scholarly journals Deep-float salinity data synthesis for deep ocean state estimation: method and impact

Author(s):  
Shuhei Masuda ◽  
Satoshi Osafune ◽  
Tadashi Hemmi
2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Shuhei Masuda ◽  
Nozomi Sugiura ◽  
Satoshi Osafune ◽  
Toshimasa Doi

We investigated the impact of assimilating a mapped dataset of subsurface ocean currents into an ocean state estimation. We carried out two global ocean state estimations from 2000 to 2007 using the K7 four-dimensional variational data synthesis system, one of which included an additional map of climatological geostrophic currents estimated from the global set of Argo floats. We assessed the representativeness of the volume transport in the two exercises. The assimilation of Argo ocean current data at only one level, 1000 dbar depth, had subtle impacts on the estimated volume transports, which were strongest in the subtropical North Pacific. The corrections at 10°N, where the impact was most notable, arose through the nearly complete offset of wind stress curl by the data synthesis system in conjunction with the first mode baroclinic Rossby wave adjustment. Our results imply that subsurface current data can be effective for improving the estimation of global oceanic circulation by a data synthesis.


2004 ◽  
Author(s):  
Carl Wunsch ◽  
Ichiro Fukumori ◽  
Tong Lee ◽  
Dimitris Menemenlis ◽  
David W. Behringer ◽  
...  

2021 ◽  
Vol 1802 (3) ◽  
pp. 032088
Author(s):  
Xiaonan Yang ◽  
Yansheng Lang ◽  
Heng Zhang ◽  
Yan Lv ◽  
Chengzhi Zhu ◽  
...  

2004 ◽  
Vol 17 (22) ◽  
pp. 4301-4315 ◽  
Author(s):  
Dietmar Dommenget ◽  
Detlef Stammer

Abstract Simulations and seasonal forecasts of tropical Pacific SST and subsurface fields that are based on the global Consortium for Estimating the Circulation and Climate of the Ocean (ECCO) ocean-state estimation procedure are investigated. As compared to similar results from a traditional ENSO simulation and forecast procedure, the hindcast of the constrained ocean state is significantly closer to observed surface and subsurface conditions. The skill of the 12-month lead SST forecast in the equatorial Pacific is comparable in both approaches. The optimization appears to have better skill in the SST anomaly correlations, suggesting that the initial ocean conditions and forcing corrections calculated by the ocean-state estimation do have a positive impact on the predictive skill. However, the optimized forecast skill is currently limited by the low quality of the statistical atmosphere. Progress is expected from optimizing a coupled model over a longer time interval with the coupling statistics being part of the control vector.


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