The Pan Third Pole is sensitive to global climate change, its warming rate is more than twice of the global rate, and it is affected by the synergy of westerlies and monsoons. How to respond to climate change will have a profound impact on regional ecological security. However, the estimation of NPP by current products is still uncertain. For this reason, this product combines multi-source remote sensing data, including AVHRR NDVI, MODIS reflectivity data, a variety of climate variables (temperature, precipitation, radiation, VPD) and a large number of field measured data, and uses machine learning algorithm to retrieve the net primary production capacity of Pan third polar ecosystem.
The data includes the county-level data of characteristic agriculture distribution in the Qinghai Tibet Plateau, which lays the foundation for the spatial distribution and development of characteristic agriculture in the Qinghai Tibet Plateau. The data are from the development plan of Tibet Plateau characteristic agricultural products base (2015-2020), Qinghai province's 13th five year plan, Sichuan Province's 13th five year plan for agricultural and rural economic development, Xinjiang Uygur Autonomous Region's 13th five year plan for targeted poverty alleviation of agricultural characteristic industries (2016-2020), Yunnan Province's overall plan for plateau characteristic agricultural modernization（ 2016-2020), implementation opinions on fostering and strengthening characteristic agricultural industries in Gansu Province to boost poverty alleviation, China National Geographic Indication product network (http://www.cgi.gov.cn/home/default/), regional layout planning of characteristic agricultural products (2013-2020). The data is the distribution of county-level characteristic agriculture, realizing the spatialization of county-level characteristic agriculture. The data can be applied to the research on the spatial distribution of characteristic agriculture and the development of characteristic agriculture in the future.
The data include the datasets of temporal changes in water level, water storage and area of the Aral sea (1911−2017), the inter-decadal change of ecosystem structure (NDVI—Normalized Difference Vegetation Index) of the Aral sea (1977−2017), and dust intensity (EDI—Enhanced Dust Index) in the Aral sea (2000−2018). Using data fusion technology in the construction of a lake basin terrain, terrain based on remote sensing monitoring and field investigation, on the basis of the analysis of the Aral sea terrain data, generalized analyses the water - area - the changes of water content, the formation of water - water - area of temporal variation data set, can clearly reflect the Aral sea water change process and the present situation, provide basic data for the Aral sea environmental change research. The NDVI was used to reflect the vegetation ecology in the receding area. Landsat satellite data, with a spatial resolution of 30 m, was used for NDVI analysis in 1977, 1987, 1997, 2007, and 2017. Based on ENVI and GIS software, remote sensing image fusion, index calculation, and water extraction were used to determine the lake surface and lakeshore line of the Aral sea. The lakeside line in the south of the Aral sea is taken as the starting point, and it extends for 3 km to the receding area. The variation characteristics of vegetation NDVI in the lakeside zone within 0-3 km are obtained to reflect the structural changes of the lakeside ecosystem. EDI was extracted from MODIS image data. This index is introduced into the dust optical density to enhance the dust information to form the enhanced dust index. Based on remote sensing monitoring, the use of EDI, established the Aral sea area-EDI index curve, the curve as the construction of the Aral sea dry lake bed dust release and meteorological factors, quantitative relationship laid the foundation of soil physical and chemical properties, in order to determine the control of sand/salt dust in the reasonable area of the lake.
LUO Yi ZHENG Xinjun HUANG Yue JILILI Abuduwaili
To describing the quantity of atmospheric water resource gaining over the TP, we provide two indexs based on ERA5 monthly reanalysis. One is called column water income (CWI), defined as the sum of vertical integrated divergence of water vapor flux and surface evaporation. It is 0.25 ×0.25 gridded with unit of kg/m2 or millimeter. Another one is Atmospheric water tower index (AWTI), total of net income of atmospheric water resource for the entire TP area, i.e., and unit is Gt.
1. The data content is the monthly groundwater level data measured between the tail of chengdina River, Kuqa Weigan River and Kashgar river of Tarim River, which is required to be the water level data of 30 wells, but the number of wells in this data reaches 44; 2. The data is translated into CSV through hobo interpretation, and the single bit time-lapse value is found through MATLAB, and then extracted and calculated through Excel screening, that is, through the interpretation of original data, through the communication Out of date and daily data, calculated monthly data; 3. Data is measured data, 2 decimal places are reserved, unit is meter, data is accurate; 4. Data can be applied to scientific research and develop groundwater level data for local health.
CHEN Yaning HAO Xingming
The spatial-temporal distribution map of topographic shadows in the upper reaches of Heihe River (2018), which is calculated based on the SRTM DEM and the solar position (http://www.esrl.noaa.gov/gmd/grad/solcalc/azel.html). The spatial resolution is 100 m and the time resolution is 15 min. The datased can be used in the fields of ecological hydrology and remote sensing research. Using the observed solar radiation at several automatic weather stations in the upper reaches of Heihe River, the accuracy of the calculation results is verified. Results show that the dataset can accurately capture the temporal and spatial changes of the topographic shadow at the stations, and the time error is within 20 minutes.
According to the characteristics of the Qinghai Tibet Plateau and the principles of scientificity, systematization, integrity, operability, measurability, conciseness and independence, the human activity intensity evaluation index system suitable for the Qinghai Tibet Plateau has been constructed, which mainly includes the main human activities such as agricultural and animal husbandry activities, industrial and mining development, urbanization development, tourism activities, major ecological engineering construction, pollutant discharge, etc, On the basis of remote sensing data, ground observation data, meteorological data and social statistical yearbook data, the positive and negative effects of human activities are quantitatively evaluated by AHP, and the intensity and change characteristics of human activities are comprehensively evaluated. The data can not only help to enhance the understanding of the role of human activities in the vegetation change in the sensitive areas of global change, but also provide theoretical basis for the sustainable development of social economy in the Qinghai Tibet Plateau, and provide scientific basis for protecting the ecological environment of the plateau and building a national ecological security barrier.
YUAN Xiu FAN Jiangwen XIN Liangjie ZHANG Haiyan
The climate model used is a fast air sea coupled model (famous) developed jointly by the British meteorological agency and the University of England. In the famous model, the horizontal resolution of the atmospheric model is 5 °× 7.5 ° and there are 11 layers in the vertical direction; the horizontal resolution of the ocean model is 2.5 °× 3.75 ° and there are 20 layers in the vertical direction. The atmosphere and the ocean are coupled once a day without flux adjustment
1) data content: social and economic data of major countries and regions in the pan third polar region, including four categories: urbanization index, economic and industrial index, population index and social index, including urbanization rate, total population, population in the largest city, population, GDP, life expectancy and other indicators in the urban agglomeration with population over 1 million; 2) data source and processing method: data source World Bank, 65 countries and regions of Pan third pole are extracted, others are not processed; 3) data quality description: some data are missing from 1960-1992; 4) data application results and prospects: it can be used for urbanization and other socio-economic analysis.
Firstly, country-wise sectorial water withdrawal data are collected from FAO AQUASTAT database, Peter Gleick’s water use data, country statistics and literatures. In order to get consistent data, all data are unified to 2015 due to inconsistent times. For the data of year 2013-2017 close to 2015, the values of these years are directly used as water withdrawals of 2015. For the others, GDP, population, temperature, precipitation, irrigation area, carbon dioxide emission, nighttime light index, coal production, urban population corresponding to the water use data of different years in each country are collected, the panel data regression model of fixed effect and random effect between industrial water, agricultural water and domestic water and these factors are established, respectively. Sectorial water withdrawals in 2015 are estimated for every country.
The observation data set of Central Asia field meteorological station includes the field observation data of temperature, precipitation, wind direction and speed, relative humidity, air pressure, radiation, soil heat flux, sunshine time and soil temperature of 10 Central Asia field meteorological stations. 10 field stations cover farmland, forest, grassland, desert, desert, wetland, plateau, mountain and other ecosystem types. The original meteorological data collected by the ground meteorological observation station is obtained after screening and review, and format conversion. Data quality is good. Central Asia has a variety of climate types, fragile ecological environment and frequent meteorological disasters. The establishment of this data set provides data support for long-term research in the fields of Central Asia ecological environment monitoring, disaster prevention and mitigation, climate change and ecological environment in Central Asia, and has been applied in the research of Central Asia ecological environment monitoring.
This data is the aridity index (AI) under the rcp4.5 scenario. AI data is the ratio of precipitation to potential evapotranspiration. This data is calculated by the average of 14 models. These 14 modes are canesm2; ccsm4; cnrm-cm5; csiro-mk3-6-0; giss-e2-r; hadgem2-cc; hadgem2-es; inmcm4; ipsl-cm5a-lr; miroc5; miroc-esm-chem; miroc-esm; mpi-esm-lr; mri-cgcm3. The spatial resolution is 2 * 2 degrees, and the temporal resolution is from January 2020 to December 2099. This data set can be used to analyze the future dry and wet change scenarios in the Great Lakes region of Central Asia, as well as the dry and wet past and pattern in other regions of the world under the future scenarios.
The Simao Basin is located in the south of the Yunnan province and the southeast of the Qinghai-Tibet plateau. It is classified as the Sanjiang tectonic domain belongs to the eastern part of Tethyan tectonic domain. The thick and continuous Early Cenozoic strata preserved in the basin is thought to be an ideal achieve to reconstruct the history of tectonic evolution in this area as well as on the southeastern plateau. The most complete Early Cenozoic strata in the Simao Basin are located in Xiaojinggu Town, Jinggu County, which mainly includes the sedimentary strata of the Mengyejing Formation, the Denghei Formation and the Mengla Formation. Previously, the chronological study of sedimentary strata in the Simao Basin is mainly concentrated in the Mengyejing Formation with potassium salt. However, scholars still have significant controversy about the deposition time of this group at this stage. Further, a complete sedimentary profile containing the middle and lower part of the Mengyejing Formation could not obtain due to vegetation cover and village construction. Through the systematic thermal demagnetization analysis of the 361.86-meter-thick borehole that encompasses the entire Mengyejing Formation, a Paleocene-Cretaceous high-resolution magnetic chronology results were obtained in this area initially.
The Qujing Basin is located in the eastern part of Yunnan Province, is a long and narrow rift basin with north-south trend in shape. The Basin preserves thick and continuous Cenozoic sediments, which can be divided into Xiaotun Formation, Caijiachong Formation and Ciying Formation from bottom to top. These thick Cenozoic sediments deposited are ideal achieves used to explore the history of local deformation process affected by the collision of the Indian-Eurasian plate as well as the evolution of the Indian monsoon in the Cenozoic. Previously, the macrochronological framework of these stratum was mainly defined by biological fossils, but high-resolution chronology with precise chronological control has not been carried out, thus limiting the understanding of tectonic evolution and climate and environmental changes since the Eocene in Yunnan. Based on the paleomagnetic test performed on the 300-meters thick boreholes drilled in the Qujing Basin as well as the U-Pb age (35.49 ± 0.78 Ma) results of volcanic tuff zircon collected from the top of the Caijiachong Formation, we then present the preliminary results of a precise chronological controlled high-resolution magnetic chronology record.
The data set integrated glacier inventory data and 426 Landsat TM/ETM+/OLI images, and adopted manual visual interpretation to extract glacial lake boundaries within a 10-km buffer from glacier terminals using ArcGIS and ENVI software, normalized difference water index maps, and Google Earth images. It was established that 26,089 and 28,953 glacial lakes in HMA, with sizes of 0.0054–5.83 km2, covered a combined area of 1692.74 ± 231.44 and 1955.94 ± 259.68 km2 in 1990 and 2018, respectively.The current glacial lake inventory provided fundamental data for water resource evaluation, assessment of glacial lake outburst floods, and glacier hydrology research in the mountain cryosphere region
This dataset includes few pollen data and high-resolution microcharcoal dataset in a ~4000 m-thick sedimentary outcrops retrieved from the Huatutou, Qaidam Basin. Pollen data from the sediment are rare, only 15 samples got enough pollen grains for pollen assemblages division and analysis, the results indicates that during the early period, the vegetation are favor a relatively warm and wet climate correlated with the global warming stages (only ice-sheet accumulated in the Antarctic), then along with the global cooling, the xerophytic taxa increased and the vegetation types became similar than before. Sedimentary microcharcoals from fine grains (e.g., mudstone, siltstone and sandstone) are one of the typical wildfire proxies commonly used in paleoclimatic studies, as they have the potential to record past variations in wildfire history related with the vegetation and precipitation. The sediment samples were grounded and treated with 10% HCl and 40% HF to remove carbonates and silica. Separation of the microcharcoals from the residue was accomplished using a 10-lm nylon sieve. Finally, they were mounted in glycerin jelly. Based on the data of outcrops in the Qaidam Basin, the evolution history of wildfire and arid environment together vegetation in the west Qaidam Basin since the early Oligocene can be reconstructed, allowing further exploring of trends, variability and mechanisms of vegetation and wildfire history.
The thick Cenozoic sediments deposited in Yunnan are ideal achieves used to explore the history of local deformation process affected by the collision of the Indian-Eurasian plate as well as the evolution of the Indian monsoon in the Cenozoic. However, due to the lack of precise age control, the early Neogene strata in Yunnan are poorly constrained. The Qujing Basin in the northern part of Yunnan Province preserves thick and continuous Cenozoic sediments, which can be divided into the Xiaotun Formation, the Caijiachong Formation and the Ciying Formation from bottom to top. Through the combination of the field outcrop profile and the borehole core, the research team obtained the stratified stratum of the Xiaotun Formation and the Caijiachong Formation with a total thickness of 251 m in the Qujing Basin. The U-Pb geochronology of the top volcanic tuff layer (35.49 ± 0.78 Ma), Caijiachong mammal fossil group (late Eocene) as well as magnetic stratigraphy collectively reveals that the age at the bottom of the Xiaotun Formation is 46.2 Ma, the top of the Caijiachong Formation should be < 36.2 Ma, and the epoch line of the two groups is 41.2 Ma. However, due to the weak influence of tectonic activities in the late Cenozoic and the small deformation of the formation, the terrain in the middle of the basin is relatively flat, resulting in the inability to obtain the top of the continuous Caijiachong Formation and the upper Ciying Formation samples. A total of 320.1 meter core covering the entire Ciying Formation and the Caijiachong Formation was obtained through the continuous drilling mission carried out in the center of the basin. Among them, the overall lithology of the core of the Ciying Formation (0-216.3 m) is dominated by gray mudstone and siltstone, and several layers of coal seams are intercalated; while the lower Caijiachong Formation (216.3-305.5 m) is grayish and grayish green mudstone. The lithology of the Xiaotun Formation (305.5-320.1 m) is mainly dominated by red mudstone.
The most complete Early Cenozoic strata in the Simao Basin are located in Xiaojinggu Town, Jinggu County, which mainly includes the sedimentary strata of the Mengyejing Formation, the Denghei Formation and the Mengla Formation. Due to the tectonic uplifting of the mountain in the late Cenozoic, the syncline structure caused the top of the Mengyejing Formation, the Denghei Formation and the Mengla Formation to be exposed to the surface. However, a complete sedimentary profile containing the middle and lower part of the Mengyejing Formation could not be obtained due to vegetation cover and village construction. The chronological study of sedimentary strata in the Simao Basin is mainly concentrated in the Mengyejing Formation with potassium salt. However, there still has significant controversy about the deposition time of this group at this stage. Recently, a continuous and complete high-resolution sequence (361.86 m in thickness) of the Mengyejing Formation was obtained through the continuous drilling. Among them, the Mengyejing Formation (0-353.3 m) is mainly a set of purple-red muddy silt and mudstone combination, while the underlying Mangang Formation (353.3-361.86 m) is a set of gray-white sandstone.
The RCM employed is the International Center for Theoretical Physics (ICTP) Regional Climate Model version 4 (RegCM4, Giorgi et al., 2012). The domain used is the Coordinated Regional Climate Downscaling Experiment (CORDEX) Phase II East Asia domain, covering whole of China and its surrounding East Asia areas. The model is run at 25 km gird spacing, with its standard configuration of 18 vertical sigma layers with a model top at 10 hPa. Configuration of the model follows Gao et al. (2016, 2017), with land cover data over China was updated as reported by Han et al. (2015) to better represent the realistic vegetation. The initial and lateral boundary conditions needed to drive RegCM4 are derived from the CMIP5 models of HadGEM2-ES (RCP4.5 pathways), and the data set include temperature and precipitation.