为了建立多因素作用下沿海沿江潮位预报，收集了沿线南京、江阴等站潮位数据、河口潮差数据河口风速数据、气压数据、大通流量数据、典型台风数据、覆盖模型范围的水下地形数据，对原始进行存在重复值、错误值及缺失值，需要进行数据的清洗和缺补。数据填补主要采用回归填补的方法，利用相关关系较好的邻近站点潮位时间序列与待填补站点潮位时间序列的相关关系，建立一种回归模型进行潮位序列缺测值填补，提高数据质量。为研究多因素作用条件下沿江沿海潮位预报研究提供了数据支撑。", "ds_source": "
收集了南京潮位站（ 118°43′ 32°05′）、江阴潮位站（ 120°18′ 31°57′）逐时潮位数据，单位为，高程基面为吴淞基面数据时期为2019、2020年期间。\n
收集了大通水文站（117°38′ 30°46′ ）逐时流量数据，单位m3/s,数据时期为2019、2020年期间。
收集了长江口六滧潮位站(121°42′ 31°30′ )潮差数据，单位为m,数据时期为2019、2020年期间。
收集了覆盖沿江、沿海模型范围的地形数据，采用2020年实测水下地形与全球海洋陆地高程数据ETOPO1拼接而成,基面为85基面。\n
收集了河口风速、气压数据，数据来源于欧洲中尺度天气预报中心(ECMWF)全球大气再分析数据EAR5，风速单位m/s,气压单位hPa。 \n
收集了两场典型台风路径、强度信息，数据来源为CMA热带气旋最佳路径数据集（tcdata.typhoon.org.cn）", "ds_process_way": "
（1）对于站点潮位、流量、风速、气压等原始数据，存在重复值、异常值、错误值及缺失值，进行数据的清洗，统计清洗后数据缺测率；\n
（2）对于缺测较少的数据采用三次样条插值方法进行补缺；\n
（3）对于缺测较多的数据用相关关系较好的邻近站点潮位时间序列与待填补站点潮位时间序列的相关关系，建立一种回归模型进行潮位序列缺测值填补，提高数据质量。", "ds_quality": "
经数据清洗、补缺后的潮位无缺测，通过数据一致性检测。本数据集可作为典型蓄滞洪区评价分析的可靠基础数据。", "ds_acq_start_time": "2019-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "长江下游典型站点,沿江沿海区域", "ds_acq_lon_east": 120.26666666666667, "ds_acq_lat_south": 30.76, "ds_acq_lon_west": 117.63, "ds_acq_lat_north": 31.916666666666668, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 976313, "ds_files_count": 16, "ds_format": "*.txt", "ds_space_res": "10m", "ds_time_res": "1小时", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "64493c60-165c-44c4-9e59-32200d23bc61.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "37eb642a-c117-47e4-a677-07ecffb4b8b7", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.55" ], "quality_level": 3, "publish_time": "2025-03-27 21:07:11", "last_updated": "2025-03-27 21:07:11", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NHRI.DB6786.2025", "i18n": { "en": { "title": "Hydrological and meteorological dataset along the lower reaches of the Yangtze River from 2019 to 2020", "ds_format": "", "ds_source": "", "ds_quality": "", "ds_ref_way": "", "ds_abstract": "", "ds_time_res": "1小时", "ds_acq_place": "Typical stations in the lower reaches of the Yangtze River, along the coastal areas along the river", "ds_space_res": "10m", "ds_projection": "", "ds_process_way": "", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "风暴潮", "天文潮", "径流" ], "ds_subject_tags": [ "水文学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国", "长江下游", "感潮河段" ], "ds_time_tags": [ 2019, 2020 ], "ds_contributors": [ { "true_name": "夏明嫣", "email": "MY.xia@outlook.com", "work_for": "南京水利科学研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "夏明嫣", "email": "MY.xia@outlook.com", "work_for": "南京水利科学研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "夏明嫣", "email": "MY.xia@outlook.com", "work_for": "南京水利科学研究院", "country": "中国" } ], "category": "气象" }