Spatial-Temporal Precipitation Dataset in Hengduan Mountains (1998-2012)
ZHANG Tao1LI Baolin1HE Yuanqing2DU Jiankuo2NIU Hewen2XIN Huijuan22
1 Institute of Geographic Sciences and Natural Resources Research CAS，Beijing 100101，China2 Cold and Arid Region Environment and Engineering Research Institute CAS，Lanzhou 730000，China
DOI:10.3974/geodb.2016.06.06.V1
Published:Sep. 2016
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Key Words：
Hengduan Mountains,precipitation,TRMM satellite,Spatial-Temporal,Journal of Natural Resources
Abstract：
Based on the monthly records from 38 metrological stations from 1998-2012 in Hengduan Mountains and the monthly TRMM 3B43 rainfall estimation data, the spatial-temporal precipitation dataset in Hengduan Mountains (1998-2012) was calculated using the ISODATA clustering and maximum likelihood method. The dataset is consisted of the following group of data files: (1) the geolocation of the study area and the metrological stations; (2) 4 groups of data files which are in 0.25。x 0.25。spatial resolution and yearly, seasonally and monsoon season in temporal scales. They are: (2-1) yearly precipitation grid data from 1998-2012; (2-2）mean annual precipitation grid data during 1998-2012; (2-3) mean annual precipitation grid data based on the records from the 38 metrological stations; (2-4) mean annual precipitation grid data on change trends and their significances. The dataset is archived in the grid and .shp data format with the compressed data size of 773KB. The analysis paper was published in the Journal of Natural Resources, No. 2, Vol. 30, 2015.
Foundation Item：
Ministry of Science and Technology of China (2015CB954101, 2015CB954103, 2012BAH33B01)
Data Citation：
ZHANG Tao, LI Baolin, HE Yuanqing, DU Jiankuo, NIU Hewen, XIN Huijuan2. Spatial-Temporal Precipitation Dataset in Hengduan Mountains (1998-2012)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2016. https://doi.org/10.3974/geodb.2016.06.06.V1.
Zhang, T., Li, B. L., Yuan, Y. C., et al. Spatio-temperalprecipitationdataset in Hengduan Mountains (1998–2012) [J]. Journal of Global Change Data & Discovery, 2019, 3(2): 168–174. DOI: 10.3974/geodp.2019.02.07.
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SpaTempPrecipHengduanMt1998_2012.rar |
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