The surface PM2.5 concentration data of Tibet Plateau is named by date (YYYYMMDD). Each NC file contains one day's data, which is composed of PM2.5 concentration, longitude, latitude, and time information of the area (the corresponding variables in the data are named with PM2.5, lon, lat, time). The data inversion relies on the reanalysis data MERRA-2 released by NASA and the AOD product of Multi-angle Imaging SpectroRadiometer (MISR). MERRA-2 is mainly based on NASA GMAO Earth system model version 5 (GEOS 5). The algorithm is able to assimilate all the in-situ and re- motely-sensed atmospheric data. This dataset mainly focuses on the aerosol field of MERRA-2. This is the first multi-decadal reanalysis within which meteorological and aerosol observations are jointly assimilated into a global assimilation system. MISR views Earth with cameras pointed in 9 different directions， which can help us know the amount of sunlight that is scattered in different directions under natural conditions. The main data products used in this data algorithm are MERRA-2 aerosol analysis product (M2T1NXAER) and MISR Level 3 version 4 global aerosol products (MIL3DAEN_4). Firstly, the ratio of PM2.5 to AOD in each grid was calculated by using the aerosol information provided by MERRA-2. Second, the PM2.5 concentration of the grid was calculated by multiplying the AOD of MISR by the ratio. The mean prediction error of PM2.5 concentration obtained by this method is within 20 μg/m3. The corresponding PM2.5 products can be used for the assessment of particulate pollution in the Tibet Plateau.
FU Disong
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.
ZHANG Dongqi
The data of aerosol optical depth were daily collected at Qomolangma Station for Atmospheric and Environmental Observation and Research with An automatic sun/sky scanning radiometer (Cimel 318), over the period from Jan. to Dec. The data were measured at 2020. 340, 380, 440, 500, 675, 870 and 1020 nm channel with uncertainty of 0.01 - 0.02.
CONG Zhiyuan
The data set records the average sunshine hours in the main areas of Qinghai Province, and the data are divided by region. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 18 data tables with the same structure. For example, the data table in 2001 has nine fields: Field 1: month Field 2: Xining Field 3: Ping An Field 4: source Field 5: chabcha Field 6: colleagues Field 7: Dawu Field 8: Jiegu Field 9: Delingha
Qinghai Provincial Bureau of Statistics
The data set records the average temperature in the main areas of Qinghai Province, and the data are divided by region. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 18 data tables with the same structure. For example, the data table in 2001 has nine fields: Field 1: month Field 2: Xining Field 3: Ping An Field 4: source Field 5: chabcha Field 6: colleagues Field 7: Dawu Field 8: Jiegu Field 9: Delingha
Qinghai Provincial Bureau of Statistics
The data set records the average wind speed in the main areas of Qinghai Province, and the data are divided by region. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 19 data tables, which are: average wind speed in main areas of Qinghai Province in 1998.xls, average wind speed in main areas of Qinghai Province in 1999.xls, average wind speed in main areas of Qinghai Province in 2000.xls, average wind speed in main areas of Qinghai Province in 2018.xls, etc. The data table structure is the same. For example, the data table in 1999 has nine fields: Field 1: month Field 2: Xining Field 3: Ping An Field 4: source Field 5: chabcha Field 6: colleagues Field 7: Dawu Field 8: Jiegu Field 9: Delingha
Qinghai Provincial Bureau of Statistics
The data set records the precipitation statistics of the main areas in Qinghai Province, and the data are divided by region. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 18 data tables with the same structure. For example, the data table in 2001 has nine fields: Field 1: month Field 2: Xining Field 3: Ping An Field 4: source Field 5: chabcha Field 6: colleagues Field 7: Dawu Field 8: Jiegu Field 9: Delingha
Qinghai Provincial Bureau of Statistics
The data set includes annual mass balance of Naimona’nyi glacier (northern branch) from 2008 to 2018, daily meteorological data at two automatic meteorological stations (AWSs) near the glacier from 2011 to 2018 and monthly air temperature and relative humidity on the glacier from 2018 to 2019. In the end of September or early October for each year , the stake heights and snow-pit features (snow layer density and stratigraphy) are manually measured to derive the annual point mass balance. Then the glacier-wide mass balance was then calculated （Please to see the reference). Two automatic weather stations (AWSs, Campbell company) were installed near the Naimona’nyi Glacier. AWS1, at 5543 m a. s.l., recorded meteorological variables from October 2011 at half hourly resolution, including air temperature (℃), relative humidity (%), and downward shortwave radiation (W m-2) . AWS2 was installed at 5950 m a.s.l. in October 2010 at hourly resolution and recorded wind speed (m/s), air pressure (hPa), precipitation (mm). Data quality: the quality of the original data is better, less missing. Firstly, the abnormal data in the original records are removed, and then the daily values of these parameters are calculated. Two probes (Hobo MX2301) which record air temperature and relative humidity was installed on the glacier at half hour resolution since October 2018. The observed meteorological data was calculated as monthly values. The data is stored in Excel file. It can be used by researchers for studying the changes in climate, hydrology, glaciers, etc.
Huabiao Zhao
The West Pamir glacier meteorological station in Tajikistan (38 ° 3 ′ 15 ″ n, 72 ° 16 ′ 52 ″ e, 3730m) is jointly constructed by Urumqi Institute of desert meteorology of China Meteorological Administration, Institute of water energy and ecology of Tajik National Academy of Sciences and Tajik hydrometeorological Bureau. The observational data include hourly meteorological elements (average wind direction (°), average internal wind speed (M / s), maximum wind speed (°), maximum wind speed (M / s), average temperature (℃), maximum temperature (℃), minimum temperature (℃), average relative humidity (%), minimum relative humidity (%), average atmospheric pressure (HPA), maximum atmospheric pressure (HPA), minimum atmospheric pressure (HPA)). The data period is from November 1, 2019 to November 30, 2020 Meteorological observation data can provide important basic data for the study of the relationship between climate change, glaciers and water resources in the West Pamir mountains, and provide important data for the economic construction of the lower reaches of the Amu Darya River Basin in Tajikistan.
HUO Wen, Ruibo Zhang
Kara batkak glacier weather station in Western Tianshan Mountains of Kyrgyzstan (42 ° 9'46 ″ n, 78 ° 16'21 ″ e, 3280m). The observational data include hourly meteorological elements (hourly rainfall (mm), instantaneous wind direction (°), instantaneous wind speed (M / s), 2-minute wind direction (°), 2-minute wind speed (M / s), 10 minute wind direction (°), 10 minute wind speed (M / s), maximum wind direction (°), maximum wind speed (M / s), maximum wind speed time, maximum wind direction (°), maximum wind speed (M / s), maximum wind speed time, maximum instantaneous wind speed within minutes) Direction (°), maximum instantaneous wind speed in minutes (M / s), air pressure (HPA), maximum air pressure (HPA), time of maximum air pressure, time of minimum air pressure (HPA), time of minimum air pressure. Meteorological observation elements, after accumulation and statistics, are processed into climate data to provide important data for planning, design and research of agriculture, forestry, industry, transportation, military, hydrology, medical and health, environmental protection and other departments.
HUO Wen
This data is based on the modified radiosonde observation data of 2008 used by Chen et al. 2016, Chen et al. 2011 and Chen et al. 2013. The vertical resolution of the processed atmospheric wind speed, wind direction, temperature, relative humidity and pressure is 20m. The data of three observation stages in 2008 are processed, namely iop1, IOP2 and iop3. Iop1 started from February 25, 2008 to March 19, 2008, IOP2 from May 13, 2008 to June 12, 2008, and iop3 from July 7, 2008 to July 16, 2008.
CHEN Xuelong, MA Yaoming
(1) Daily average of atmospheric black carbon concentration(ng/m3) at the NASDE. (2) Instruments: Aethalometer (AE33). This instrument collected data with a resolution of one minute. The abnormal data collected at the start-up or faulty stage were manually excluded before analysis further. We generated daily average based on the National Ambient Air Quality Standard of China (GB 3095-2012). (3) From May to November, 2018, a wildlife Conservation Station nearby was constructed, which frequentlyexposed largeamounts of particles, thus the BC concentration was far beyond that collected in the same season of other years. The data in this period shouldbeusedwith greatcaution. Due to problems in the instrument or electric power supply, thedata was lost in other periods. (4) The instrument was placed at the Ngari Station for Desert Environment Observation and Research (79.70° E, 33.39°N, 4270 m above sea level).
WANG Mo, XU Baiqing, ZHAO Huabiao, YANG Song
(1) This data is the meteorological data of mustag station from 2015 to 2018. The observation point is located at 75.29 ° E and 38 ° 40 'n, with an altitude of 4924 meters. The parameters include temperature, relative humidity, air pressure, precipitation and wind speed. (2) Data source and processing method: the data comes from the half-hour data of the automatic weather station of the station. Firstly, the abnormal data in the original records are removed, and then the daily values of these parameters are calculated. (3) Data quality description: data is discontinuous in some periods from January to March (4) The meteorological data can be used in the research of atmospheric science, climatology, physical geography and ecology.
XIE Ying
(1) This data is the meteorological data of mustag station in 2019. The observation point is located at 75 ° 03.35'e and 38 ° 24.77'n, with an altitude of 3650m. The parameters include temperature, relative humidity, air pressure, precipitation, radiation and wind speed. (2) Data source and processing method: the data comes from the half-hour data of the automatic weather station of the station. Firstly, the abnormal data in the original records are removed, and then the daily values of these parameters are calculated. (3) The meteorological data can be used in the research of atmospheric science, climatology, physical geography and ecology.
XIE Ying
This data is the data of automatic weather station (AWS, Campbell company) set up at the top of the mountain in the west slope of Sejila by the comprehensive observation and research station of Southeast Tibet alpine environment of Chinese Academy of Sciences in 2016. The geographical coordinates are 29.5919 n, 94.6102 e, with an altitude of 4640 m, and the underlying surface is alpine grassland. The data include daily arithmetic mean data of air temperature (℃), relative humidity (%), wind speed (M / s) and air pressure (MB) and daily accumulated value of precipitation. The original data is an average of 30 minutes before October 2018, and an average of 10 minutes after that. The temperature and humidity are measured by hmp155a temperature and humidity probe. The rainfall instrument model is rg3-m, the atmospheric pressure sensor probe is ptb210, and the wind speed sensor is 05103. These probes are 2 m above the ground. In terms of data quality: the obvious abnormal values are eliminated, the battery is damaged due to snow in the first half of 2019, and the data is missing. The missing temperature data is corrected by using the temperature fitting regression of 43900 m at nearby stations, and the data is yellow. Please pay attention when using it; the monitoring of precipitation starts from August 2019. The data station is a high altitude meteorological station in Southeast Tibet, which will be updated from time to time. It can be used by scientific researchers studying ecology, climate, hydrology, glaciers, etc.
LUO Lun
This data is the data of the automatic weather station (AWS, Campbell company) set up in Yigong Zangbu basin by the Southeast Tibet alpine environment comprehensive observation and research station of Chinese Academy of Sciences in 2018. The geographic coordinates are 30.1741 n, 94.9334 e, and the altitude is 2282m. The underlying surface is grassland. The data include daily arithmetic mean data of air temperature (℃), relative humidity (%), wind speed (M / s), water vapor pressure (kPa) and air pressure (MB) and daily accumulated value of precipitation. The original data is an average value recorded in 10 minutes. The temperature and humidity are measured by hmp155a temperature and humidity probe. The rainfall instrument is tb4, the atmospheric pressure sensor is ptb210, and the wind speed sensor is 05103. These probes are 2 m above the ground. Data quality: the quality of the original data is better, less missing. The data station is a meteorological station in the lower altitude of the Qinghai Tibet Plateau, which will be updated from time to time in the future. It can be used by researchers studying climate, hydrology, glaciers, etc.
LUO Lun
Based on the meteorological data of 105 meteorological stations in and around the Qinghai Tibet Plateau from 1980 to 2019 (data from China Meteorological Administration and National Meteorological Science Data Center), the oxygen content was calculated. It was found that there was a significant linear correlation between oxygen content and altitude, y = -0.0263x + 283.8, R2 = 0.9819. Therefore, the oxygen content distribution map can be calculated based on DEM data grid. Due to the limitation of the natural environment in the Qinghai Tibet Plateau, there are few related fixed-point observation institutions. This data can reflect the distribution of oxygen content in the Qinghai Tibet Plateau to a certain extent, and has certain reference significance for the research of human living environment in the Qinghai Tibet Plateau.
XIN Zhongbao
The long-time series data set of extreme precipitation index in the arid region of Central Asia contains 10 extreme precipitation index long-time series data of 49 stations. Based on the daily precipitation data of the global daily climate historical data network (ghcn-d), the data quality control and outlier elimination were used to select the stations that meet the extreme precipitation index calculation. Ten extreme precipitation indexes (prcptot, SDII, rx1day, rx5day, r95ptot, r99ptot, R10, R20) defined by the joint expert group on climate change detection and index (etccdi) were calculated 、CWD、CDD）。 Among them, there are 15 time series from 1925 to 2005. This data set can be used to detect and analyze the frequency and trend of extreme precipitation events in the arid region of Central Asia under global climate change, and can also be used as basic data to explore the impact of extreme precipitation events on agricultural production and life and property losses.
YAO Junqiang, CHEN Jing, LI Jiangang
This dataset includes the observation data from 01 Jan. 2019 through 31 Dec. 2018, collected by lysimeters, which are located at 115.788 E, 40.349 N and 480 m above sea level, near the Huailai Station in East Garden Town, Huailai County, Hebei Province. The land cover around the station was maize crop. The weighable lysimeter was built by UMS GmbH (Germany), with a surface area of 1m2, and a soil column of 1.5 m high. The original data sampling frequency was 1 Hz, and then averaged to 10min for distribution. The precision of the weighing data is 10g (equivalent to 0.01mm). During the crop growth period, a lysimeter is covered by bare soil and another one is covered by planted maize. The soil moisture, temperature and soil water potential sensors are installed both inside and outside of the lysimeter to ensure that the water cycle in the soil column is consistent with that of the field. Different sensors are located at different depths: 5, 50, 100 cm for soil temperature sensors, and 5, 10, 30, 50, 100 cm for soil moisture sensors, and 30 and 140cm for soil water potential sensors (the tensionmeter here can also measure soil temperature at 30, 140 cm). The soil heat flux plates in both lysimeters are buried at 10cm depth. The data processes and quality control according to: 1) ensuring there were 144 data every day, the lost data were replaced by -6999; 2) deleting the abnormal data; 3) deleting the outlier data; 4) keeping the consistent date and time format (e.g.2018-6-10 10:30). The distributed data include the following variables: Date-Time, Weight (I.L_1_WAG_L_000(Kg), I.L_2_WAG_L_000(Kg)), Drainage Weight (I.L_1_WAG_D_000(Kg), I.L_2_WAG_D_000(Kg)), Soil Heat Flux (Gs_1_10cm, Gs_2_10cm) (W/m2), Soil Moisture (Ms_1_5cm, Ms_1_10cm, Ms_1_30cm, Ms_1_50cm, Ms_1_100cm, Ms_2_5cm, Ms_2_10cm, Ms_2_30cm, Ms_2_50cm, Ms_2_100cm) (%), Soil Temperature (Ts_1_5cm , Ts_1_30cm, Ts_1_50cm, Ts_1_100cm, Ts_1_140cm, Ts_2_5cm , Ts_2_30cm, Ts_2_50cm, Ts_2_100cm, Ts_2_140cm) (C), Soil Water Potential (TS_1_30(hPa), TS_1_140(hPa), TS_2_30(hPa), TS_2_140(hPa)). The format of datasets was *.xls.
LIU Shaomin, ZHU Zhongli, XU Ziwei
This dataset includes the observation data from 01 Jan. 2019 through 31 Dec. 2019, collected by lysimeters, which are located at 115.788E, 40.349N and 480 m above sea level, near the Huailai Station in East Garden Town, Huailai County, Hebei Province. The land cover around the station was maize crop. The weighable lysimeter was built by UMS GmbH (Germany), with a surface area of 1m2, and a soil column of 1.5 m high. The original data sampling frequency was 1 Hz, and then averaged to 10min for distribution. The precision of the weighing data is 10g (equivalent to 0.01mm). During the crop growth period, a lysimeter is covered by bare soil and another one is covered by planted maize. The soil moisture, temperature and soil water potential sensors are installed both inside and outside of the lysimeter to ensure that the water cycle in the soil column is consistent with that of the field. Different sensors are located at different depths: 5, 50, 100 cm for soil temperature sensors, and 5, 10, 30, 50, 100 cm for soil moisture sensors, and 30 and 140cm for soil water potential sensors (the tensionmeter here can also measure soil temperature at 30, 140 cm). The soil heat flux plates in both lysimeters are buried at 10cm depth. The data processes and quality control according to: 1) ensuring there were 144 data every day, the lost data were replaced by -6999; 2) deleting the abnormal data; 3) deleting the outlier data; 4) keeping the consistent date and time format (e.g. 2019-01-01 10:30). The distributed data include the following variables: Date-Time, Weight (I.L_1_WAG_L_000(Kg), I.L_2_WAG_L_000(Kg)), Drainage Weight (I.L_1_WAG_D_000(Kg), I.L_2_WAG_D_000(Kg)), Soil Heat Flux (Gs_1_10cm, Gs_2_10cm) (W/m2), Soil Moisture (Ms_1_5cm, Ms_1_10cm, Ms_1_30cm, Ms_1_50cm, Ms_1_100cm, Ms_2_5cm, Ms_2_10cm, Ms_2_30cm, Ms_2_50cm, Ms_2_100cm) (%), Soil Temperature (Ts_1_5cm , Ts_1_30cm, Ts_1_50cm, Ts_1_100cm, Ts_1_140cm, Ts_2_5cm , Ts_2_30cm, Ts_2_50cm, Ts_2_100cm, Ts_2_140cm) (C), Soil Water Potential (TS_1_30(hPa), TS_1_140(hPa), TS_2_30(hPa), TS_2_140(hPa)). The format of datasets was *.xls.
LIU Shaomin, ZHU Zhongli, XU Ziwei
