scholarly journals Rossby Waves and the Variability of the North Pacific Current during 2002–03

2011 ◽  
Vol 41 (9) ◽  
pp. 1708-1719
Author(s):  
Shawn M. Donohue ◽  
Michael W. Stacey

Abstract A numerical model, the Parallel Ocean Program (POP), with 0.25° horizontal spatial resolution and 28 vertical levels is used to simulate the circulation of the North Pacific Ocean for the time period 1960–2006. Spectral nudging is used so that model drift of the mean state over the 46-yr time period of the simulation is prevented while allowing for the prognostic evolution of the circulation at time scales that are not nudged. The simulation successfully reproduces a southward shift in the North Pacific Current in 2002–03 as calculated from scalar observations. It is suggested that this calculated shift may not be solely due to meridional current drift but also a consequence of the shifting intensity of two eastward-moving current bands separated by 300–500 km, a distance consistent with the Rhines scale (the scale at which the 2D turbulence cascade tends to be arrested), which implies an influence from Rossby waves that are heavily affected by nonlinearities. The simulation suggests that the North Pacific Current may indeed have been influenced by a Rossby wave–like disturbance. This disturbance could have been forced to a significant extent by the local winds, but there is also evidence in the model for a coastally generated Rossby wave–like disturbance. This coastal disturbance was generated during the 1997/98 ENSO and traveled westward from the coast at about 1 cm s−1, taking 3–5 yr to travel into the region of the North Pacific Current. The noncoastal portion of the disturbance, which was generated by the local winds away from the coast, propagated westward at about 1 cm s−1 as well.

2021 ◽  
pp. 1-53
Author(s):  
Hua Li ◽  
Shengping He ◽  
Ke Fan ◽  
Yong Liu ◽  
Xing Yuan

AbstractThe Meiyu withdrawal date (MWD) is a crucial indicator of flood/drought conditions over East Asia. It is characterized by a strong interannual variability, but its underlying mechanism remains unknown. We investigated the possible effects of the winter sea surface temperature (SST) in the North Pacific Ocean on the MWD on interannual to interdecadal timescales. Both our observations and model results suggest that the winter SST anomalies associated with the MWD are mainly contributed by a combination of the first two leading modes of the winter SST in the North Pacific, which have a horseshoe shape (the NPSST). The statistical results indicate that the intimate linkage between the NPSST and the MWD has intensified since the early 1990s. During the time period 1990–2016, the NPSST-related SST anomalies persisted from winter to the following seasons and affected the SST over the tropical Pacific in July. Subsequently, the SST anomalies throughout the North Pacific strengthened the southward migration of the East Asian jet stream (EAJS) and the southward and westward replacement of the western North Pacific subtropical high (WPSH), leading to an increase in Meiyu rainfall from July 1 to 20. More convincingly, the anomalous EAJS and WPSH induced by the SST anomalies can be reproduced well by numerical simulations. By contrast, the influence of the NPSST on the EASJ and WPSH were not clear between 1961 and 1985. This study further illustrates that the enhanced interannual variability of the NPSST may be attributed to the more persistent SST anomalies during the time period 1990–2016.


Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 388
Author(s):  
Hao Cheng ◽  
Liang Sun ◽  
Jiagen Li

The extraction of physical information about the subsurface ocean from surface information obtained from satellite measurements is both important and challenging. We introduce a back-propagation neural network (BPNN) method to determine the subsurface temperature of the North Pacific Ocean by selecting the optimum input combination of sea surface parameters obtained from satellite measurements. In addition to sea surface height (SSH), sea surface temperature (SST), sea surface salinity (SSS) and sea surface wind (SSW), we also included the sea surface velocity (SSV) as a new component in our study. This allowed us to partially resolve the non-linear subsurface dynamics associated with advection, which improved the estimated results, especially in regions with strong currents. The accuracy of the estimated results was verified with reprocessed observational datasets. Our results show that the BPNN model can accurately estimate the subsurface (upper 1000 m) temperature of the North Pacific Ocean. The corresponding mean square errors were 0.868 and 0.802 using four (SSH, SST, SSS and SSW) and five (SSH, SST, SSS, SSW and SSV) input parameters and the average coefficients of determination were 0.952 and 0.967, respectively. The input of the SSV in addition to the SSH, SST, SSS and SSW therefore has a positive impact on the BPNN model and helps to improve the accuracy of the estimation. This study provides important technical support for retrieving thermal information about the ocean interior from surface satellite remote sensing observations, which will help to expand the scope of satellite measurements of the ocean.


2021 ◽  
Author(s):  
R. J. David Wells ◽  
Veronica A. Quesnell ◽  
Robert L. Humphreys ◽  
Heidi Dewar ◽  
Jay R. Rooker ◽  
...  

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