Based on the monthly precipitation data of 262 rain gauges, WRF and ERA5 precipitation data in the Yarlung Zangbo River basin, the daily precipitation data with a resolution of 10km from 1951 to 2020 in the Yarlung Zangbo River basin and seven sub basins are reconstructed using random forest learning algorithm. This data has been verified by the single point of the station and performs well in terms of annual and seasonal changes. And the data has been reverse evaluated by the hydrological model, which is used to drive the VIC hydrological model to simulate the runoff change of Yajiang River basin and each sub basin, and verified by the measured runoff, MODIS and glacier cataloging data. On the basis of the original first edition, this data has considered the spatial distribution characteristics of precipitation, which can better describe the precipitation characteristics in alpine regions.
SUN He
The ground-based observation dataset of aerosol optical properties over the Tibetan Plateau was obtained by continuous observation with a Cimel 318 sunphotometer, involving two stations: Qomolangma Station and Nam Co Station. These products have taken the process of cloud detection. The data cover the period from January 1, 2021 to December 31, 2021, and the time resolution is daily. The sunphotometer has eight observation channels from visible light to near infrared, and the central wavelengths are 340, 380, 440, 500, 670, 870, 940 and 1120 nm, respectively. The field of view angle of the instrument is 1.2°, and the sun tracking accuracy is 0.1°. Six bands of aerosol optical thickness can be obtained from direct solar radiation, and the accuracy is estimated to be 0.01-0.02. Finally, AERONET unified inversion algorithm was used to obtain the aerosol optical thickness, Ångström index, aerosol particle size distribution, single scattering albedo, phase function, complex refraction index and asymmetry factor.
CONG Zhiyuan
CMIP6 is the sixth climate model comparison plan organized by the World Climate Research Program (WCRP). Original data from https://www.wcrp-climate.org/wgcm-cmip/wgcm-cmip6 。 This dataset contains four SSP scenarios of Scenario MIP in CMIP6. (1) SSP126: Upgrade of RCP2.6 scenario based on SSP1 (low forcing scenario) (radiation forcing will reach 2.6W/m2 in 2100). (2) SSP245: Upgrade of RCP4.5 scenario based on SSP2 (moderate forcing scenario) (radiation forcing will reach 4.5 W/m2 in 2100). (3) SSP370: New RCP7.0 emission path based on SSP3 (medium forcing scenario) (radiation forcing will reach 7.0 W/m2 in 2100). (4) SSP585: Upgrade the RCP8.5 scenario based on SSP5 (high forcing scenario) (SSP585 is the only SSP scenario that can make the radiation forcing reach 8.5 W/m2 in 2100). Using GRU data to correct the post-processing deviation of the original CMIP data, the post-processing data set of monthly precipitation (pr) and temperature (tas) estimates from 2046-2065 was obtained, with a reference period of 1985-2014.
YE Aizhong
The triple pole aerosol type data product is an aerosol type result obtained through a series of data pre-processing, quality control, statistical analysis and comparative analysis processes by comprehensively using MEERA 2 assimilation data and active satellite CALIPSO products. The key of the aerosol type fusion algorithm is to judge the aerosol type of CALIPSO. During the data fusion of aerosol type, the final aerosol type data (12 types in total) and quality control results in the three polar regions are obtained according to the types and quality control of CALIPSO aerosol types and referring to MERRA 2 aerosol types. The data product fully considers the vertical and spatial distribution of aerosols, and has a high spatial resolution (0.625 ° × 0.5 °) and time resolution (month).
ZHAO Chuanfeng
The water resources simulation data of Southeast Asian countries and the Lancang Mekong River Basin (1980-2019) is the result of using the meteorological data output from the WRF model as the driving data and simulation through the ways model. The data includes evapotranspiration, surface runoff, underground runoff, total runoff, groundwater, infiltration and soil moisture data of Southeast Asia land area from 1980 to 2019. The temporal resolution is daily and the spatial resolution is 3km. The data is generally good, but due to the limitations of the model, there are certain errors in the simulation results of a few variables. It is not recommended to use the research with high requirements for data accuracy. The data can reflect the situation of water resources in Southeast Asia to a certain extent, and provide data support for relevant research.
LIU Junguo
We developed a 1-km resolution long-term soil moisture dataset of China derived through machine learning trained with in-situ measurements of 1,648 stations, named as SMCI1.0 (Soil moisture of China based on In-situ data, Li et al, 2022). SMCI1.0 provides 10-layer soil moisture with 10 cm intervals up to 100 cm deep at daily resolution over the period 2000-2020. Random Forest is used to predict soil moisture using ERA5-land time series, leaf area index, land cover type, topography and soil properties as covariates. Using in-situ soil moisture as the benchmark (The data comes from China Meteorological Administration), two independent experiments are conducted to investigate the estimation accuracy of the SMCI1.0: year-to-year experiment (ubRMSE ranges from 0.041-0.052 and R ranges from 0.883-0.919) and station-to-station experiment (ubRMSE ranges from 0.045-0.051 and R ranges from 0.866-0.893). As SMCI1.0 is based on in-situ data, it can be useful complements of existing model-based and satellite-based datasets for various hydrological, meteorological, and ecological analyses and modeling, especially for those applications requiring high resolution SM maps. Please read the readme file for more details. We provided two versions with different resolution, i.e., 30 arc seconds (~1km) and 0.1 degree (~9km).
SHANGGUAN Wei, LI Qingliang , SHI Gaosong
This data is the plant diversity and distribution data of the chnab005 grid on the Qinghai Tibet Plateau, including the Chinese name, Latin name, latitude and longitude, altitude, collection number, number of molecular materials, number of specimens, administrative division, small place, collector, collection time and creator of the plants in this grid. This data is obtained from e-Science website（ http://ekk.kib.ac.cn/web/index/#/ ）And partially complete the identification. This data has covered the list of plants in this flora and the specific distribution information. This data can be used not only to study the floristic nature of this region, but also to explore the horizontal and vertical gradient pattern of plants in this region. What is different from last year is that the grid with the most scientific research data this year has changed, which may be affected by the epidemic or the environment.
DENG Tao
Precipitation over the Tibetan Plateau (TP) known as Asia's water tower plays a critical role in regional water and energy cycles, largely affecting water availability for downstream countries. Rain gauges are indispensable in precipitation measurement, but are quite limited in the TP that features complex terrain and the harsh environment. Satellite and reanalysis precipitation products can provide complementary information for ground-based measurements, particularly over large poorly gauged areas. Here we optimally merged gauge, satellite, and reanalysis data by determining weights of various data sources using artificial neural networks (ANNs) and environmental variables including elevation, surface pressure, and wind speed. A Multi-Source Precipitation (MSP) data set was generated at a daily timescale and a spatial resolution of 0.1° across the TP for the 1998‒2017 period. The correlation coefficient (CC) of daily precipitation between the MSP and gauge observations was highest (0.74) and the root mean squared error was the second lowest compared with four other satellite products, indicating the quality of the MSP and the effectiveness of the data merging approach. We further evaluated the hydrological utility of different precipitation products using a distributed hydrological model for the poorly gauged headwaters of the Yangtze and Yellow rivers in the TP. The MSP achieved the best Nash-Sutcliffe efficiency coefficient (over 0.8) and CC (over 0.9) for daily streamflow simulations during 2004‒2014. In addition, the MSP performed best over the ungauged western TP based on multiple collocation evaluation. The merging method could be applicable to other data-scarce regions globally to provide high quality precipitation data for hydrological research. The latitude and longitude of the left bottom corner across the TP, the number of rows and columns, and grid cells information are all included in each ASCII file.
HONG Zhongkun , LONG Di
(1) The data content is the environmental monitoring data of high slope of Zala hydropower station, including the environmental data of automatic monitoring of high slope of Zala hydropower station, which has certain guiding significance for the stability of slope of Zala hydropower station and can provide data support for disaster prevention and reduction of Zala hydropower station; (2) The data comes from the automatic transmission of automatic monitoring equipment, and is automatically interpreted and processed by the software of monitoring and early warning platform to finally generate the data in Excel; (3) The data transmission is stable and the quality is high, which can provide a basis for the slope stability of zhala hydropower station; (4) The data can reflect the environmental changes of the high slope of zhala hydropower station, and has a wide application prospect.
XU Kunzhen
Photosynthetically active radiation (PAR) is fundamental physiological variable driving the process of material and energy exchange, and is indispensable for researches in ecological and agricultural fields. In this study, we produced a 35-year (1984-2018) high-resolution (3 h, 10 km) global grided PAR dataset with an effective physical-based PAR model. The main inputs were cloud optical depth from the latest International Satellite Cloud Climatology Project (ISCCP) H-series cloud products, the routine variables (water vapor, surface pressure and ozone) from the ERA5 reanalysis data, aerosol from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) products and albedo from Moderate Resolution Imaging Spectroradiometer (MODIS) product after 2000 and CLARRA-2 product before 2000. The grided PAR products were evaluated against surface observations measured at seven experimental stations of the SURFace RADiation budget network (SURFRAD), 42 experimental stations of the National Ecological Observatory Network (NEON), and 38 experimental stations of the Chinese Ecosystem Research Network (CERN). The instantaneous PAR was validated at the SURFRAD and NEON, and the mean bias errors (MBEs) and root mean square errors (RMSEs) are 5.6 W m-2 and 44.3 W m-2, and 5.9 W m-2 and 45.5 W m-2, respectively, and correlation coefficients (R) are both 0.94 at 10 km scale. When averaged to 30 km, the errors were obviously reduced with RMSEs decreasing to 36.3 W m-2 and 36.3 W m-2 and R both increasing to 0.96. The daily PAR was validated at the SURFRAD, NEON and CERN, and the RMSEs were 13.2 W m-2, 13.1 W m-2 and 19.6 W m-2, respectively at 10 km scale. The RMSEs were slightly reduced to 11.2 W m-2, 11.6 W m-2, and 18.6 W m-2 when upscaled to 30 km. Comparison with the other well-known global satellite-based PAR product of the Earth's Radiant Energy System (CERES) reveals that our PAR product was a more accurate dataset with higher resolution than the CRERS. Our grided PAR dataset would contribute to the ecological simulation and food yield assessment in the future.
TANG Wenjun
1) Data content: the average zonal wind speed of 200 hPa and 850 hPa (reflecting the high and low-level westerly wind) and meridional wind speed of 850 hPa (reflecting the monsoon circulation) during the past millennium; 2) Data source: monthly data of the third phase of the international paleoclimate simulation and comparison program, processing method: multi-mode equal weight arithmetic average, climate average, 3) data application: used for the study of paleoclimate change and dynamic mechanism.
YAN Qing, JIANG Nanxuan, WANG Huijun
This data set includes the PM2.5 mass concentration of atmospheric aerosol particles at Southeast Tibet station, Ali station, mostag station, Everest station and Namuco station (unit: mm) μ g/m3）。 Aerosol PM2.5 fine particles refer to particles with aerodynamic equivalent diameter less than or equal to 2.5 microns in the ambient air. It can be suspended in the air for a long time, which has an important impact on air quality and visibility. The higher its concentration in the air, the more serious the air pollution. The concentration characteristic data of PM2.5 is output at the frequency of obtaining a set of data every 5 minutes, which can realize the analysis of aerosol mass concentration at different time scales such as hour, day and night, season and interannual, which provides the analysis of changes and influencing factors of aerosol mass concentration at different locations in the Qinghai Tibet plateau at different time scales, as well as the evaluation of local air quality, It provides important data support. This data is an update of the published data set of PM2.5 concentration of aerosol particles at different stations on the Qinghai Tibet Plateau (2018 and 2019).
WU Guangjian
The data set includes the start time (year, month), location (longitude and latitude), duration (month), drought intensity and vulnerability data of vegetation response to drought in Central Asia from 1982 to 2015, with a spatial resolution of 1 / 12 °. The drought events were identified by the standardized precipitation evapotranspiration index at the time scale of 12 months (spei12) < - 1.0. The specific algorithm of drought characteristics and vegetation vulnerability is detailed in the citation. The dataset has been applied in the study of vegetation vulnerability to drought in Central Asia, and has application prospects in the research fields of spatial-temporal characteristics of drought events, drought-vegetation interaction mechanism, drought risk assessment and so on.
DENG Haoyu
Vulnerability refers to a property of the system that is susceptible to changes in structure and function due to the system's sensitivity to internal and external disturbances and its lack of ability to respond, that is, the ability of the region to cope with disasters to reduce losses when heat waves occur. This dataset is based on the pan-third pole regional road network data, GDP data, medical facility spatial distribution data, vegetation coverage data, and water distribution data as basic data,and takes 2015 as the base year. The Euclidean Metric calculation method is adopted to determine the spatial distribution of road networks, water and medical facilities in the area. The distance from roads, water bodies, medical facilities, GDP, and vegetation coverage are used as evaluation indicators. The equal-weight overlapping addition is used to evaluate the vulnerability of heat waves at each node. In order to eliminate the impact of unit differences, the data of each index layer is normalized before the evaluation.Finally, the vulnerability level of each node is divided by the natural Jenks method.
GE Yong, YANG Fei, LIU Qingsheng
The data comes from the National Centers for environmental information (NCEI), which provides meteorological records of all stations in the world since they were built, including temperature, wind speed, dew point, precipitation and other information. There are four recorded stations near Dhaka city. The monitoring data of meteorological stations have the characteristics of high precision. Firstly, the monitoring data of stations in the world are downloaded from NCEI, and then four stations in Dhaka city are selected according to longitude and latitude. The data level records the daily meteorological station monitoring data from January 1, 2016 to December 31, 2019.
GE Yong, YANG Fei
The data source of this data set is the first, second and third bands of the atmospheric top layer reflectance data of Landsat-5 satellite. Landsat satellite is a sun synchronous satellite. The satellite moves from north to south. The earth rotates from west to East. The satellite circles the earth 14.5 times a day. Each circle moves 159km to the west of the equator. It covers every 16 days repeatedly. This data set mainly covers Dhaka City, Bangladesh. Based on the top layer reflectance data of Landsat-5 atmosphere in 2010, this data is downloaded from the geospatial data cloud platform, and uses ArcGIS to synthesize the data band. Finally, the 30 meter resolution multispectral remote sensing image data of Dhaka area 2010 in TIFF format is obtained.
GE Yong, YANG Fei
The basic data source of this dataset is from the website of the National Oceanic and Atmospheric Administration (NOAA). NOAA satellites are meteorological observation satellites. Provide meteorological environment information including temperature, precipitation, dew point, wind speed, etc. This dataset mainly covers key nodes in the Southeast Asia and Middle East regions. The main steps of data processing are as follows: firstly, the daily maximum temperature data is obtained by screening from a large number of basic meteorological data; the daily maximum temperature relative humidity relationship is integrated, and the daily relative humidity calculation is completed based on the dew point temperature data of the weather station. This data set provides basic information and a strong reference for evaluating the high temperature weather process in key node areas.
GE Yong, LIU Qingsheng
The data sources of this dataset are the first to seventh bands of the top-of-atmosphere (TOA) reflectance data of Landsat-5 and landsat-8 satellites. Landsat satellites are sun synchronous satellite with a repetition period of 16 days. Based on the data of Landsat-5 and landsat-8 TOA reflectance from 2000 to 2016, this dataset mainly covers the pan third polar key points region in Southeast Asia and the Middle East. It uses Google Earth engine cloud computing platform to clip the data of the study area, and finally gets the 30-meter resolution multi spectral remote sensing image data of the pan third polar region 2000-2016 in TIFF format.
GE Yong, LING Feng, ZHANG Yihang
The data sources of this dataset are the first to seventh bands of the top-of-atmosphere (TOA) reflectance data of Landsat-5 and landsat-8 satellites. Landsat satellites are sun synchronous satellite with a repetition period of 16 days. Based on the data of Landsat-5 and landsat-8 TOA reflectance from 2000 to 2016, this dataset mainly covers the pan third polar key points region in Southeast Asia and the Middle East. It uses Google Earth engine cloud computing platform to clip the data of the study area, and finally gets the 30-meter resolution multi spectral remote sensing image data of the pan third polar region 2000-2016 in TIFF format.
GE Yong, LING Feng, ZHANG Yihang
The data sources of this dataset are the first to seventh bands of the top-of-atmosphere (TOA) reflectance data of Landsat-5 and landsat-8 satellites. Landsat satellites are sun synchronous satellite with a repetition period of 16 days. Based on the data of Landsat-5 and landsat-8 TOA reflectance from 2000 to 2016, this dataset mainly covers the pan third polar key points region in Southeast Asia and the Middle East. It uses Google Earth engine cloud computing platform to clip the data of the study area, and finally gets the 30-meter resolution multi spectral remote sensing image data of the pan third polar region 2000-2016 in TIFF format.
GE Yong, LING Feng, ZHANG Yihang
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