本数据首次在受热带气旋引发的风暴潮严重影响的区域内，以准全球尺度实施了基于数据驱动模型的全站点建模框架。利用潮位站记录和欧洲中期天气预报中心 （ECMWF）再分析数据集v5（ERA5）数据，生成了一套高空间分辨率（沿海岸线10公里）的每小时风暴潮数据集，即ASM-SS（全站点建模风暴潮），覆盖范围为南纬45°至北纬45°，记录长度超过80年（1940年至2020年）。该数据集以NetCDF文件形式按月提供，每个文件包含五个参数：经度、纬度、节点、时间和风暴潮水位。经度和纬度以度为单位表示节点的地理位置。时间单位为自1900年1月1日00:00:00起累积的小时数。风暴潮水位以米为单位给出。用户可使用经度、纬度和时间作为关键词，在目标时间段内筛选感兴趣节点处的风暴潮水位。此外，沿海岸线的节点空间分辨率为10公里。由于热带气旋期间海面变化迅速，风暴潮水位的时间分辨率设置为每小时。该数据集可为沿海社区提供相关SS分析应用提供可能的替代支持。", "ds_source": "
1、大气数据：1940年至2020年的大气预测数据来自欧洲中期天气预报中心（ECMWF）再分析数据集v5（ERA5）数据库；
2、潮位观测数据：来源于高频率（15分钟或1小时）的GESLA-3数据集，该数据集由36个国际和国家数据提供商提供；
3、数值模型模拟的涌浪数据：来自GTSM版本3全球模拟，该模拟以ERA5（1979–2018年）的平均海平面气压和风场为驱动，其SS精度已得到广泛评估，并与TG观测结果具有良好至较好的吻合度；
4、海岸线轮廓数据：海岸线节点生成采用了全球自洽分层高分辨率地理数据库（GSHHG版本2.3.7）海岸线数据库（Wessel和Smith，1996）。该数据集的海岸线数据源自《世界矢量海岸线与冰冻圈图集》，提供了五种不同分辨率的海岸线轮廓（粗略、低、中等、高和完整）。", "ds_process_way": "
ASM-SS准全球风暴潮数据集是基于ASM数据驱动模型生成的。", "ds_quality": "
评估结果表明，对于第95百分位极端风暴潮，ASM-SS模型的精度（相关系数、均方根误差和平均偏差的中位数分别为0.63、0.093和−0.050米）优于当前最先进的全球水动力模型（中位数分别为0.55、 0.106和−0.045米）。对于年度最大SS值，该模型比数值模型更稳定，整体均方根误差和决定系数分别优化了22.3%和14.8%。", "ds_acq_start_time": "1940-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "全球", "ds_acq_lon_east": 180.0, "ds_acq_lat_south": -45.0, "ds_acq_lon_west": -180.0, "ds_acq_lat_north": 45.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 15176322656, "ds_files_count": 2, "ds_format": "NetCDF", "ds_space_res": "10", "ds_time_res": "月", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "72ef6321-b9d3-4e28-bf3e-2b977d932527.jpg", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "0a4269e1-65f4-45f1-aeba-88ea3068eebf", "ds_serv_man": "敏玉芳", "ds_serv_phone": "09314967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2025-07-30 15:09:30", "last_updated": "2026-01-14 10:56:31", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.ZENODO.DB6930.2025", "i18n": { "en": { "title": "ASM-SS: The first quasi global high spatial resolution coastal storm surge dataset reconstructed based on tidal level observation records (1940-2020)", "ds_format": "NetCDF", "ds_source": "
1. Atmospheric data: The atmospheric forecast data from 1940 to 2020 is sourced from the European Centre for Medium Range Weather Forecasts (ECMWF) reanalysis dataset v5 (ERA5) database;
2. Tide level observation data: sourced from the high-frequency (15 minutes or 1 hour) GESLA-3 dataset, which is provided by 36 international and national data providers;
3. Numerical model simulation of surge data: from GTSM version 3 global simulation, which is driven by the average sea level pressure and wind field of ERA5 (1979-2018). Its SS accuracy has been widely evaluated and has a good to good agreement with TG observation results;
4. Coastline contour data: Coastline nodes were generated using a globally consistent hierarchical high-resolution geographic database (GSHHG version 2.3.7) and a coastline database (Wessel and Smith, 1996). The coastline data in this dataset is sourced from the World Atlas of Vector Coastlines and Cryospheres, providing five different resolutions of coastline contours (coarse, low, medium, high, and complete).", "ds_quality": "
The evaluation results indicate that for extreme storm surges at the 95th percentile, the accuracy of the ASM-SS model (median correlation coefficient, root mean square error, and mean deviation of 0.63, 0.093, and -0.050 meters, respectively) is superior to the current state-of-the-art global hydrodynamic models (median of 0.55, 0.106, and -0.045 meters, respectively). For the annual maximum SS value, this model is more stable than the numerical model, with an overall root mean square error and coefficient of determination optimized by 22.3% and 14.8%, respectively.", "ds_ref_way": "", "ds_abstract": "
This data is the first to implement a data-driven model-based full site modeling framework at a quasi global scale in areas severely affected by storm surges caused by tropical cyclones. Using tide station records and the European Centre for Medium Range Weather Forecasts (ECMWF) reanalysis dataset v5 (ERA5) data, a high spatial resolution (10 kilometers along the coastline) hourly storm surge dataset, ASM-SS (Site wide Modeling Storm Surge), was generated, covering a range of latitude 45 ° S to latitude 45 ° N and recording a length of over 80 years (1940 to 2020). This dataset is provided monthly in the form of NetCDF files, each containing five parameters: longitude, latitude, node, time, and storm surge level. Longitude and latitude represent the geographical location of nodes in degrees. The time unit is the accumulated number of hours since January 1, 1900 at 00:00:00. The storm surge water level is given in meters. Users can use longitude, latitude, and time as keywords to filter storm surge levels at nodes of interest within the target time period. In addition, the spatial resolution of nodes along the coastline is 10 kilometers. Due to the rapid changes in sea surface during tropical cyclones, the time resolution of storm surge levels is set to per hour. This dataset can provide potential alternative support for SS analysis applications in coastal communities.
", "ds_time_res": "月", "ds_acq_place": "Global", "ds_space_res": "10", "ds_projection": "", "ds_process_way": "The ASM-SS quasi global storm surge dataset is generated based on the ASM data-driven model.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "极端海平面", "风暴潮", "数据驱动模型", "全站点建模" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "全球" ], "ds_time_tags": [ 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020 ], "ds_contributors": [ { "true_name": "金涛勇", "email": "tyjin@sgg.whu.edu.cn", "work_for": "武汉大学大地测量与测绘学院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "金涛勇", "email": "tyjin@sgg.whu.edu.cn", "work_for": "武汉大学大地测量与测绘学院", "country": "中国" } ], "ds_managers": [ { "true_name": "金涛勇", "email": "tyjin@sgg.whu.edu.cn", "work_for": "武汉大学大地测量与测绘学院", "country": "中国" } ], "category": "水文" }