scholarly journals Sea surface salinity interannual variability in the western tropical Atlantic: An ocean general circulation model study

2004 ◽  
Vol 109 (C5) ◽  
Author(s):  
Nicolas Ferry
Keyword(s):  
Interannual Variability ◽  
General Circulation ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Tropical Atlantic ◽  
Surface Salinity ◽  
Model Study ◽  
Ocean General Circulation

scholarly journals A global eddying hindcast ocean simulation with OFES2

2020 ◽  
Vol 13 (7) ◽  
pp. 3319-3336 ◽  
Author(s):  
Hideharu Sasaki ◽  
Shinichiro Kida ◽  
Ryo Furue ◽  
Hidenori Aiki ◽  
Nobumasa Komori ◽  
...  
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Tidal Mixing ◽  
Surface Salinity ◽  
Previous Version ◽  
Spatiotemporal Scales ◽  
The Kuroshio

Abstract. A quasi-global eddying ocean hindcast simulation using a new version of our model, called OFES2 (Ocean General Circulation Model for the Earth Simulator version 2), was conducted to overcome several issues with unrealistic properties in its previous version, OFES. This paper describes the model and the simulated oceanic fields in OFES2 compared with OFES and also observed data. OFES2 includes a sea-ice model and a tidal mixing scheme, is forced by a newly created surface atmospheric dataset called JRA55-do, and simulated the oceanic fields from 1958 to 2016. We found several improvements in OFES2 over OFES: smaller biases in the global sea surface temperature and sea surface salinity as well as the water mass properties in the Indonesian and Arabian seas. The time series of the Niño3.4 and Indian Ocean Dipole (IOD) indexes are somewhat better in OFES2 than in OFES. Unlike the previous version, OFES2 reproduces more realistic anomalously low sea surface temperatures during a positive IOD event. One possible cause of these improvements in El Niño and IOD events is the replacement of the atmospheric dataset. On the other hand, several issues remained unrealistic, such as the pathways of the Kuroshio and Gulf Stream and the unrealistic spreading of salty Mediterranean overflow. Given the worldwide use of the previous version and the improvements presented here, the output from OFES2 will be useful in studying various oceanic phenomena with broad spatiotemporal scales.

scholarly journals A global eddying hindcast ocean simulation with OFES2

2020 ◽  
Author(s):  
Hideharu Sasaki ◽  
Shinichiro Kida ◽  
Ryo Furue ◽  
Hidenori Aiki ◽  
Nobumasa Komori ◽  
...  
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Tidal Mixing ◽  
Surface Salinity ◽  
Previous Version ◽  
Spatiotemporal Scales ◽  
The Kuroshio

Abstract. A quasi-global eddying ocean hindcast simulation using a new version of our model called OFES2 (Ocean General Circulation Model for the Earth Simulator version 2) was conducted to overcome several issues with unrealistic properties in its previous version OFES. This paper describes the model and the simulated oceanic fields in OFES2 compared with OFES and also observed data. A sea-ice model and a tidal mixing scheme were implemented in OFES2, which was forced by a newly created surface atmospheric dataset called JRA55-do and simulated the oceanic fields from 1958 to 2016. We found several improvements in OFES2 over OFES: smaller biases in the global sea surface temperature and sea surface salinity and the water properties in the Indonesian and Arabian Seas. The time series of the Niño3.4 and Indian Ocean Dipole (IOD) indexes are somewhat better in OFES2 than in OFES. Unlike the previous version, OFES2 reproduces more realistic anomalous low sea surface temperatures during a positive IOD event. One possible cause for these improvements in El Niño and IOD events is the replacement of the atmospheric dataset. On the other hand, several issues remained unrealistic, such as the pathways of the Kuroshio and Gulf Stream and the unrealistic spreading of salty Mediterranean overflow. Given the worldwide use of the previous version and the improvements presented here on it, the output from OFES2 will be useful in studying various oceanic phenomena with broad spatiotemporal scales.

scholarly journals Simulated Sea Surface Salinity Variability in the Tropical Indian Ocean

2010 ◽  
Vol 23 (24) ◽  
pp. 6542-6554 ◽  
Author(s):  
Rashmi Sharma ◽  
Neeraj Agarwal ◽  
Imran M. Momin ◽  
Sujit Basu ◽  
Vijay K. Agarwal
Keyword(s):  
Indian Ocean ◽  
Time Scales ◽  
General Circulation ◽  
Circulation Model ◽  
Equatorial Indian Ocean ◽  
Tropical Indian Ocean ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Salinity Variability

Abstract A long-period (15 yr) simulation of sea surface salinity (SSS) obtained from a hindcast run of an ocean general circulation model (OGCM) forced by the NCEP–NCAR daily reanalysis product is analyzed in the tropical Indian Ocean (TIO). The objective of the study is twofold: assess the capability of the model to provide realistic simulations of SSS and characterize the SSS variability in view of upcoming satellite salinity missions. Model fields are evaluated in terms of mean, standard deviation, and characteristic temporal scales of SSS variability. Results show that the standard deviations range from 0.2 to 1.5 psu, with larger values in regions with strong seasonal transitions of surface currents (south of India) and along the coast in the Bay of Bengal (strong Kelvin-wave-induced currents). Comparison of simulated SSS with collocated SSS measurements from the National Oceanographic Data Center and Argo floats resulted in a high correlation of 0.85 and a root-mean-square error (RMSE) of 0.4 psu. The correlations are quite high (>0.75) up to a depth of 300 m. Daily simulations of SSS compare well with a Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction (RAMA) buoy in the eastern equatorial Indian Ocean (1.5°S, 90°E) with an RMSE of 0.3 psu and a correlation better than 0.6. Model SSS compares well with observations at all time scales (intraseasonal, seasonal, and interannual). The decorrelation scales computed from model and buoy SSS suggest that the proposed 10-day sampling of future salinity sensors would be able to resolve much of the salinity variability at time scales longer than intraseasonal. This inference is significant in view of satellite salinity sensors, such as Soil Moisture and Ocean Salinity (SMOS) and Aquarius.

scholarly journals Retrospective Forecasts of Interannual Sea Surface Temperature Anomalies from 1982 to Present Using a Directly Coupled Atmosphere–Ocean General Circulation Model

2005 ◽  
Vol 133 (10) ◽  
pp. 2972-2995 ◽  
Author(s):  
David G. DeWitt
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation Model ◽  
General Circulation ◽  
Coupled Model ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Sea Surface ◽  
Initial Condition ◽  
Ocean General Circulation

Abstract A large number of ensemble hindcasts (or retrospective forecasts) of tropical Pacific sea surface temperature (SST) have been made with a coupled atmosphere–ocean general circulation model (CGCM) that does not employ flux correction in order to evaluate the potential skill of the model as a seasonal forecasting tool. Oceanic initial conditions are provided by an ocean data assimilation system. Ensembles of seven forecasts of 6-month length are made starting each month in the 1982 to 2002 period. Skill of the coupled model is evaluated from both a deterministic and a probabilistic perspective. The skill metrics are calculated using both the bulk method, which includes all initial condition months together, and as a function of initial condition month. The latter method allows a more objective evaluation of how the model has performed in the context in which forecasts are actually made and applied. The deterministic metrics used are the anomaly correlation and the root-mean-square error. The coupled model deterministic skill metrics are compared with those from persistence and damped persistence reference forecasts. Despite the fact that the coupled model has a large cold bias in the central and eastern equatorial Pacific this coupled model is shown to have forecast skill that is competitive with other state-of-the-art forecasting techniques. Potential skill from probabilistic forecasts made using the coupled model ensemble members are evaluated using the relative operating characteristics method. This analysis indicates that for most initial condition months this coupled model has more skill at forecasting cold events than warm or neutral events in the central Pacific. In common with other forecasting systems, the coupled model forecast skill is found to be lowest for forecasts passing through the Northern Hemisphere (NH) spring. Diagnostics of this so-called spring predictability barrier in the context of this coupled model indicate that two factors likely contribute to this predictability barrier. First, the coupled model shows a too-weak coupling of the surface and subsurface temperature anomalies during NH spring. Second, the coupled-model-simulated signal-to-noise ratio for SST anomalies is much lower during NH spring than at other times of the year, indicating that the model’s potential predictability is low at this time.

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