scholarly journals Using a regional ocean model to understand the structure and variability of acoustic arrivals in Fram Strait

2020 ◽  
Vol 147 (2) ◽  
pp. 1042-1053
Author(s):  
Florian Geyer ◽  
Hanne Sagen ◽  
Bruce Cornuelle ◽  
Matthew R. Mazloff ◽  
Heriberto J. Vazquez
2021 ◽  
Author(s):  
Subekti Mujiasih ◽  
Jean-Marie Beckers ◽  
Alexander Barth

<p>Regional Ocean Model System (ROMS) has been simulated for the Sunda Strait, the Java Sea, and the Indian Ocean. The simulation was undertaken for thirteen months of data period (August 2013 – August 2014). However, we only used four months period for validation, namely September – December 2013. The input data involved the HYbrid Coordinate Ocean Model (HYCOM) ocean model output by considering atmospheric forcing from the European Centre for Medium-Range Weather Forecasts (ECMWF), without and with tides forcing from TPXO and rivers. The output included vertical profile temperature and salinity, sea surface temperature (SST), seas surface height (SSH), zonal (u), and meridional (v) velocity. We compared the model SST to satellite SST in time series, SSH to tides gauges data in time series, the model u and v component velocity to High Frequency (HF) radial velocity. The vertical profile temperature and salinity were compared to Argo float data and XBT. Besides, we validated the amplitude and phase of the ROMS seas surface height to amplitude and phase of the tides-gauges, including four constituents (M2, S2, K1, O1).</p>


Author(s):  
Zhenchang Zhang ◽  
Libin Gao ◽  
Minquan Guo ◽  
Riqing Chen

The 4D variational (4DVAR) assimilation numerical ocean model research is proposed. This model for Taiwan Straits (TWS) is based on Regional Ocean Model System (ROMS). The background of the 4DVAR method is introduced and the development process of assimilation system is presented. In the present research, the model assimilated with Sea Surface Temperature (SST) data of HY-2 satellite (Qi, 2012; Xu, 2013) which is the first marine environmental monitoring satellite of China. In this paper, the model processes from Feb. 1 to Feb. 7, 2014 with one-day assimilation time window and root mean square error (RMSE) reduces averagely by 14.7%.


2016 ◽  
Vol 121 (7) ◽  
pp. 4601-4617 ◽  
Author(s):  
Hanne Sagen ◽  
Brian D. Dushaw ◽  
Emmanuel K. Skarsoulis ◽  
Dany Dumont ◽  
Matthew A. Dzieciuch ◽  
...  

2011 ◽  
Vol 38 (4) ◽  
pp. n/a-n/a ◽  
Author(s):  
Clarissa R. Anderson ◽  
Raphael M. Kudela ◽  
Claudia Benitez-Nelson ◽  
Emily Sekula-Wood ◽  
Christopher T. Burrell ◽  
...  

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