科技重大计划进展

中国积雪特性及分布调查

  • 王建 ,
  • 车涛 ,
  • 李震 ,
  • 李弘毅 ,
  • 郝晓华 ,
  • 郑照军 ,
  • 肖鹏峰 ,
  • 李晓峰 ,
  • 黄晓东 ,
  • 钟歆玥 ,
  • 戴礼云 ,
  • 李红星 ,
  • 柯长青 ,
  • 李兰海
展开
  • 1.中国科学院西北生态环境资源研究院,甘肃 兰州 730000
    2. 中国科学院遥感与数字地球研究所,北京 100101
    3.国家卫星气象中心,北京 100081
    4. 南京大学,江苏 南京 210093
    5.中国科学院东北地理与农业生态研究所,吉林 长春 130102
    6.兰州大学,甘肃 兰州 730000
    7.中国科学院新疆生态与地理研究所,新疆 乌鲁木齐 830011
    8.江苏省地理信息资源开发与利用协同创新中心, 210097
    9. 中国科学院青藏高原地球科学卓越创新中心, 北京 100101
作者简介:王建(1963-),男,安徽休宁人,研究员,主要从事积雪遥感和融雪径流模拟模型研究.E-mail:wjian@lzb.ac.cn

收稿日期: 2017-10-25

  修回日期: 2017-12-11

  网络出版日期: 2018-03-06

基金资助

科技部国家科技基础资源调查专项“中国积雪特性及分布调查”(编号:2017FY100500)资助

版权

, 2018,

Investigation on Snow Characteristics and Their Distribution in China

  • Jian Wang ,
  • Tao Che ,
  • Zhen Li ,
  • Hongyi Li ,
  • Xiaohua Hao ,
  • Zhaojun Zheng ,
  • Pengfeng Xiao ,
  • Xiaofeng Li ,
  • Xiaodong Huang ,
  • Xinyue Zhong ,
  • Liyun Dai ,
  • Hongxing Li ,
  • Changqing Ke ,
  • Lanhai Li
Expand
  • 1.Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences,Lanzhou 730000, China
    2.Institute of Remote Sensing and Digital Earth,Beijing 100101, China
    3.National Satellite Meteorological Centre,Beijing 100081, China
    4.Nanjing University,Nanjing 210093, China
    5.Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences,Changchun 130102, China
    6.Lanzhou University,Lanzhou 730000,China
    7.Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences,Urumchi 830011, China
    8.Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210097, China
    9. Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing 100101, China
First author:Wang Jian(1963-),male,Xiuning County,Anhui Province,Professor. Research areas include remote sensing of snow and modeling of snowmelt runoff.E-mail:wjian@lzb.ac.cn

Received date: 2017-10-25

  Revised date: 2017-12-11

  Online published: 2018-03-06

Supported by

Project supported by the Science & Technology Basic Resources Investigation Program of China “Investigation on snow characteristics and their distribution in China” (No.2017FY100500)

Copyright

地球科学进展 编辑部, 2018,

摘要

介绍了“中国积雪特性及分布调查”的背景、科学目标、调查内容及方案。调查的总体目标是建立中国全面而系统的积雪特性数据库,服务于气候变化、水资源调查和积雪灾害的数据需求。调查将从历史资料整编、典型积雪区积雪特性地面调查以及积雪遥感调查等方面展开。历史资料的整编包括收集气象站以及各单位已开展的积雪特性观测资料,并按照一定的规范进行整编;典型积雪区地面调查主要是在东北地区、新疆地区和青藏高原开展不同季节的积雪特性调查,以点、线、面3种方式开展,观测内容包括雪深、雪密度、雪水当量、积雪形态、表层硬度、液态水含量、雪粒径、雪层温度、雪土界面温度、介电常数以及积雪的若干化学特性;遥感积雪调查将利用地面调查的积雪特性信息改进已有的积雪参数反演算法,建立中国长序列的积雪面积、反照率以及雪水当量数据集。最终,利用地面和遥感调查所获取的积雪特性及分布数据集对中国进行积雪类型划分,并生产系列积雪特性及专题分布图。

本文引用格式

王建 , 车涛 , 李震 , 李弘毅 , 郝晓华 , 郑照军 , 肖鹏峰 , 李晓峰 , 黄晓东 , 钟歆玥 , 戴礼云 , 李红星 , 柯长青 , 李兰海 . 中国积雪特性及分布调查[J]. 地球科学进展, 2018 , 33(1) : 12 -15 . DOI: 10.11867/j.issn.1001-8166.2018.01.0012

Abstract

The background, scientific objective, investigation contents and scheme of project “Investigation on snow characteristics and their distribution in China” was introduced in this paper. The general objective of the investigation is to build comprehensive and systematic database of snow characteristics in China, at the service of providing data for the climate change, water resource and snow disaster studies. The investigation will be performed on the three fields including the compilation of historical data, in situ measurement of snow characteristics in the typical regions, and investigation of snow characteristics using remote sensing methods. For the compilation of historical data, the historical snow data from the meteorological stations and research institutes will be firstly collected, and then they will be compiled based on a standard rule. In situ observation will be performed at point, line and area-scale on the typical regions which include Northeast region, Xinjiang Degion, and Qinghai-Tibet Plateau. The observation content will contain snow depth, snow density, snow water equivalent, snow particle shape, hardness of snowpack surface, liquid water content, grain size, snow temperature, snow/soil temperature, dielectric constant, and some chemical parameters. These snow characteristics are the priority information used for the modification of retrieval algorithm on snow parameters. Remote sensing methods will be used to build long-time series of snow cover, snow albedo and snow water equivalent datasets based on these modified algorithms. Finally, the snow characteristics from both in situ and remote sensing investigation will be used to classify snow types in China, and produce distribution maps of snow characteristic and other thematic maps.

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