Accuracy Evaluation of Regional and Global Tidal Models (TPXO9 and Goddard Ocean Tide) at Kabil Tidal Station

S. N. Chayati, Muhammad Zainuddin Lubis, Adinda Syahrani
{"title":"Accuracy Evaluation of Regional and Global Tidal Models (TPXO9 and Goddard Ocean Tide) at Kabil Tidal Station","authors":"S. N. Chayati, Muhammad Zainuddin Lubis, Adinda Syahrani","doi":"10.30871/jagi.v7i1.5591","DOIUrl":null,"url":null,"abstract":"Indonesia  is an archipelagic country with a total marine area of 5.9 million km², consisting of 3.2 million km² of territorial  waters  and  2.7  km²  of  Exclusive  Economic  Zone waters, not including the continental shelf. With the vast waters in  Indonesia,  sufficient  information  about  the  tides  is  needed. Limitations of terrestrial tide data amidst the increasing need for marine information can be overcome by using global and regional tide models. This study uses the regional tidal data model released by BIG (Geospatial Information Agency) and the global tide model TPXO9 and GOT (Goddard Ocean Tides). From the two global tidal models, the tidal harmonic constant values are extracted at the tidal observation point in Kabil. Evaluation of global and regional tide models is carried out by comparing the amplitude values of the main harmonic constants of the tide models of global and regional tides with the amplitude values of the harmonic constants of terrestrial tidal measurement data to obtain a comparison of accuracy. The results of this research show the value of main tidal harmonic.","PeriodicalId":503070,"journal":{"name":"Journal of Applied Geospatial Information","volume":"51 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Geospatial Information","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30871/jagi.v7i1.5591","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Indonesia  is an archipelagic country with a total marine area of 5.9 million km², consisting of 3.2 million km² of territorial  waters  and  2.7  km²  of  Exclusive  Economic  Zone waters, not including the continental shelf. With the vast waters in  Indonesia,  sufficient  information  about  the  tides  is  needed. Limitations of terrestrial tide data amidst the increasing need for marine information can be overcome by using global and regional tide models. This study uses the regional tidal data model released by BIG (Geospatial Information Agency) and the global tide model TPXO9 and GOT (Goddard Ocean Tides). From the two global tidal models, the tidal harmonic constant values are extracted at the tidal observation point in Kabil. Evaluation of global and regional tide models is carried out by comparing the amplitude values of the main harmonic constants of the tide models of global and regional tides with the amplitude values of the harmonic constants of terrestrial tidal measurement data to obtain a comparison of accuracy. The results of this research show the value of main tidal harmonic.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
卡比尔潮汐站区域和全球潮汐模型(TPXO9 和戈达德海洋潮汐)精度评估
印度尼西亚是一个群岛国家,海洋总面积为 590 万平方公里,其中领海 320 万平方公里,专属经济区水域 270 平方公里,不包括大陆架。印度尼西亚水域广阔,因此需要足够的潮汐信息。在对海洋信息的需求日益增长的情况下,可以通过使用全球和区域潮汐模型来克服陆地潮汐数据的局限性。本研究使用了地理空间信息局(BIG)发布的区域潮汐数据模型以及全球潮汐模型 TPXO9 和 GOT(戈达德海洋潮汐)。从这两个全球潮汐模型中,提取了卡比尔潮汐观测点的潮汐谐波常数值。通过比较全球和区域潮汐模型的主要谐波常量振幅值与陆地潮汐测量数据的谐波常量振幅值,对全球和区域潮汐模型进行评估,以获得精度比较。研究结果显示了潮汐主谐波的值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Underwater Acoustic Propagation using Monterey-Miami Parabolic Equation in Shallow Water Kayeli Bay Buru Distric Design and Development of A Digital Soil Temperature Monitoring System Based on The Internet of Things at North Sumatra Climatological Station Geographic Information System Mapping Risk Factors Stunting Using Methods Geographically Weighted Regression Data-Driven Modeling of Human Development Index in Eastern Indonesia's Region Using Gaussian Techniques Empowered by Machine Learning Machine Learning-Enhanced Geographically Weighted Regression for Spatial Evaluation of Human Development Index across Western Indonesia
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1