Shule River Basin is one of the three inland river basins in Hexi corridor. In recent years, with the obvious change of climate and the aggravation of human activities, the shortage of water resources and the problem of ecological environment in Shule River Basin have become increasingly prominent. It is of great significance to study the runoff change of Shule River Basin in the future climate situation for making rational water resources planning and ecological environment protection. The Shule River basin boundary is cut from "China's 1:100000 desert sand data set". Taking the 2000 TM image as the data source, it interprets, extracts, revises, and uses remote sensing and geographic information system technology to combine with the 1:100000 scale mapping requirements to carry out thematic mapping of desert, sand and gravel gobi. Data attribute table: Area (area), perimeter (perimeter), ash_ (sequence code), class (desert code), ash_id (desert code). The desert code is as follows: mobile sand 2341010, semi mobile sand 2341020, semi fixed sand 2341030, Gobi 2342000, salt alkali land 2343000. Collect and sort out the basic, meteorological, topographical and geomorphic data of Shule River Basin, and provide data support for the management of Shule River Basin.
The temperature humidity index (THI) was proposed by J.E. Oliver in 1973. Its physical meaning is the temperature after humidity correction. It considers the comprehensive impact of temperature and relative humidity on human comfort. It is an important index to measure regional climate comfort. On the basis of referring to the existing classification standards of physiological and climatic evaluation indexes, combined with the natural and geographical characteristics of the Qinghai Tibet Plateau and facing the needs of human settlements suitability evaluation in the Qinghai Tibet Plateau, the temperature and humidity index and its suitability zoning results of the Qinghai Tibet Plateau (more than 3000 meters) are developed (including unsuitable, critical suitable, general suitable, relatively suitable and highly suitable).
LI Peng, LIN Yumei
The data set covers 599 meteorological stations in five Central Asian countries, including the following elements: * daily maximum temperature, * daily minimum temperature, * observed temperature, * Precipitation (i.e. rain, melting snow), covering the following dates: 1980-1986; 1996-2005; 2010; 2014; 2015 The data comes from ghcn-d, a data set containing global land area daily observation data, which integrates climate records. The data is a direct measurement of surface temperature, without interpolation or model assumptions, and contains many long-term site records. The disadvantage is uneven space coverage. Due to changes in observation time, site location, and the type of thermometer used, the records contain many heterogeneity. For more information about this dataset, see https://www.ncdc.noaa.gov/ghcnd-data-access
The CO2 emission reduction resilience of the countries along the "Belt and Road" reflects the level of CO2 emission reduction resilience of the countries along the Belt and Road, and the higher the value of the data, the stronger the CO2 emission reduction resilience of the countries along the Belt and Road. The Emissions Database for Global Atmospheric Research (EDGAR) was used to prepare data on the total CO2 emissions of the countries along the "Belt and Road" from 2000 to 2020, taking into account the year-on-year changes. Based on the sensitivity and adaptation analysis, a comprehensive diagnosis was made based on the annual data of the total CO2 emissions of the countries along the "Belt and Road" from 2000 to 2020, and a resilience product for CO2 emission reduction was prepared. "The data set of CO2 emission reduction resilience of countries along the Belt and Road is an important reference for the analysis and comparison of the current CO2 emission reduction resilience of countries.
XU Xinliang
Coupled Model Intercomparison Project Phase 5 (CMIP5) provides a multiple climate model environment, which can be used to predict the future climate change in the key nodes in the Belts and Road to deal with the environmental and climate problems. Key nodes in the Belt and Road are taken as the study regions of this dataset. The ability of 43 climate models in CMIP5 to predict the future climate change in the study regions was assessed and the optimal models under different scenarios were selected according to the RMSE between the prediction results and real observations. This dataset is composed of the prediciton results of precipitation and near-surface air temperature between 2006 and 2065 using the optimal models in monthly temporal frequncy. The spatial resolution of the dataset has been downscaled to 10 km using statistical downscaling method. Data of each period has three bands, namely maximum near-surface air temperature, minimum near-surface air temperature and precipitation. In this data set, the unit of precipitation is kg / (m ^ 2 * s), and the unit of near-surface air temperature is K. This dataset provides data basis for solving environmental and climate problems of the key nodes in the Belts and Road.
LI Xinyan, LING Feng
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