F. Geyer, G. Gopalakrishnan, H. Sagen, B. Cornuelle, F. Challet, M. Mazloff
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引用次数: 0
Abstract
The 2010-2012 Acoustic Technology for Observing the Interior of the Arctic Ocean (ACOBAR) experiment provided acoustic tomography data along three 167-301 km long sections in Fram Strait between Greenland and Spitsbergen. Ocean sound speed data were assimilated into a regional numerical ocean model using the Massachusetts Institute of Technology General Circulation Model-Estimating the Circulation and Climate of the Ocean four-dimensional variational (MITgcm-ECCO 4DVAR) assimilation system. The resulting state estimate matched the assimilated sound speed time series, the root mean squared (RMS) error of the sound speed estimate (~0.4 m s−1) is smaller than the uncertainty of the measurement (~0.8 m s−1). Data assimilation improved modeled range-and-depth-averaged ocean temperatures at the 78°50’N oceanographic mooring section in Fram Strait. The RMS error of the state estimate (0.21°C) is comparable to the uncertainty of the interpolated mooring section (0.23°C). Lack of depth information in the assimilated ocean sound speed measurements caused an increased temperature bias in the upper ocean (0-500 m). The correlations with the mooring section were not improved as short-term variations in the mooring measurements and the ocean state estimate do not always coincide in time. This is likely due to the small-scale eddying and non-linearity of the ocean circulation in Fram Strait. Furthermore, the horizontal resolution of the state estimate (4.5 km) is eddy-permitting, rather than eddy resolving. Thus, the state estimate cannot represent the full ocean dynamics of the region. This study is the first to demonstrate the usefulness of large-scale acoustic measurements for improving ocean state estimates at high latitudes.
2010-2012年北冰洋内部观测声学技术(ACOBAR)实验提供了格陵兰岛和斯匹次卑尔根岛之间的弗拉姆海峡三个167-301公里长的剖面的声学层析成像数据。利用麻省理工学院环流模式-估算海洋环流和气候四维变分(MITgcm-ECCO 4DVAR)同化系统,将海洋声速数据同化为区域数值海洋模式。所得状态估计与同化的声速时间序列相匹配,声速估计的均方根误差(~0.4 m s−1)小于测量的不确定度(~0.8 m s−1)。数据同化改善了Fram海峡78°50′n海洋系泊段的距离和深度平均海洋温度模型。状态估计的均方根误差(0.21°C)与内插系泊段的不确定性(0.23°C)相当。在同化的海洋声速测量中缺乏深度信息导致上层海洋(0-500 m)的温度偏差增加。由于系泊测量的短期变化和海洋状态估计并不总是在时间上一致,因此与系泊段的相关性没有得到改善。这可能是由于弗拉姆海峡的小尺度涡旋和海洋环流的非线性。此外,状态估计(4.5 km)的水平分辨率是允许涡流的,而不是涡流分辨率。因此,状态估计不能代表该地区的全部海洋动态。这项研究首次证明了大规模声学测量对改善高纬度地区海洋状态估计的有用性。
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.