海面adcp对海洋混合层深度和温度的声感测

IF 1.9 4区 地球科学 Q2 ENGINEERING, OCEAN Journal of Atmospheric and Oceanic Technology Pub Date : 2022-11-07 DOI:10.1175/jtech-d-22-0055.1
S. Brenner, J. Thomson, L. Rainville, D. Torres, M. Doble, J. Wilkinson, Craig M. Lee
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引用次数: 1

摘要

表面混合层(ML)的性质对于理解和预测不断变化的北冰洋中的大气-海洋-冰-海洋相互作用至关重要。系泊测量通常无法解决北极的ML,因为需要将仪器保持在水面以下,以避免与海冰和冰山接触。在这里,我们使用在波弗特海安装了一年的三个系泊系统的测量结果来证明安装在地下浮子上的向上看声学多普勒海流剖面仪(ADCP)可以用于估计ML特性。开发了一种方法,用于组合ADCP的声学反向散射和惯性剪切中的测量峰值来估计ML深度。此外,我们使用反向声速模型,根据开放水域期间ADCP高度计距离的偏移来推断夏季ML温度。ADCP对ML深度和ML温度的估计与系泊温度传感器、卫星SST和自主滑翔机的测量结果相比是有利的。这些方法可以应用于其他现存的系泊记录,以恢复有关ML特性变化和可变性的额外信息。
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Acoustic sensing of ocean mixed layer depth and temperature from uplooking ADCPs
Properties of the surface mixed layer (ML) are critical for understanding and predicting atmosphere-sea ice-ocean interactions in the changing Arctic Ocean. Mooring measurements are typically unable to resolve the ML in the Arctic due to the need for instruments to remain below the surface to avoid contact with sea ice and icebergs. Here, we use measurements from a series of three moorings installed for one year in the Beaufort Sea to demonstrate that upward looking Acoustic Doppler Current Profilers (ADCPs) installed on subsurface floats can be used to estimate ML properties. A method is developed for combining measured peaks in acoustic backscatter and inertial shear from the ADCPs to estimate the ML depth. Additionally, we use an inverse sound speed model to infer the summer ML temperature based on offsets in ADCP altimeter distance during open water periods. The ADCP estimates of ML depth and ML temperature compare favourably with measurements made from mooring temperature sensors, satellite SST, and from an autonomous Seaglider. These methods could be applied to other extant mooring records to recover additional information about ML property changes and variability.
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来源期刊
CiteScore
4.50
自引率
9.10%
发文量
135
审稿时长
3 months
期刊介绍: The Journal of Atmospheric and Oceanic Technology (JTECH) publishes research describing instrumentation and methods used in atmospheric and oceanic research, including remote sensing instruments; measurements, validation, and data analysis techniques from satellites, aircraft, balloons, and surface-based platforms; in situ instruments, measurements, and methods for data acquisition, analysis, and interpretation and assimilation in numerical models; and information systems and algorithms.
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