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

IF 4.2 2区 地球科学 Q2 ENVIRONMENTAL SCIENCES Remote Sensing Pub Date : 2024-09-09 DOI:10.3390/rs16173340
Mahmoud Pirooznia, Behzad Voosoghi, Mohammad Amin Khalili, Diego Di Martire, Arash Amini
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引用次数: 0

摘要

近年来,利用海洋动能已成为一种前景广阔的可再生能源解决方案。然而,确定提取动能的最佳地点仍是一项重大挑战。本研究提出了一种新方案,通过整合大地测量数据和现场测量数据来估算作为永久性表层流的总表层流(TSC)。总表层流通常是根据动态地形得出的地营海流和埃克曼海流的组合。我们利用 NOAA 的 Ekman 海流数据来补充地转海流并获得 TSC。为了进一步提高 TSC 估算的准确性,我们采用了 3DVAR 数据同化方法,并结合了当地海流计观测数据。结果与两个对照海流计站进行了验证。数据同化过程使计算的 TSC 精度提高了 4 至 15 厘米/秒。利用同化的 TSC 数据,我们对动能潜力进行了评估,并确定了六个最有希望提取海洋动能的区域。这种创新方法可以帮助研究人员和决策者锁定最适合利用海洋可再生能源的地点。
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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.
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来源期刊
Remote Sensing
Remote Sensing REMOTE SENSING-
CiteScore
8.30
自引率
24.00%
发文量
5435
审稿时长
20.66 days
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.
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