中国高寒区地表环境与观测网络气象数据（2018）

1)数据内容（包含的要素及意义）：高寒网21个站（藏东南站、纳木错站、珠峰站、慕士塔格站、阿里站、那曲站、双湖站、格尔木站、天山站、祁连山站、若尔盖站（西北院）、玉龙雪山站、那曲站（寒旱所）、海北站、三江源站、申扎站、贡嘎山站、若尔盖站（成都生物所）、那曲站（地理所）、拉萨站、青海湖站）2018年青藏高原气象观测数据集（气温、降水、风向风速、相对湿度、气压、辐射和蒸发）

2)数据来源及加工方法：高寒网21个站实地观测Excel格式

3)数据质量描述：站点日分辨率

4)数据应用成果及前景：在高寒网各野外站和泛第三极地区境外台站的长期观测数据基础上，建立泛第三极地区气象、水文及生态要素系列数据集；通过重点区域的强化观测与样地和样点验证，完成气象要素、湖泊水量与水质、地上植被生物量、冰川冻土变化等数据产品的反演；基于物联网技术，研制建立多站联网的气象、水文、生态数据管理平台，实现联网数据实时获取与远程控制及共享。

1) Data Content (including elements and their meanings): The 2018 Qinghai-Tibet Plateau meteorological observation dataset from 21 stations of the Alpine Network, namely Southeast Tibet Station, Nam Co Station, Mount Qomolangma Station, Muztag Ata Station, Ngari Station, Nagqu Station, Shuanghu Station, Golmud Station, Tianshan Station, Qilian Mountains Station, Zoige Station (Northwest Institute), Yulong Snow Mountain Station, Nagqu Station (Cold and Arid Regions Institute), Haibei Station, Sanjiangyuan Station, Shenzha Station, Gongga Mountain Station, Zoige Station (Chengdu Institute of Biology), Nagqu Station (Institute of Geography), Lhasa Station, Qinghai Lake Station. This dataset covers meteorological elements including air temperature, precipitation, wind direction and speed, relative humidity, atmospheric pressure, radiation and evaporation.
2) Data Source and Processing Method: Field observational data stored in Excel format from the 21 stations of the Alpine Network.
3) Data Quality Description: Daily temporal resolution per station.
4) Data Application Achievements and Prospects: Based on long-term observation data from various field stations of the Alpine Network and overseas stations in the Pan-Third Pole region, a series of datasets of meteorological, hydrological and ecological elements in the Pan-Third Pole region will be established. Through intensive observations in key areas and verification via sample plots and sampling points, inversion of data products such as meteorological elements, lake water volume and quality, above-ground vegetation biomass, and glacial and permafrost changes will be completed. Based on Internet of Things (IoT) technology, a multi-station interconnected meteorological, hydrological and ecological data management platform will be developed and built, enabling real-time acquisition, remote control and sharing of interconnected data.

搜集汇总

背景与挑战

背景概述

该数据集包含2018年中国高寒区21个观测站的气象数据，覆盖气温、降水、风向风速等关键要素，时间分辨率为日，空间分辨率为100km-1000km，以Excel格式提供。数据用于支持泛第三极地区环境变化研究，需通过申请获取并遵循特定引用规范。