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Potential of space-borne GNSS reflectometry to constrain simulations of the ocean circulation

机译:星载GNSS反射法对海洋环流模拟的潜力

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The Agulhas current system transports warm and salty water masses from the Indian Ocean into the Southern Ocean and into the Atlantic. The transports impact past, present, and future climate on local and global scales. The size and variability, however, of the respective transports are still much debated. In this study, an idealized model based twin experiment is used to study whether sea surface height (SSH) anomalies estimated from reflected signals of the Global Navigation Satellite System reflectometry (GNSS-R) can be used to determine the internal water mass properties and transports of the Agulhas region. A space-borne GNSS-R detector on the International Space Station (ISS) is assumed and simulated. The detector is able to observe daily SSH fields with a spatial resolution of 1-5(a similar to). Depending on reflection geometry, the precision of a single SSH observation is estimated to reach 3 cm (20 cm) when the carrier phase (code delay) information of the reflected GNSS signal is used. The average precision over the Agulhas region is 7 cm (42 cm). The proposed GNSS-R measurements surpass the radar-based satellite altimetry missions in temporal and spatial resolution but are less precise. Using the estimated GNSS-R characteristics, measurements of SSH are generated by sampling a regional nested general circulation model of the South African oceans. The artificial observations are subsequently assimilated with a 4DVAR adjoint data assimilation method into the same ocean model but with a different initial state and forcing. The assimilated and the original, i.e., the sampled model state, are compared to systematically identify improvements and degradations in the model variables that arise due to the assimilation of GNSS-R based SSH observations. We show that SSH and the independent, i.e., not assimilated model variables velocity, temperature, and salinity improve by the assimilation of GNSS-R based SSH observations. After the assimilation of 90 days of SSH observations, improvements in the independent variables cover the whole water column. Locally, up to 39 % of the original model state are recovered. Shorter assimilation windows result in enhanced reproduction of the observed and assimilated SSH but are accompanied by an insufficient or wrong recovery of sub-surface water properties. The assimilation of real GNSS-R observations, when available, and consequently the estimation of Agulhas water mass properties and the leakage of heat and salt into the Atlantic will benefit from this model-based study.
机译:Agulhas当前的系统将温暖的咸水团块从印度洋运输到南洋和大西洋。交通运输对本地和全球范围的过去,现在和将来的气候产生影响。但是,各个运输工具的大小和可变性仍然存在很多争议。在这项研究中,基于理想模型的双生子实验用于研究根据全球导航卫星系统反射法(GNSS-R)的反射信号估计的海面高度(SSH)异常是否可用于确定内部水团性质和运输Agulhas地区。假设并模拟了国际空间站(ISS)上的星载GNSS-R检测器。该检测器能够以1-5(类似于)的空间分辨率观察每日SSH字段。根据反射几何形状,当使用反射的GNSS信号的载波相位(代码延迟)信息时,单个SSH观测的精度估计达到3厘米(20厘米)。 Agulhas区域的平均精度为7厘米(42厘米)。拟议的GNSS-R测量在时间和空间分辨率上均超过了基于雷达的卫星测高任务,但精度较低。使用估计的GNSS-R特性,通过对南非海洋的区域嵌套总环流模型进行采样来生成SSH的测量值。随后,将人工观测值与4DVAR伴随数据同化方法同化为相同的海洋模型,但初始状态和强迫不同。比较同化的和原始的(即采样的模型状态),以系统地识别由于基于GNSS-R的SSH观测的同化而引起的模型变量的改进和退化。我们显示SSH和基于GNSS-R的SSH观测值的同化可以提高SSH和独立模型的速度,温度和盐度的同化度。在接受了90天的SSH观测结果之后,自变量的改进涵盖了整个水柱。在本地,最多可恢复原始模型状态的39%。较短的同化窗口会导致观察到的和被同化的SSH的再现性增强,但伴随着地下水质恢复不足或错误。可以使用真实的GNSS-R观测数据进行同化,从而对Agulhas的水团性质以及热量和盐分渗入大西洋的估算将受益于此基于模型的研究。

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