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首页> 外文期刊>Ocean Dynamics >Observing system experiments over the Atlantic Ocean with the REMO ocean data assimilation system (RODAS) into HYCOM
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Observing system experiments over the Atlantic Ocean with the REMO ocean data assimilation system (RODAS) into HYCOM

机译:使用REMO海洋数据同化系统(RODAS)进入HYCOM的大西洋观测系统实验

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摘要

The Oceanographic Modeling and Observation Network (REMO) focuses on scientific and technological development of operational oceanography in Brazil considering both numerical forecasting and observational systems. A key component of the forecasting system is the recently constructed REMO Ocean Data Assimilation System (RODAS) into the HYbrid Coordinate Ocean Model (HYCOM). Here, RODAS is presented for the first time with its full capability. RODAS employs a multivariate ensemble optimal interpolation scheme that is able to assimilate Argo temperature (T) and salinity (S) profiles, sea surface temperature (SST) analyses, and satellite along-track or gridded sea-level anomaly (SLA) data. RODAS is presented together with a series of Observing System Experiments (OSEs), in which components of the Global Ocean Observing System (GOOS) were systematically withheld from 3-year assimilation runs over the Atlantic Ocean. Using the same initial condition from a full assimilation run, OSEs were performed from 1 January 2010 to 31 December 2012 withholding (i) only Argo data; (ii) only UK MetOffice OSTIA SST analyses; (iii) only satellite along-track altimetry data; and (iv) all observation types. These runs were also compared with the full assimilation run and the model free run to evaluate the impact of different observations into the model state. The results show that each observation type brings complementary information into the analyses. Assimilation of SST is needed to better constrain the mixed layer temperature, while assimilation of SLA mainly improves the representation of circulation by adding mesoscale-like features, such as those found in the Gulf Stream and the Brazil-Malvinas Confluence. In the subsurface, only Argo observations are able to constrain the thermohaline state. When Argo data are withheld, the quality of S is seriously compromised and becomes worse than the free run in the upper ocean. Additionally, the run withholding all observation types shows that the model state in the surface almost reaches the free run state by the end of the third year. However, below 300 m, the memory of the Argo data assimilation is longer and the quality of T and S is only degraded by 35% in comparison with the full assimilation run.
机译:海洋建模和观测网络(REMO)着重考虑了数值预报和观测系统的巴西业务海洋学的科学技术发展。预测系统的关键组成部分是最近在混合坐标海洋模型(HYCOM)中构建的REMO海洋数据同化系统(RODAS)。在这里,RODAS首次以其全部功能展示。 RODAS采用多元整体最优插值方案,该方案能够吸收Argo温度(T)和盐度(S)剖面,海面温度(SST)分析以及卫星沿轨或网格化海平面异常(SLA)数据。 RODAS与一系列观测系统实验(OSE)一起展示,其中系统性地禁止了在大西洋上进行3年同化的全球海洋观测系统(GOOS)的组成部分。在完全同化过程中使用相同的初始条件,从2010年1月1日至2012年12月31日进行了OSE(i)仅保留Argo数据; (ii)仅英国MetOffice OSTIA SST分析; (iii)仅卫星沿线测高数据; (iv)所有观察类型。还将这些运行与完全同化运行和自由模型运行进行了比较,以评估不同观测值对模型状态的影响。结果表明,每种观察类型都将补充信息引入分析中。需要SST的同化来更好地限制混合层温度,而SLA的同化主要通过添加类似中尺度的特征(例如在墨西哥湾流和巴西-马尔维纳斯汇合处发现的特征)来改善循环的表示。在地下,只有Argo观测值才能约束热盐状态。如果保留Argo数据,则S的质量将受到严重损害,并且会比上层海洋的自由航行更差。此外,保留所有观察类型的运行表明,到第三年末,表面的模型状态几乎达到了自由运行状态。但是,在300 m以下,与完全同化运行相比,Argo数据同化的存储时间更长,T和S的质量仅下降35%。

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