Influence of the Ocean Mesoscale Eddy–Atmosphere Thermal Feedback on the Upper-Ocean Haline Stratification

2020 ◽  
Vol 50 (9) ◽  
pp. 2475-2490
Author(s):  
Xuan Shan ◽  
Zhao Jing ◽  
Bingrong Sun ◽  
Ping Chang ◽  
Lixin Wu ◽  
...  

AbstractThe ocean mesoscale eddy–atmosphere (OME-A) interaction through the eddy-induced sea surface temperature anomaly can feedback on ocean dynamics in various ways (referred to as the OME-A thermal feedback). In this study, the influence of the OME-A thermal feedback on the upper-ocean haline structure is analyzed based on high-resolution coupled simulations. In the Oyashio Extension where pronounced surface temperature and salinity fronts are collocated, the haline stratification in the upper 200 m is significantly enhanced by the OME-A thermal feedback. This enhancement is mainly attributed to the weakening of the upward eddy salinity transport in response to the OME-A thermal feedback. The OME-A thermal feedback influences the vertical eddy salinity transport through its differed impacts on the mesoscale buoyancy and temperature anomaly variances. As temperature and salinity in the Oyashio Extension are strongly compensated for their effects on buoyancy, the dissipation of the mesoscale buoyancy anomaly variance b′2 by the OME-A thermal feedback is considerably weaker than that estimated from the mesoscale temperature anomaly alone, i.e., (gαT′)2, with g the gravity acceleration and α the thermal expansion coefficient. Correspondingly, the vertical eddy buoyancy transport (w′b′) is weakened by the OME-A thermal feedback to a lesser extent than its thermal component (gαw′T′). The different responses of w′b′ and gαw′T′ to the OME-A thermal feedback are reconciled by the reduced vertical eddy salinity transport.

2019 ◽  
Vol 86 (sp1) ◽  
pp. 239
Author(s):  
Dhanya Joseph ◽  
Vazhamattom Benjamin Liya ◽  
Girindran Rojith ◽  
Pariyappanal Ulahannan Zacharia ◽  
George Grinson

Ocean Science ◽  
2018 ◽  
Vol 14 (2) ◽  
pp. 301-320 ◽  
Author(s):  
Mei Hong ◽  
Xi Chen ◽  
Ren Zhang ◽  
Dong Wang ◽  
Shuanghe Shen ◽  
...  

Abstract. With the objective of tackling the problem of inaccurate long-term El Niño–Southern Oscillation (ENSO) forecasts, this paper develops a new dynamical–statistical forecast model of the sea surface temperature anomaly (SSTA) field. To avoid single initial prediction values, a self-memorization principle is introduced to improve the dynamical reconstruction model, thus making the model more appropriate for describing such chaotic systems as ENSO events. The improved dynamical–statistical model of the SSTA field is used to predict SSTA in the equatorial eastern Pacific and during El Niño and La Niña events. The long-term step-by-step forecast results and cross-validated retroactive hindcast results of time series T1 and T2 are found to be satisfactory, with a Pearson correlation coefficient of approximately 0.80 and a mean absolute percentage error (MAPE) of less than 15 %. The corresponding forecast SSTA field is accurate in that not only is the forecast shape similar to the actual field but also the contour lines are essentially the same. This model can also be used to forecast the ENSO index. The temporal correlation coefficient is 0.8062, and the MAPE value of 19.55 % is small. The difference between forecast results in spring and those in autumn is not high, indicating that the improved model can overcome the spring predictability barrier to some extent. Compared with six mature models published previously, the present model has an advantage in prediction precision and length, and is a novel exploration of the ENSO forecast method.


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