The monthly precipitation data set of China's alpine mountains includes the qilian mountains (1960-2013), tianshan mountains (1954-2013) and Yangtze river source (1957-2014). The distributed hydrological model needs high-precision spatial distribution information of precipitation as input.Because of the scarcity of stations, the precipitation interpolation at stations cannot reflect the spatial distribution of precipitation in the alpine mountainous areas.Generation method of this dataset: (1) collect precipitation data of national meteorological stations and hydrological stations in various regions, and add precipitation observation data of field stations of Chinese academy of sciences above an altitude of 4000m; (2) use the temperature data of each station to correct the collected precipitation data of different precipitation types; (3) establish the relationship between precipitation data and altitude, longitude and latitude, and fit monthly to generate monthly precipitation data set of 1km scale. The interpolation year of this data is 1954-2014. The data projection method is Albers projection. The spatial interpolation precision is 1-km, and the time precision is monthly data.The results show that the interpolation precipitation is reliable. The data is stored in ASCII files. The file names of the monthly precipitation data files of tianshan mountain and Yangtze river source are in the form yyyymm.txt. YYYY is the year and MM is the month.The monthly precipitation data of qilian mountain is named as: month_10001.txt, this file is the precipitation data of January 1960, successively month_10002.txt is the precipitation of February 1960, and month_10013.txt is the precipitation data of January 1961,......Month_10648.txt represents the precipitation data for December 2013.Each ASCII file represents the grid precipitation data of the day in mm.
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.
The research area is located in the middle section o the northern slope of the Tianshan Mountains. The research area extends from Wusu in the Tacheng District of Xinjiang in the west to Mulei County in Changji Prefecture in the east. It is approximately 500 km long from east to west. The vertical vegetation gradient on the northern slope of the Tianshan Mountains can be divided into six different belts: alpine cushion vegetation belt (>3400 m), sub-alpine meadow belt (3400~2700 m), mid-mountain forest belt (2700~1720 m), forest steppe belt (1720~1300 m), semi-desert belt (1300~700 m) and typical desert belt (<700 m). Based on the characteristics of the vertical vegetation belts on the northern slope of the Tianshan Mountains, five sedimentary sections with different elevations, different vegetation belts and different sedimentary ages were selected for analysis. Five mid-late Holocene sections were measured to calculate the composite dissimilarity index of sporopollen, and the index was used to explain the sporopollen diversity. The index was then combined with integrated multiple analysis data, such as particle size, magnetic susceptibility, and ignition loss, and the changes in biodiversity and environmental characteristics since the mid-late Holocene in the area were assessed. The data include the following: 1. Sporopollen grain number data for the Daxigou section (8-110 cm, a total of 52 layers were analysed for sporopollen grain number, 3640±60 a BP to 890±60 a BP) 2. Sporopollen grain number data for the Xiaoxigou section (0-90 cm, a total of 38 layers were analysed for sporopollen grain number, 3240±60 a BP) 3. Sporopollen grain number data for the Huashuwozi section (0-106 cm, a total of 52 layers were analysed for sporopollen grain number, 2170±185 a BP to 450±155 a BP) 4. Sporopollen grain number data for the Sichanghu section (10-84 cm, a total of 19 layers were analysed for sporopollen grain number, 1000±50 a BP to 665±65 a BP) 5. Sporopollen grain number data for the Dongdaohaizi section (0-190 cm, a total of 64 layers were analysed for sporopollen grain number, 4500±310 a BP to 305±130 a BP) For detailed descriptions of the data, please refer to the following study: "Palaeo-biodiversity at the Northern Piedmont of Tianshan Mountains in Xinjiang During the Middle to Late Holocene"
Contact SupportNorthwest Institute of Eco-Environment and Resources, CAS 0931-4967287 email@example.com
LinksNational Tibetan Plateau Data Center