{"id":"7a11f968-ef31-4b30-b7bf-b8c7471997c7","title":"北极雪水当量格网数据集（1979-2019）","title_en":"Arctic Snow Water Equivalent Grid Dataset (1979-2019)","serial":"","user_limit":"为尊重知识产权、保障数据作者的权益、扩展数据中心的服务、评估数据的应用潜力，请数据使用者在使用数据所产生的研究成果中（包括公开发表的论文、论著、数据产品和未公开发表的研究报告、数据产品等成果），明确注明数据来源和数据作者。对于转载（二次或多次发布）的数据，作者还须注明原始数据来源。","instructions":"文件命名: 雪水当量数据以NetCDF格式存储，文件的名称为“Arctic_SWE_yyyy.nc”，其中yyyy代表年，比如Arctic_SWE_1979.nc就代表这个netcdf文件描述的1979年逐日的格网雪水当量数据集。\n数据读取方式：该数据集可使用Panoply或PyNcView软件进行查看，可使用Linux CDO命令行工具，或Python的netCDF4库和xarray库进行相关的处理运算。","description":"雪水当量（Snow water equivalent，SWE）是地表水文模型和气候模型的重要参数。本数据基于机器学习的岭回归算法融合了多种现有的雪水当量数据产品，形成了一套时间序列连续且精度较高的雪水当量数据产品。数据的空间范围为泛北极地区（北纬45°至北纬90°），数据时间序列为1979-2019年。该数据集有望为水文模型和气候模型提供更为精确的雪水当量数据，为冰冻圈变化及全球变化提供数据支撑。","doi":"10.11888/Snow.tpdc.271556","projection":"North_Pole_Stereographic","language":"zh","share_type":"online","east":180.0,"west":-180.0,"south":45.0,"north":90.0,"scale":null,"crs":null,"filesize":109286.25,"share_policy":"a","ts_created":"2021-06-25T09:23:18.283171+08:00","doi_type":"拥有自主知识产权","ts_updated":"2021-11-02T09:37:04.094116+08:00","time_description":"","datas_group":3,"time_description_en":"","data_format":null,"project":[10],"specials":[],"cite":null,"review_status":5,"review_invite":[{"user_name":"高杨","username":"yanggao@itpcas.ac.cn","email":"yanggao@itpcas.ac.cn","is_cancel_expert":false}],"review_editor":{"id":42421,"last_login":"2022-04-08T15:16:51.670544+08:00","username":"任慧霞","email":"510727846@qq.com","is_active":true,"is_staff":true,"user_name":"任慧霞"},"data_sources":null,"temporal_resolution":"Daily","spatial_resolution":"1km - 10km","license":"Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","fund":[394,396],"subtopics":{"metadata":"7a11f968-ef31-4b30-b7bf-b8c7471997c7","three_pole":null,"third_pole":null},"username":"吴玉伟","review_time":null,"protected_duration":0,"protected_describe":null,"is_important":false,"hit_count":1081}