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.
SUN Peng
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
Xiaodongkemadi glacier, located in Tanggula Mountain, is a continental glacier. The glacier is a compound valley glacier formed by the confluence of a southward main glacier (also known as dadongkemadi glacier) and a Southwest Branch glacier (also known as xiaodongkemadi glacier). The daily temperature and humidity observation data of 6 points in xiaodongkemadi, 4 points in Yangbajing and 4 points in hariqin from 2012 to 2015.
XU Baiqing
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.
Luo Lun
This dataset contains the automatic weather station (AWS) measurements from Bajitan Gobi station in the flux observation matrix from 13 May to 21 September, 2012. The site (100.30420° E, 38.91496° N) was located in a Gobi surface, which is near Zhangye city, Gansu Province. The elevation is 1562 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP45AC; 5 m and 10 m, towards north), air pressure (PTB110; 2 m), rain gauge (TE525M; 10 m), wind speed (03001; 5 m and 10 m, towards north), wind direction (03001; 10 m, towards north), a four-component radiometer (CNR1; 6 m, towards south), two infrared temperature sensors (IRTC3; 6 m, vertically downward), soil temperature profile (AV-10T; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), soil moisture profile (ECh2o-5; -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), and soil heat flux (HFT3; 3 duplicates, 0.06 m). The observations included the following: air temperature and humidity (Ta_5 m and Ta_10 m, RH_5 m and RH_10 m) (℃ and %, respectively), air pressure (press, hpa), precipitation (rain, mm), wind speed (Ws_5 m and Ws_10 m, m/s), wind direction (WD_10 m, °), 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 IR_2, ℃), soil heat flux (Gs_1, Gs_2 and Gs_3, W/m^2), soil temperature profile (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm, and Ts_100 cm, ℃), and soil moisture profile (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm, and Ms_100 cm, %). The data processing and quality control steps were as follows. (1) The AWS data were averaged over intervals of 10 min; therefore, there were 144 records per day. The missing data were filled with -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) In this dataset, the time of 0:10 corresponds to the average data for the period between 0:00 and 0:10; the data were stored in *.xlsx format. (5) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, XU Ziwei
This dataset contains the flux observation matrix measurements obtained from the automatic weather station (AWS) at the Daman superstation between 10 May and 26 September, 2012. The site (100.37223° E, 38.85551° N) was located in a cropland (maize surface) in the Daman irrigation, which is near Zhangye, Gansu Province. The elevation is 1556.06 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), four-component radiometer (PSP&PIR; 12 m, towards south), two infrared temperature sensors (IRTC3; 12 m, vertically downward), photosynthetically active radiation (LI-190SB; 12 m, towards south), 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), and soil heat flux (HFP01SC; 3 duplicates with one below the vegetation; and the other between plants, -0.06 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_30 m, 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 IR_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, 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, ℃), and 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, %). The data processing and quality control steps were as follows. (1) The AWS data were averaged over intervals of 10 min; therefore, there were 144 records per day. The missing data were filled with -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) In this dataset, the time of 0:10 corresponds to the average data for the period between 0:00 and 0:10; the data were stored in *.xlsx format. (5) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, XU Ziwei
This dataset is derived from the global atmospheric reanalysis dataset, ERA-Interim, based on the 4-dimensional variational analysis (4D-Var) released by the European Centre for Medium-Range Weather Forecasts (ECMWF). ERA-Interim represents a major undertaking by ECMWF (European Centre for Medium-Range Weather Forecasts) to produce a reanalysis with an improved atmospheric model and assimilation system which replaces those used in ERA-40, particularly for the data-rich 1990s and 2000s, and to be continued as an ECMWF Climate Data Assimilation System (ECDAS) until superseded by a new reanalysis. Through systematic increases in computing power, 4-dimensional variational assimilation (4D-Var) became feasible and part of ECMWF operations since 1997. Enhanced computing power also allowed horizontal resolution to be increased from T159 to T255, and the latest Integrated Forecasting System(IFS CY31r1 and CY31r2) to be used, taking advantage of improved model physics. ERA-interim retains the same 60 model levels used for ERA-40 with the highest level being 0.1 hPa. Besides, data assimilation of ERA-Interim also benefits from quality control that draws on experience from ERA-40 and JRA-25, variational bias correction of satellite radiance data, and more extensive use of radiances with an improved fast radiative transfer model. In addition, ERA-Interim uses the new ERS (European Remote Sensing Satellite) altimeter wave heights, EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) reprocessed winds and clear-sky radiances, GOME (Global Ozone Monitoring Experiment) ozone data from the Rutherford Appleton Laboratory, and CHAMP (CHAllenging Minisatellite Payload), GRACE (Gravity Recovery and Climate Experiment), and COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) GPS radio occultation measurements processed and archived by UCAR (University Corporation for Atmospheric Research).
DENG Chuangwu
The China Meteorological Forcing Dataset (CMFD) is a high spatial-temporal resolution gridded near-surface meteorological dataset that was developed specifically for studies of land surface processes in China. The dataset was made through fusion of remote sensing products, reanalysis dataset and in-situ observation data at weather stations. Its record starts from January 1979 and keeps extending (currently up to December 2018) with a temporal resolution of three hours and a spatial resolution of 0.1°. Seven near-surface meteorological elements are provided in CMFD, including 2-meter air temperature, surface pressure, specific humidity, 10-meter wind speed, downward shortwave radiation, downward longwave radiation and precipitation rate.
YANG Kun, HE Jie, WENJUN TANG , LU Hui, QIN Jun , CHEN Yingying, LI Xin
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.
GAO Jing
Solar radiation data were obtained using the internationally accepted solar radiation meter (LI200SZ, LI-COR, Inc., USA). The measured data are total solar radiation, including direct and diffuse solar radiation, with a wavelength range of 400-1100 nm. The units of the measurement results are W/㎡, and the typical error under natural lighting is ±3% (within an incident angle of 60°). Data from different locations in the three poles (Everest Station and Namco Station on the Tibetan Plateau, Sodankylä Station in the Arctic, and Dome A Station in the Antarctic) are derived from site cooperation and website downloads. The temporal coverage of data from the Everest Station and Namco Station on the Tibetan Plateau is from 2009 to 2016, that from the Sodankylä Station in the Arctic is from 2001 to 2017, and that from the Dome A Station in the Antarctic is from 2005 to 2014.
BAI Jianhui
The dataset of CMA operational meteorological stations observations in the Heihe river basin were provided by Gansu Meteorological Administration and Qinghai Meteorological Administration. It included: (1) Diurnal precipitation, sunshine, evaporation, the wind speed, the air temperature and air humidity (2, 8, 14 and 20 o'clock) in Mazongshan, Yumen touwnship, Dingxin, Jinta, Jiuquan, Gaotai, Linze, Sunan, Zhangye, Mingle, Shandan and Yongchang in Gansu province (2) the wind direction and speed, the temperature and the dew-point spread (8 and 20 o'clock; 850, 700, 600, 500, 400, 300, 250, 200, 150, 100 and 50hpa) in Jiuquan, Zhangye and Mingqin in Gansu province and Golmud, Doulan and Xining in Qinghai province (3) the surface temperature, the dew point, the air pressure, the voltage transformation (3 hours and 24 hours), the weather phenomena (the present and the past), variable temperatures, visibility, cloudage, the wind direction and speed, precipitation within six hours and unusual weather in Jiuquan, Sunan, Jinta, Dingxin, Mingle, Zhangye, Gaotai, Shandan, Linze, Yongchang and Mingqin in Gansu province and Tuole, Yeniugao, Qilian, Menyuan, Xining, Gangcha and Huangyuan in Qinhai province.
Gansu meteorological bureau, Qinghai Meteorological Bureau
Original information on the long-term dry-wet index (1500-2000) in western China is obtained by integrating data on dry-wet/drought-flood conditions and precipitation amounts in the western region published over more than a decade. The integrated data sets include tree rings, ice cores, lake sediments, historical materials, etc., and there are more than 50 such data sets. In addition to widely collecting representative data sets on dry-wet changes in the western region, this study also clarifies the main characteristics of the dry-wet changes and climate zones in the western region, and the long-term dry-wet index sequence was generated by extracting representative data from different zones. The data-based dry-wet index sequence has a 10-year temporal resolution for five major characteristic climate zones in the western region over nearly four hundred years and a high resolution (annual resolution) for three regions over the past five hundred years. The five major characteristic climate zones in the western region with a 10-year dry-wet index resolution over the last four hundred years are the arid regions, plateau bodies, northern Xinjiang, Hetao region, and northeastern plateau, and the three regions with a annual resolution over the last five hundred years are the northeastern plateau, Hetao region, and northern Xinjiang. For a detailed description of the data, please refer to the data file named Introduction of Dry-Wet Index Sequence Data for West China.doc.
QIAN Weihong, LIN Xiang
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
GAO Jing
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.
GAO Jing
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)
GAO Jing
1) The data set is composed of global atmospheric reanalysis data jointly produced by the National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). These grid data are generated by reanalysing the global meteorological data from 1948 to present by applying observation data, forecasting models and assimilation systems. The data variables include surface, near-surface (.995 sigma layer) and multiple meteorological variables in different barospheres, such as precipitation, temperature, relative humidity, sea level pressure, geopotential height, wind field, heat flux, etc. 2) The coverage time is from 1948 to 2018, and the data from 1948 to 1957 are non-Gaussian grid data. The data cover the whole world. The spatial resolution is a 2.5° latitude by 2.5° longitude grid. The vertical resolution is a 17-layer standard pressure barosphere, with layer boundaries at 1000, 925, 850, 700, 600, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30, 20, and 10 hPa, and 28 sigma levels. Some variables are calculated for 8 layers (omega) or 12 layers (humidity), with temporal resolutions of 6 hours, daily, monthly or a long-term monthly average (from 1981 to 2010). The daily data are obtained by averaging the daily values of 0Z, 6Z, 12Z and 18Z. 3) Missing values are assigned a value of -9.99691e+36f. The data are stored in the .nc format with the file name var.time.stat.nc, and each file includes data on latitude, longitude, time, and atmospheric variables. For detailed data specifications, please visit http://www.esrl.noaa.gov/pad/data.
National Oceanic and Atmospheric Administration, National Center for Atmospheric Research
The data set is the meteorological and observational data of hulugou shrub experimental area in the upper reaches of Heihe River, including meteorological data, albedo data and evapotranspiration data under shrubs. 1. Meteorological data: Qilian station longitude: 99 ° 52 ′ E; latitude: 38 ° 15 ′ n; altitude: 3232.3m, scale meteorological data from January 1, 2012 to December 31, 2013. Observation items include: temperature, humidity, vapor pressure, net radiation, four component radiation, etc. The data are daily scale data, and the calculation period is 0:00-24:00 2. Albedo: daily surface albedo data from January 1, 2012 to July 3, 2014, including snow and non snow periods. The measuring instrument is the radiation instrument on the 10m gradient tower in hulugou watershed. Among them, the data from August 4 to October 2, 2012 was missing due to instrument circuit problems, and the rest data quality was good 3. Evapotranspiration: surface evapotranspiration data of Four Typical Shrub Communities in hulugou watershed. The observation period is from July 18 to August 5, 2014, which is the daily scale data. The data include precipitation data, evaporation and infiltration data observed by lysimeter. The data set can be used to analyze the evapotranspiration data of alpine shrubs and forests. The evapotranspiration of grassland under canopy was measured by a small lysimeter with a diameter of 25 cm and a depth of 30 cm. Two lysimeters were set up in each shrub plot, and one lysimeter was set for each shrub in transplanting experiment. The undisturbed undisturbed soil column with the same height as the barrel is placed in the inner bucket, and the outer bucket is buried in the soil. During the embedding, the outer bucket shall be 0.5-1.0 cm higher than the ground, and the outer edge of the inner barrel shall be designed with a rainproof board about 2.0 cm wide to prevent surface runoff from entering the lysimeter. Lysimeter was set up in the nearby meteorological stations to measure grassland evapotranspiration, and a small lysimeter with an inner diameter of 25 cm and a depth of 30 cm was also set up in the sample plot of Picea crassifolia forest to measure the evaporation under the forest. All lysimeters are weighed at 20:00 every day (the electronic balance has a sensing capacity of 1.0 g, which is equivalent to 0.013 mm evaporation). Wind proof treatment should be taken to ensure the accuracy of measurement. Data processing method: evapotranspiration is mainly calculated by mass conservation in lysimeter method. According to the design principle of lysimeter lysimeter, evapotranspiration is mainly determined by the quality difference in two consecutive days. Since it is weighed every day, it is calculated by water balance.
SONG Yaoxuan, LIU Zhangwen
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.
LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
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.
Ma Shupo
This dataset is derived from the Nagqu Station of Plateau Climate and Environment (31.37N, 91.90E, 4509 a.s.l), Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences. The ground is flat, with open surrounding terrain. An uneven growth of alpine steppe, with a height of 3–20 cm. The observation time of this dataset is from January 1, 2014 to December 31, 2017. The observation elements primarily included the wind speed, air temperature, air relative humidity, air pressure, downward shortwave radiation, precipitation, evaporation, latent heat flux and CO2 flux. The precipitation , evaporation and CO2 flux data are daily cumulative values, and the other variables are daily average values. The observed data are generally continuous, but some data are missing due to power supply failure, and the missing data in this dataset are marked as NAN.
HU Zeyong, GU Lianglei, SUN Fanglei, WANG Shujin
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