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
(1) Data content: the annual mean Northern Annular mode index and the Northern Annular mode index from 1500 to 2000; (2) Data source and processing method: this data is independently produced by the author. It is based on PAGES2k data set and reconstructed by machine learning model (random forest, extreme tree, Light GBM and catboost). (3) Data quality description: the data set has high consistency with multiple instrumental data during the observed period, and the reconstruction is better. The data can be used to study the change and mechanism of the main atmospheric circulation in the northern and southern hemispheres on multiple time scales (interannual, interdecadal and multidecadal).
YANG Jiao
The Qinghai-Tibet Engineering Corridor runs from Golmud to Lhasa. It passes through the core region of the Qinghai-Tibet Plateau and is an important passage connecting the interior and Tibet. As the primary parameter in the surface energy balance, the land surface temperature represents the degree of energy and water exchange between the earth and the atmosphere, and is widely used in the research of climatology, hydrology and ecology. The annual average surface land temperature is obtained by using the four day and night observations of Aqua and Terra. Therefore, the 8-day land surface temperature synthesis products MOD11A2 and MYD11A2 with a resolution of 1km were downloaded first, and then the data were batch projected by MRT (MODIS Reprojection Tool). Finally, the annual average MODIS land surface temperature data after 2010 was calculated by IDL.
NIU Fujun
According to the data of three future scenarios of CMIP5 (RCP2.6、RCP4.5、RCP8.5), the spatial variation characteristics and temporal variation trend of the global mean annual air temperature from 2006 to 2100 are analyzed. Under rcp2.6 scenario, the mean annual air temperature shows an increasing trend, with the growth rate ranging from 0.0 ° c/decade to 0.2 ° c/decade (P<0.05), the growth in high latitude regions is faster, ranging from 0.1 ° c/decade to 0.2 ° C / decade. Based on the spatial and temporal characteristics of the mean annual air temperature in the northern hemisphere in the 21st century, under different scenarios, the mean annual air temperature shows a warming trend, and the high latitudes show a more sensitive and rapid growth.
NIU Fujun
The Human Development Index (HDI) was developed by the United Nations Development Programme (UNDP) in the Human Development Report 1990 to measure the level of economic and social development of the United Nations member countries. The HDI is a composite indicator based on three basic variables: life expectancy, educational attainment and quality of life, and is calculated according to a certain methodology. "The One Belt One Road (OBOR) human development resilience dataset is a comprehensive indicator of human development resilience in each country. "The human development resilience dataset for countries along the Belt and Road is a comprehensive diagnosis based on sensitivity and adaptability analysis using year-by-year data of the Human Development Index for countries along the Belt and Road from 2000 to 2020. The Human Development Resilience Indicator (HDRI) data was prepared based on sensitivity and adaptation analysis. Please refer to the documentation for the methodology of preparing the dataset. "The Human Development Resilience Dataset for countries along the Belt and Road is an important reference for analysing and comparing the current state of human development resilience in each country.
XU Xinliang
To understand the potential impact of projected climate changes on the vulnerable agriculture in Central Asia (CA) in the future, six agroclimatic indicators are calculated based on the 9km-resolution dynamical downscaled results of three different global climate models and a high-resolution projection dataset of agroclimatic indicators over CA is produced. These indicators are growing season length (GSL, days), biologically effective degree days (BEDD, ℃), frost days (FD, days), summer days (SU, days), warm spell duration index (WSDI, days), and tropical nights (TR, days). The periods are 1986-2005 and 2031-2050. The spatial resolution is 0.1°. As all the indicators except WSDI are defined with absolute temperature thresholds and particularly sensitive to the systematics biases in the model data, the quantile mapping (QM) method is applied to correct the simulated temperature. Results show the QM method largely reduces the biases in all the indicators. GSL, SU, WSDI, and TR will significantly increase over CA and FD will decrease. However, changes in BEDD are spatially heterogeneous, with the increases in northern CA and the mountainous areas and decreases in the southern and middle part of the plain areas. This dataset can be applied for assessing the future risks in the local agriculture for climate changes and will be beneficial to adaption and mitigation actions for food security in this region.
QIU Yuan QIU Yuan
Rainfall erosivity is one of the important basic data to quantify soil erosion in the Tibet Plateau. High precision rainfall erosivity data is the key to understand the current situation of soil and water loss in theTibet Plateau and formulate soil and water conservation measures. Meanwhile, it can provide a powerful reference for the prevention and control of geological disasters in the Tibet Plateau. Based on the 1-min dense precipitation observations and the grid precipitation product, a new annual rainfall erosivity dataset in Tibet Plateau from 1950 to 2020 is constructed through the steps of correction, reconstruction and validation. This dataset is the rainfall erosivity data set with the highest accuracy and the longest time series in the Tibet Plateau.
CHEN Yueli
The Third Pole 1:100,000 settlements distribution data set：Settlements（Tibet_Cities)、Capitals（Tibet_Capitals）、Cities up to 75K（Tibet_Cities_up_to_75K）vector space data set and its attribute name：Cities Name(ENG_NAME)、 urban population（CITY_POP) The data comes from the 1:100,000 ADC_WorldMap global data set，The data through topology, warehousing and other data quality inspection，Data through the topology, into the library，It's comprehensive, up-to-date and seamless geodigital data. The world map coordinate system is latitude and longitude, D_WGS_1984 datum surface
ADC WorldMap
The 1:1,000,000 Antarctic settlements data set includes vector spatial data of Antarctic settlements and its related attributes：City name (ENG_NAME), city population (CNTEY_NAME), (CNTRY_CODE), etc. The data comes from the 1:100,000 ADC_WorldMap global data set，The data through topology, warehousing and other data quality inspection，Data through the topology, into the library，It's comprehensive, up-to-date and seamless geodigital data. The world map coordinate system is latitude and longitude, WGS84 datum surface，Antarctic specific projection parameters（South_Pole_Stereographic）.
ADC WorldMap
The data set of 1:100,000 settlements in the Arctic includes all settlements in the North Pole (Arctic_Resident), capital settlements (Arctic_Capitals), Cities_up_to_75K settlements and other vector spatial data and related attribute data: urban name (ENG_NAME), CITY_POP and other properties. The data comes from the 1:100,000 ADC_WorldMap global data set，The data through topology, warehousing and other data quality inspection，It's most comprehensive, current and seamless geographic digital data for the whole earth. The world map coordinate system is latitude and longitude, WGS84 datum surface，Arctic specific projection parameters（North_Pole_Stereographic）.
ADC WorldMap
Qinghai Lake is the largest inland salt water lake in China, which is located in the northeast of Qinghai Tibet Plateau. Its unique natural ecological environment and biodiversity are of great significance in the western development and ecological construction. The data is the distribution data of residential areas in the Qinghai Lake Basin, including the distribution of cities, counties, towns and villages in the Qaidam River Basin. The data mainly has two attribute fields: Code (residential area code) and name (residential area name). Collect and sort out the basic, meteorological, topographical and geomorphological data of Qinghai Lake Basin, and provide data support for ecological management of Qinghai Lake Basin.
National Basic Geographic Information Center
The data is the distribution data of the settlements in the Tarim River Basin, mainly including the distribution of cities, counties, towns, and villages in the Tarim River Basin. The data mainly has two attribute fields: Code (settlement code), Name (settlement name)
National Basic Geographic Information Center
The data is the resident site distribution dataset of the north slope of Tianshan River Basin, including the hierarchical distribution of cities, counties, towns and villages at the north slope of Tianshan River Basin. The data mainly has two attribute fields: Code (residential area code) and Name (residential area name).
National Basic Geographic Information Center
The data is the distribution data of residential areas in the chaidamu river basin, including the distribution of cities, counties, towns and villages in the chaidamu river basin. The data mainly has two attribute fields: Code (residential area Code) and Name (residential area Name).
National Basic Geographic Information Center
This data mainly includes the distribution of city, county, township and village level residential areas in the Heihe River Basin, and the data base year is 2009. The data is based on the existing data of residential areas in Heihe River Basin, the latest Google electronic map and the atlas of Gansu Province. There are two main attributes of the data, i.e. residential area classification and total name. The residential area classification is classified according to level 1 - City, level 2 - County, level 3 - Township and level 4 - village.
National Basic Geographic Information Center
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