{"id":"29dcbed6-af6e-4a8e-b5ef-9d3d7bf909d0","title":"基于浅水波方程的自适应局地化算法评估数据","title_en":"Evaluation data of adaptive localization algorithm based on 2-D shallow water equation model","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：数据以文本格式存储，文件名称为\"Loc_i4DVar_xx_yy.txt\", 其中，xx代表变量，yy代表不同局地化方案。\n数据读取方式：该数据可用ｎｃｌ打开，并进行画图。","description":"本数据用于基于浅水波方程进行自适应局地化方案的性能评估。该理想试验的数据来自于浅水波方程数值模式的模拟，构造了真实场，背景场，观测，集合样本，采用NLS-i4DVar方法进行同化分析得到最优分析场，进而进行模式预报。求解不同变量的预报场和真实场的均方根误差进行自适应局地化方案评估。试验一首先是在不同的局地化方案下高度场和风场的同化精度；试验二是自适应局地化方案对集合样本数的敏感性研究；试验三是自适应局地化方案对不同采样方案的敏感性研究。","doi":"10.11888/Atmos.tpdc.272233","projection":"","language":"zh","share_type":"online","east":1.0,"west":1.0,"south":-1.0,"north":1.0,"scale":null,"crs":null,"filesize":2.0,"share_policy":"a","ts_created":"2022-04-07T08:51:06.415700+08:00","doi_type":"拥有自主知识产权","ts_updated":"2022-04-07T16:13:49.518712+08:00","time_description":"预报６０小时","datas_group":2,"time_description_en":"Forecast 60 hours","data_format":null,"project":[11],"specials":[],"cite":null,"review_status":5,"review_invite":[],"review_editor":{"id":21054,"last_login":"2022-04-10T10:49:12.540341+08:00","username":"tingting","email":"panxd@itpcas.ac.cn","is_active":true,"is_staff":true,"user_name":"潘小多"},"data_sources":null,"temporal_resolution":"Hourly","spatial_resolution":"100km - 1000km","license":"Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","fund":[],"subtopics":{"metadata":"29dcbed6-af6e-4a8e-b5ef-9d3d7bf909d0","three_pole":null,"third_pole":null},"username":"张洪芹","review_time":null,"protected_duration":null,"protected_describe":null,"is_important":false,"hit_count":16}