The application of general circulation models (GCMs) can improve our understanding of climate forcing. In addition, longer climate records and a wider range of climate states can help assess the ability of the models to simulate climate differences from the present. First, we try to find a substitute index that combines the effects of temperature in different seasons and then combine it with the Beijing stalagmite layer sequence and the Qilian tree-ring sequence to carry out a large-scale temperature reconstruction of China over the past millennium. We then compare the results with the simulated temperature record based on a GCM and ECH-G for the past millennium. Based on the 31-year average, the correlation coefficient between the simulated and reconstructed temperature records was 0.61 (with P < 0.01). The asymmetric V-type low-frequency variation revealed by the combination of the substitute index and the simulation series is the main long-term model of China's millennium-scale temperature. Therefore, solar irradiance and greenhouse gases can account for most of the low-frequency variation. To preserve low-frequency information, conservative detrended methods were used to eliminate age-related growth trends in the experiment. Each tree-ring series has a negative exponential curve installed while retaining all changes. The four fields of the combined 1000-yr (1000 AD-2000 AD) reconstructed temperature records derived from stalagmite and tree-ring archives (excel table) are as follows: 1) Year 2) Annual average temperature reconstruction 3) Reconstructed temperature deviation 4) Simulated temperature deviation
This data set is based on China's second inventory data, Landsat series optical image data with a spatial resolution of 30 meters and cloud coverage of less than 10% and SRTM and other data using ArcGIS, ENVI, Google Earth and other processing software and extracting the glacial lake boundary within 10 km of the glacier boundary by artificial visual interpretation. In addition, the data set adds attributes such as glacial lake type, the mountain range, the province, and the basin to the data as well as quality checking and accuracy verification for the interpreted data. The spatial resolution is 30 meters. It consists of two parts: the glacial lake distribution area vector file and the Inventory Data set of glacial lakes in west China in 2015. It can provide reference data for glacial lake-glacier coupling, water resource utilization and management in west China and can also be used as basic data for regional climate change and cryospheric studies.
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.
The project studying the evolution pattern and development trend of the arid environment in western China was a major research component of the project Environmental and Ecological Science for West China, which was funded by the National Natural Science Foundation of China. The leading executive of the project was Academician Zhisheng An from the Institute of Earth Environment of the Chinese Academy of Sciences. The project ran from January 2002 to December 2004. The data collected by the project include the following: 1. History and variability data for arid regions in western China: 1) Chinese Loess Plateau mass accumulation rate data (3600-0 kyr BP): Fields include age and mass accumulation rate (MAR) (txt file). 2) Chinese Loess Plateau grain size and magnetic susceptibility data (3600-0 kyr BP): Fields include age, stacked mean grain size, and stacked magnetic susceptibility (txt file). 2. Sporopollen content data of different loess strata since 12 kyr BP in the Yaozhou District of Shanxi Province (excel table): The distributions of 27 species of sporopollen (0-397 cm) from 67 different layers of loess samples are included. 3. 10Be record data (table) 10Be concentration, magnetic susceptibility and bulk density data of loess with different thicknesses (79.67- 0.09 kyr BP). 4. Simulation data on the modulation of the East Asian monsoon resulting from orbital variability driven by the uplift of the Tibetan Plateau: ah0-sum.nc nc file, hh0-sum.nc nc file, jfh0-sum.nc nc file, kdh0-sum.nc nc file, lfh0-sum.nc nc file, mask.nc nc file, phis.nc nc file.
The assessment of changes in the atmospheric water cycle and the associated impacts in a key area of the Tibetan Plateau under the background of the global warming was a major component of the research project “The Environmental and Ecological Science of West China” run by the National Natural Science Foundation of China. The leading executive of the project was Xiangde Xu from the Chinese Academy of Meteorological Sciences. The project ran from January 2006 to December 2008. The following data were collected by the project of the Sino-Japan Joint Research Center of Meteorological Disaster (JICA Project): 1. Observation category, time period and number of stations 1) JICA AWS data: From January to July of 2008, 73 automatic stations (including 5 automatic stations of the Chinese Academy of Sciences) collected data in Tibet, Yunnan, Sichuan and other provinces or autonomous regions. 2) JICA GPS water vapour data: From January to October of 2008, 24 observation stations collected data in Tibet, Yunnan, Sichuan and other provinces or autonomous regions. 3) JICA encrypted observation GPS sonde data: From March to July of 2008, observations were made in Tibet, Yunnan, Sichuan and other provinces or autonomous regions (detailed observation time and location data can be found in the data catalogue). 2. Observation categories, data content 1) GPS water vapour Data content: serial number, station name (Chinese), station number, longitude, latitude, altitude, year, month, day, time, surface pressure, surface air temperature, relative humidity, total delay (m), precipitation (cm) (Measurement interval: 1 hour). 2) GPS encrypted sonde Data content: air pressure P, temperature T, relative humidity RH, V component, U component, vertical height H, dew point temperature Td, water vapour content Mr, wind direction Wd, wind speed Ws, longitude Lon, latitude Lat, radar height RdH. A value of "-999.90" means no observation data. 3) AWS Data content: station number, longitude, latitude, elevation, site level, total cloud volume, wind direction, wind speed, sea level pressure, 3-hour pressure variable, past weather 1, past weather 2, 6-hour precipitation, low cloud form, low cloud volume, low cloud height, dew point, visibility, current weather, temperature, medium cloud form, high cloud form, 24-hour temperature variable, 24-hour pressure variable. Project Science Advisers: Guoguang Zheng, Xiaofeng Xu, Xiuji Zhou, Zechun Li, Jifan Niu, Jianmin Xu, Lianshou Chen, Dahe Qin, Yihui Ding Project Superintendent: Jixin Yu Project Executives: Renhe Zhang, Xiangde Xu Data set hosting organizations: Chinese Academy of Meteorological Sciences, JICA Project Implementation Expert Group, State Key Laboratory of Severe Weather, JICA Project Implementation Office. Collaborative organizations involved in the production of the data set: Chinese Academy of Meteorological Sciences, State Key Laboratory of Severe Weather, National Satellite Meteorological Center, The Research Center for Atmospheric Sounding Techniques, National Meteorological Center, National Meteorological Information Center, National Climate Center, Sichuan Meteorological Department, Yunnan Meteorological Department, Tibet Autonomous Region Meteorological Department, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Tianjin Meteorological Department. Data set implementation organizations: Beijing Headquarters of JICA Project; JICA Project Sub-center in Sichuan Province, Yunnan Province, Tibet Autonomous Region and Institute of Tibetan Plateau Research, Chinese Academy of Sciences.
Contact SupportNorthwest Institute of Eco-Environment and Resources, CAS 0931-4967287 email@example.com
LinksNational Tibetan Plateau Data Center