Mahmoud Pirooznia, Behzad Voosoghi, Mohammad Amin Khalili, Diego Di Martire, Arash Amini
{"title":"利用大地测量观测和数据同化得出的海面洋流绘制波斯湾和阿曼海动能热点图","authors":"Mahmoud Pirooznia, Behzad Voosoghi, Mohammad Amin Khalili, Diego Di Martire, Arash Amini","doi":"10.3390/rs16173340","DOIUrl":null,"url":null,"abstract":"Harnessing ocean kinetic energy has emerged as a promising renewable energy solution in recent years. However, identifying optimal locations for extracting this energy remains a significant challenge. This study presents a novel scheme to estimate the total surface current (TSC) as permanent surface current by integrating geodetic data and in-situ measurements. The TSC is typically a combination of the geostrophic current, derived from dynamic topography, and the Ekman current. We utilize NOAA’s Ekman current data to complement the geostrophic current and obtain the TSC. To further enhance the accuracy of the TSC estimates, we employ a 3DVAR data assimilation method, incorporating local current meter observations. The results are verified against two control current meter stations. The data-assimilation process resulted in an improvement of 4 to 15 cm/s in the precision of calculated TSC. Using the assimilated TSC data, we then assess the kinetic energy potential and identify six regions with the most significant promise for marine kinetic energy extraction. This innovative approach can assist researchers and policymakers in targeting the most suitable locations for harnessing renewable ocean energy.","PeriodicalId":48993,"journal":{"name":"Remote Sensing","volume":"56 1","pages":""},"PeriodicalIF":4.2000,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mapping Kinetic Energy Hotspots in the Persian Gulf and Oman Sea Using Surface Current Derived by Geodetic Observations and Data Assimilation\",\"authors\":\"Mahmoud Pirooznia, Behzad Voosoghi, Mohammad Amin Khalili, Diego Di Martire, Arash Amini\",\"doi\":\"10.3390/rs16173340\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Harnessing ocean kinetic energy has emerged as a promising renewable energy solution in recent years. However, identifying optimal locations for extracting this energy remains a significant challenge. This study presents a novel scheme to estimate the total surface current (TSC) as permanent surface current by integrating geodetic data and in-situ measurements. The TSC is typically a combination of the geostrophic current, derived from dynamic topography, and the Ekman current. We utilize NOAA’s Ekman current data to complement the geostrophic current and obtain the TSC. To further enhance the accuracy of the TSC estimates, we employ a 3DVAR data assimilation method, incorporating local current meter observations. The results are verified against two control current meter stations. The data-assimilation process resulted in an improvement of 4 to 15 cm/s in the precision of calculated TSC. Using the assimilated TSC data, we then assess the kinetic energy potential and identify six regions with the most significant promise for marine kinetic energy extraction. This innovative approach can assist researchers and policymakers in targeting the most suitable locations for harnessing renewable ocean energy.\",\"PeriodicalId\":48993,\"journal\":{\"name\":\"Remote Sensing\",\"volume\":\"56 1\",\"pages\":\"\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.3390/rs16173340\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/rs16173340","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Mapping Kinetic Energy Hotspots in the Persian Gulf and Oman Sea Using Surface Current Derived by Geodetic Observations and Data Assimilation
Harnessing ocean kinetic energy has emerged as a promising renewable energy solution in recent years. However, identifying optimal locations for extracting this energy remains a significant challenge. This study presents a novel scheme to estimate the total surface current (TSC) as permanent surface current by integrating geodetic data and in-situ measurements. The TSC is typically a combination of the geostrophic current, derived from dynamic topography, and the Ekman current. We utilize NOAA’s Ekman current data to complement the geostrophic current and obtain the TSC. To further enhance the accuracy of the TSC estimates, we employ a 3DVAR data assimilation method, incorporating local current meter observations. The results are verified against two control current meter stations. The data-assimilation process resulted in an improvement of 4 to 15 cm/s in the precision of calculated TSC. Using the assimilated TSC data, we then assess the kinetic energy potential and identify six regions with the most significant promise for marine kinetic energy extraction. This innovative approach can assist researchers and policymakers in targeting the most suitable locations for harnessing renewable ocean energy.
期刊介绍:
Remote Sensing (ISSN 2072-4292) publishes regular research papers, reviews, letters and communications covering all aspects of the remote sensing process, from instrument design and signal processing to the retrieval of geophysical parameters and their application in geosciences. Our aim is to encourage scientists to publish experimental, theoretical and computational results in as much detail as possible so that results can be easily reproduced. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.