{"title":"从 SMOS 和 SMAP L 波段辐射计数据检索北冰洋薄海冰厚度的改进算法","authors":"Lian He, Senwen Huang, Fengming Hui, Xiao Cheng","doi":"10.1007/s13131-023-2280-9","DOIUrl":null,"url":null,"abstract":"<p>The aim of this study was to develop an improved thin sea ice thickness (SIT) retrieval algorithm in the Arctic Ocean from the Soil Moisture Ocean Salinity and Soil Moisture Active Passive L-band radiometer data. This SIT retrieval algorithm was trained using the simulated SIT from the cumulative freezing degree days model during the freeze-up period over five carefully selected regions in the Beaufort, Chukchi, East Siberian, Laptev and Kara seas and utilized the microwave polarization ratio (PR) at incidence angle of 40°. The improvements of the proposed retrieval algorithm include the correction for the sea ice concentration impact, reliable reference SIT data over different representative regions of the Arctic Ocean and the utilization of microwave polarization ratio that is independent of ice temperature. The relationship between the SIT and PR was found to be almost stable across the five selected regions. The SIT retrievals were then compared to other two existing algorithms (i.e., UH_SIT from the University of Hamburg and UB_SIT from the University of Bremen) and validated against independent SIT data obtained from moored upward looking sonars (ULS) and airborne electromagnetic (EM) induction sensors. The results suggest that the proposed algorithm could achieve comparable accuracies to UH_SIT and UB_SIT with root mean square error (RMSE) being about 0.20 m when validating using ULS SIT data and outperformed the UH_SIT and UB_SIT with RMSE being about 0.21 m when validatng using EM SIT data. The proposed algorithm can be used for thin sea ice thickness (<1.0 m) estimation in the Arctic Ocean and requires less auxiliary data in the SIT retrieval procedure which makes its implementation more practical.</p>","PeriodicalId":6922,"journal":{"name":"Acta Oceanologica Sinica","volume":"263 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An improved algorithm for retrieving thin sea ice thickness in the Arctic Ocean from SMOS and SMAP L-band radiometer data\",\"authors\":\"Lian He, Senwen Huang, Fengming Hui, Xiao Cheng\",\"doi\":\"10.1007/s13131-023-2280-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The aim of this study was to develop an improved thin sea ice thickness (SIT) retrieval algorithm in the Arctic Ocean from the Soil Moisture Ocean Salinity and Soil Moisture Active Passive L-band radiometer data. 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The SIT retrievals were then compared to other two existing algorithms (i.e., UH_SIT from the University of Hamburg and UB_SIT from the University of Bremen) and validated against independent SIT data obtained from moored upward looking sonars (ULS) and airborne electromagnetic (EM) induction sensors. The results suggest that the proposed algorithm could achieve comparable accuracies to UH_SIT and UB_SIT with root mean square error (RMSE) being about 0.20 m when validating using ULS SIT data and outperformed the UH_SIT and UB_SIT with RMSE being about 0.21 m when validatng using EM SIT data. 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引用次数: 0
摘要
这项研究的目的是根据土壤水分海洋盐度和土壤水分主动被动 L 波段辐射计数据,开发一种改进的北冰洋薄海冰厚度(SIT)检索算法。在波弗特海、楚科奇海、东西伯利亚海、拉普捷夫海和喀拉海五个精心选择的区域,利用冰冻期累积冰冻度日模型模拟的 SIT,并利用入射角为 40°的微波极化率(PR),对这种 SIT 检索算法进行了训练。所提议的检索算法的改进之处包括对海冰浓度影响的校正、北冰洋不同代表性区域的可靠参考 SIT 数据以及利用与冰温无关的微波极化率。研究发现,在所选的五个区域中,SIT 和 PR 之间的关系几乎是稳定的。然后,将 SIT 检索结果与其他两种现有算法(即汉堡大学的 UH_SIT 算法和不来梅大学的 UB_SIT 算法)进行了比较,并根据从系泊上视声纳(ULS)和机载电磁感应传感器获得的独立 SIT 数据进行了验证。结果表明,在使用 ULS SIT 数据进行验证时,所提出的算法可以达到与 UH_SIT 和 UB_SIT 相当的精度,均方根误差 (RMSE) 约为 0.20 米;在使用 EM SIT 数据进行验证时,所提出的算法优于 UH_SIT 和 UB_SIT,均方根误差 (RMSE) 约为 0.21 米。所提出的算法可用于北冰洋薄海冰厚度(1.0 米)的估算,并且在 SIT 检索过程中需要的辅助数据较少,因此其实施更加实用。
An improved algorithm for retrieving thin sea ice thickness in the Arctic Ocean from SMOS and SMAP L-band radiometer data
The aim of this study was to develop an improved thin sea ice thickness (SIT) retrieval algorithm in the Arctic Ocean from the Soil Moisture Ocean Salinity and Soil Moisture Active Passive L-band radiometer data. This SIT retrieval algorithm was trained using the simulated SIT from the cumulative freezing degree days model during the freeze-up period over five carefully selected regions in the Beaufort, Chukchi, East Siberian, Laptev and Kara seas and utilized the microwave polarization ratio (PR) at incidence angle of 40°. The improvements of the proposed retrieval algorithm include the correction for the sea ice concentration impact, reliable reference SIT data over different representative regions of the Arctic Ocean and the utilization of microwave polarization ratio that is independent of ice temperature. The relationship between the SIT and PR was found to be almost stable across the five selected regions. The SIT retrievals were then compared to other two existing algorithms (i.e., UH_SIT from the University of Hamburg and UB_SIT from the University of Bremen) and validated against independent SIT data obtained from moored upward looking sonars (ULS) and airborne electromagnetic (EM) induction sensors. The results suggest that the proposed algorithm could achieve comparable accuracies to UH_SIT and UB_SIT with root mean square error (RMSE) being about 0.20 m when validating using ULS SIT data and outperformed the UH_SIT and UB_SIT with RMSE being about 0.21 m when validatng using EM SIT data. The proposed algorithm can be used for thin sea ice thickness (<1.0 m) estimation in the Arctic Ocean and requires less auxiliary data in the SIT retrieval procedure which makes its implementation more practical.
期刊介绍:
Founded in 1982, Acta Oceanologica Sinica is the official bi-monthly journal of the Chinese Society of Oceanography. It seeks to provide a forum for research papers in the field of oceanography from all over the world. In working to advance scholarly communication it has made the fast publication of high-quality research papers within this field its primary goal.
The journal encourages submissions from all branches of oceanography, including marine physics, marine chemistry, marine geology, marine biology, marine hydrology, marine meteorology, ocean engineering, marine remote sensing and marine environment sciences.
It publishes original research papers, review articles as well as research notes covering the whole spectrum of oceanography. Special issues emanating from related conferences and meetings are also considered. All papers are subject to peer review and are published online at SpringerLink.