{"title":"Australian Ocean surface waves dataset from SAR","authors":"S. Khan, M. Hemer, E. Echevarria, E. King","doi":"10.1002/gdj3.238","DOIUrl":null,"url":null,"abstract":"<p>In this article, a regional ocean surface waves dataset from Sentinel-1 A and B Synthetic Aperture Radar (SAR) satellites has been described. The ocean wave data have been extracted from the Sentinel-1 level-2 OCN (ocean) product as provided by the European Space Agency and downloadable for this region from the Copernicus Australasia regional data hub. The source OCN data have been produced by evolving versions of Sentinel-1 Instrument Processing Facility (IPF). The structure of the source OCN NetCDF files changes over time and presents a challenge in performing long duration, time series analyses, including the examination of potential inconsistencies in OCN wave data, due to employment of different IPF versions over the duration of the satellite missions. Here, the input OCN wave data have been homogenized to a single, easily usable standard format after applying a quality assurance and control procedure that removes various inconsistencies in variables, coordinates, dimensions and land flag, and through the addition of new auxiliary variables. The new format has the desirable properties of being compact in size, consistent in structure, and scalable in temporal and spatial coverage. It is also convenient to use and offers opportunities to perform fast, multi-year regional processing and analysis for calibration and validation studies and scientific applications. No re-processing of Sentinel-1 level-1 data has been carried out in this work.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"638-654"},"PeriodicalIF":3.3000,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.238","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoscience Data Journal","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/gdj3.238","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
In this article, a regional ocean surface waves dataset from Sentinel-1 A and B Synthetic Aperture Radar (SAR) satellites has been described. The ocean wave data have been extracted from the Sentinel-1 level-2 OCN (ocean) product as provided by the European Space Agency and downloadable for this region from the Copernicus Australasia regional data hub. The source OCN data have been produced by evolving versions of Sentinel-1 Instrument Processing Facility (IPF). The structure of the source OCN NetCDF files changes over time and presents a challenge in performing long duration, time series analyses, including the examination of potential inconsistencies in OCN wave data, due to employment of different IPF versions over the duration of the satellite missions. Here, the input OCN wave data have been homogenized to a single, easily usable standard format after applying a quality assurance and control procedure that removes various inconsistencies in variables, coordinates, dimensions and land flag, and through the addition of new auxiliary variables. The new format has the desirable properties of being compact in size, consistent in structure, and scalable in temporal and spatial coverage. It is also convenient to use and offers opportunities to perform fast, multi-year regional processing and analysis for calibration and validation studies and scientific applications. No re-processing of Sentinel-1 level-1 data has been carried out in this work.
Geoscience Data JournalGEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍:
Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered.
An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices.
Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.