黄土高原1km分辨率逐月降雨量数据集(1941-1950年)
收藏国家地球系统科学数据中心2019-05-31 更新2024-03-04 收录
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https://www.geodata.cn/data/datadetails.html?dataguid=199438549570654&docId=17139
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资源简介:
该数据为黄土高原地区逐月降雨量数据,空间分辨率为0.0083333°(1km),时间为1941.1-1950.12。数据格式为netcdf,即.nc格式。该数据集是根据CRU发布的全球0.5°气候数据集以及CNERN发布的中国区高分辨率气候数据集,通过Delta空间降尺度方案在黄土高原地区降尺度生成的。并且,使用黄土高原地区内部及外部113个气象观测点数据进行了验证,验证结果可信。为了便于存储,数据均为int16型存于nc文件中,nc格式数据可用高版本ArcMap(Multidimension Tools)读取生成栅格数据或MATLAB直接读写。该数据集包括1901-1910年逐月降雨数据,一共有120个图层,如果用ArcMap打开,在Dimension选项value处选择所需月份图层。降水单位为0.1mm。如需要提取单点、多点、子区域数据,请联系数据生成者,可提供matlab代码。
This dataset contains monthly precipitation data for the Loess Plateau, with a spatial resolution of 0.0083333° (equivalent to approximately 1 km), covering the period from January 1941 to December 1950. All data is stored in netCDF format (i.e., .nc files). This dataset was generated through spatial downscaling over the Loess Plateau using the Delta downscaling scheme, based on the global 0.5° climate dataset released by CRU and the high-resolution climate dataset for China released by CNERN. It was further validated using observations from 113 meteorological stations both within and outside the Loess Plateau, and the validation results are credible. To facilitate storage, the data is saved as the int16 data type in the .nc files. The netCDF format data can be read to generate raster data using higher versions of ArcMap (via the Multidimension Tools) or directly read and written with MATLAB. This dataset includes monthly precipitation data from 1901 to 1910, with a total of 120 layers. When opening the dataset with ArcMap, select the required monthly layer by setting the value in the Dimension option. The unit of precipitation for this dataset is 0.1 mm. If you need to extract data for single points, multiple points or sub-regions, please contact the dataset producer, and MATLAB code for data extraction will be provided.
提供机构:
西北农林科技大学水土保持研究所
创建时间:
2018-05-16
搜集汇总
数据集介绍

背景与挑战
背景概述
该数据集包含黄土高原地区1941-1950年的逐月降雨量数据,空间分辨率为1km,采用netcdf格式存储。数据通过Delta空间降尺度方法生成,并经过严格验证,适用于高精度的气候和环境研究。
以上内容由遇见数据集搜集并总结生成



