This data set is the data set of climate elements in Hoh Xil area of Qinghai Province, covering the data of 14 observation stations, recording the climate observation data in 1990 in detail. Hoh Xil area in Qinghai Province has a high terrain with an average altitude of over 5000m. The climate is cold, the air is thin and the natural environment is bad. The vast area is still no man's land, known as "forbidden zone for human beings". Due to less interference from human activities, most of the area still maintains its original natural state. Its special geographical location, crustal structure and natural environment, as well as the unique composition of the biological flora, have been the focus of domestic surgical circles. The original data of the data set is digitized from the book "natural environment of Hoh Xil, Qinghai Province". The climate observation data include solar radiation, temperature, precipitation, air pressure, wind speed, etc. This data set provides basic data for the study of Hoh Xil area in Qinghai Province, and has reference value for the research in related fields.
LI Bingyuan
The surface air temperature dataset of the Tibetan Plateau is obtained by downscaling the China regional surface meteorological feature dataset (CRSMFD). It contains the daily mean surface air temperature and 3-hourly instantaneous surface air temperature. This dataset has a spatial resolution of 0.01°. Its time range for surface air temperature dataset is from 1979 to 2018. Spatial dimension of data: 73°E-106°E, 23°N-40°N. The surface air temperature with a 0.01° can serve as an important input for the modeling of land surface processes, such as surface evapotranspiration estimation, agricultural monitoring, and climate change analysis.
ZHOU Ji, WANG Wei , MA Jin
This data is a simulated output data set of 5km monthly hydrological data obtained by establishing the WEB-DHM distributed hydrological model of the source regions of Yangtze River and Yellow River, using temperature, precipitation and pressure as input data, and GAME-TIBET data as verification data. The dataset includes grid runoff and evaporation (if the evaporation is less than 0, it means deposition; if the runoff is less than 0, it means that the precipitation in the month is less than evaporation). This data is a model based on the WEB-DHM distributed hydrological model, and established by using temperature, and precipitation (from itp-forcing and CMA) as input data, GLASS, MODIA, AVHRR as vegetation data, and SOILGRID and FAO as soil parameters. And by the calibration and verification of runoff，soil temperature and soil humidity, the 5 km monthly grid runoff and evaporation in the source regions of Yangtze River and Yellow River from 1998 to 2017 was obtained. If asc can't open normally in arcmap, please delete the blacks space of the top 5 lines of the asc file.
WANG Lei
Monthly meteorological data of Sanjiangyuan includes 32 national standard meteorological stations. There are 26 variables: average local pressure, extreme maximum local pressure, date of extreme maximum local pressure, extreme minimum local pressure, date of extreme minimum local pressure, average temperature, extreme maximum temperature, date of extreme maximum temperature, extreme minimum temperature and date of extreme minimum temperature, average temperature anomaly, average maximum temperature, average minimum temperature, sunshine hours, percentage of sunshine, average relative humidity, minimum relative humidity, date of occurrence of minimum relative humidity, precipitation, days of daily precipitation >=0.1mm, maximum daily precipitation, date of maximum daily precipitation, percentage of precipitation anomaly, average wind speed, maximum wind speed, date of maximum wind speed, maximum wind speed, wind direction of maximum wind speed, wind direction of maximum wind speed and occurrence date of maximum wind speed. The data format is txt, named by the site ID, and each file has 26 columns. The names and units of each column are explained in the SURF_CLI_CHN_MUL_MON_readme.txt file. site_id lat lon elv name_cn 52754 37.33 100.13 8301.50 Gangcha 52833 36.92 98.48 7950.00 Wulan 52836 36.30 98.10 3191.10 Dulan 52856 36.27 100.62 2835.00 Qiapuqia 52866 36.72 101.75 2295.20 Xining 52868 36.03 101.43 2237.10 Guizhou 52908 35.22 93.08 4612.20 Wudaoliang 52943 35.58 99.98 3323.20 Xinghai 52955 35.58 100.75 8120.00 Guinan 52974 35.52 102.02 2491.40 Tongren 56004 34.22 92.43 4533.10 Togton He 56018 32.90 95.30 4066.40 Zaduo 56021 34.13 95.78 4175.00 Qumalai 56029 33.02 97.02 3681.20 Yushu 56033 34.92 98.22 4272.30 Maduo 56034 33.80 97.13 4415.40 Qingshui River 56038 32.98 98.10 9200.00 Shiqu 56043 34.47 100.25 3719.00 Guoluo 56046 33.75 99.65 3967.50 Dari 56065 34.73 101.60 8500.00 Henan 56067 33.43 101.48 3628.50 Jiuzhi 56074 34.00 102.08 3471.40 Maqu 56080 35.00 102.90 2910.00 Hezuo 56106 31.88 93.78 4022.80 Suo County 56116 31.42 95.60 3873.10 Dingqing 56125 32.20 96.48 3643.70 Nangqian 56128 31.22 96.60 3810.00 Leiwuqi 56137 31.15 97.17 3306.00 Changdu 56151 32.93 100.75 8530.00 Banma 56152 32.28 100.33 8893.90 Seda
National Meteorological Information Center
The data set contains meteorological observations from Guoluo Station from January 1, 2017, to December 31, 2017, and includes temperature (Ta_1_AVG), relative humidity (RH_1_AVG), vapour pressure (Pvapor_1_AVG), average wind speed (WS_AVG), atmospheric pressure (P_1), average downward longwave radiation (DLR_5_AVG), average upward longwave radiation (ULR_5_AVG), average net radiation (Rn_5_AVG), average soil temperature (Ts_TCAV_AVG), soil water content (Smoist_AVG), total precipitation (Rain_7_TOT), downward longwave radiation (CG3_down_Avg), upward longwave radiation (CGR3_up_Avg), average photosynthetically active radiation (Par_Avg), etc. The temporal resolution is 1 hour. Missing observations have been assigned a value of -99999.
HU Linyong
The meteorological elements distribution map of the plateau, which is based on the data from the Tibetan Plateau National Weather Station, was generated by PRISM model interpolation. It includes temperature and precipitation. Monthly average temperature distribution map of the Tibetan Plateau from 1961 to 1990 (30-year average values): t1960-90_1.e00，t1960-90_2.e00，t1960-90_3.e00，t1960-90_4.e00，t1960-90_5.e00， t1960-90_6.e00，t1960-90_7.e00，t1960-90_8.e00，t1960-90_9.e00，t1960-90_10.e00， t1960-90_11.e00，t1960-90_12.e00 Monthly average temperature distribution map of the Tibetan Plateau from 1991 to 2020 (30-year average values): t1991-20_1.e00，t1991-20_2.e00，t1991-20_3.e00，t1991-20_4.e00，t1991-20_5.e00， t1991-20_6.e00，t1991-20_7.e00，t1991-20_8.e00，t1991-20_9.e00，t1991-20_10.e00， t1991-20_11.e00，t1991-20_12.e00， Precipitation distribution map of the Tibetan Plateau from 1961 to 1990 (30-year average values): p1960-90_1.e00，p1960-90_2.e00，p1960-90_3.e00，p1960-90_4.e00，p1960-90_5.e00， p1960-90_6.e00，p1960-90_7.e00，p1960-90_8.e00，p1960-90_9.e00，p1960-90_10.e00， p1960-90_11.e00，p1960-90_12.e00 Precipitation distribution map of the Tibetan Plateau from 1991 to 2020 (30-year average values): p1991-20_1.e00，p1991-20_2.e00，p1991-20_3.e00，p1991-20_4.e00，p1991-20_5.e00， p1991-20_6.e00，p1991-20_7.e00，p1991-20_8.e00，p1991-20_9.e00，p1991-20_10.e00， p1991-20_11.e00，p1991-20_12.e00， The temporal coverage of the data is from 1961 to 1990 and from 1991 to 2020. The spatial coverage of the data is 73°~104.95° east longitude, 26.5°~44.95° north latitude, and the spatial resolution is 0.05 degrees×0.05 degrees (longitude×latitude), and it uses the geodetic coordinate projection. Name interpretation: Monthly average temperature: The average value of daily average temperature in a month. Monthly precipitation: The total precipitation in a month. Dimensions: The file format of the data is E00, and the DN value is the average value of monthly average temperature (×0.01°C) and the average monthly precipitation (×0.01 mm) from January to December. Data type: integer Data accuracy: 0.05 degrees × 0.05 degrees (longitude × latitude). The original sources of these data are two data sets of 1) monthly mean temperature and monthly precipitation observation data from 128 stations on the Tibetan Plateau and the surrounding areas from the establishing times of the stations to 2000 and 2) HadRM3 regional climate scenario simulation data of 50×50 km grids on the Tibetan Plateau, that is, the monthly average temperature and monthly precipitation simulation values from 1991 to 2020. From 1961 to 1990, the PRISM (Parameter elevation Regressions on Independent Slopes Model) interpolation method was used to generate grid data, and the interpolation model was adjusted and verified based on the site data. From 1991 to 2020, the regional climate scenario simulation data were downscaled to generate grid data by the terrain trend surface interpolation method. Part of the source data came from the results of the GCM model simulation; the GCM model used the Hadley Centre climate model HadCM2-SUL. a) Mitchell JFB, Johns TC, Gregory JM, Tett SFB (1995) Climate response to increasing levels of greenhouse gases and sulphate aerosols. Nature, 376, 501-504. b) Johns TC, Carnell RE, Crossley JF et al. (1997) The second Hadley Centre coupled ocean-atmosphere GCM: model description, spinup and validation. Climate Dynamics, 13, 103-134. The spatial interpolation of meteorological data adopted the PRISM (Parameter-elevation Regressions on Independent Slopes Model) method: Daly, C., R.P. Neilson, and D.L. Phillips, 1994: A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J. Appl. Meteor., 33, 140~158. Due to the difficult observational conditions in the plateau area and the lack of basic research data, there were deletions of meteorological data in some areas. After adjustment and verification, the accuracy of the data was only good enough to be used as a reference for macroscale climate research. The average relative error rate of the monthly average temperature distribution of the Tibetan Plateau from 1961 to 1990 was 8.9%, and that from 1991 to 2020 was 9.7%. The average relative error rate of precipitation data on the Tibetan Plateau from 1961 to 1990 was 20.9%, and that from 1991 to 2020 was 22.7%. The area of missing data was interpolated, and the values of obvious errors were corrected.
ZHOU Caiping
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