. （3）All data are presented here are raw data, after being evaluated regarding their quality. （4）This data set could be used in background description for related studies.
WEI Da, WANG Xiaodan
This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Dunhuang Station from January 1 to December 31, 2018. The site (93.708° E, 40.348° N) was located on a wetland in the Dunhuang west lake, Gansu Province. The elevation is 990 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (4m and 8 m, towards north), wind speed and direction profile (windsonic; 4m and 8 m, towards north), air pressure (1 m), rain gauge (4 m), infrared temperature sensors (4 m, towards south, vertically downward), soil heat flux (-0.05 and -0.1m ), soil soil temperature/ moisture/ electrical conductivity profile (below the vegetation in the south of tower, -0.05 and -0.2 m), photosynthetically active radiation (4 m, towards south), four-component radiometer (4 m, towards south), sunshine duration sensor(4 m, towards south). The observations included the following: air temperature and humidity (Ta_4 m, Ta_8 m; RH_2 m, RH_4 m, RH_8 m) (℃ and %, respectively), wind speed (Ws_4 m, Ws_8 m) (m/s), wind direction (WD_4 m, WD_8 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) (℃), photosynthetically active radiation (PAR) (μmol/ (s m-2)), soil heat flux (Gs_0.05m, Gs_0.1m) (W/m^2), soil temperature (Ts_0.05m, Ts_0.2m) (℃), soil moisture (Ms_0.05m, Ms_0.2m) (%, volumetric water content), soil conductivity (Ec_0.05m, Ec_0.2m)(μs/cm), sun time(h). 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 data were missing during Jan. 23 to Jan. 24 because of collector failure; the data during Mar. 17 and May 24 were wrong because of the tower body tilt; The air humidity data were rejected due to program error. (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: 2018-6-10 10:30.
ZHAO Changming, ZHANG Renyi