Impact of the North Pacific subtropical sea surface temperature front on El Niño-Southern Oscillation

2018 ◽  
Vol 38 ◽  
pp. e729-e740 ◽  
Author(s):  
Leying Zhang ◽  
Haiming Xu ◽  
Ning Shi ◽  
Jing Ma
2011 ◽  
Vol 24 (23) ◽  
pp. 6203-6209 ◽  
Author(s):  
Fabian Lienert ◽  
John C. Fyfe ◽  
William J. Merryfield

Abstract This study evaluates the ability of global climate models to reproduce observed tropical influences on North Pacific Ocean sea surface temperature variability. In an ensemble of climate models, the study finds that the simulated North Pacific response to El Niño–Southern Oscillation (ENSO) forcing is systematically delayed relative to the observed response because of winter and spring mixed layers in the North Pacific that are too deep and air–sea feedbacks that are too weak. Model biases in mixed layer depth and air–sea feedbacks are also associated with a model mean ENSO-related signal in the North Pacific whose amplitude is overestimated by about 30%. The study also shows that simulated North Pacific variability has more power at lower frequencies than is observed because of model errors originating in the tropics and extratropics. Implications of these results for predictions on seasonal, decadal, and longer time scales are discussed.


2019 ◽  
Vol 32 (19) ◽  
pp. 6271-6284 ◽  
Author(s):  
Xiaofan Li ◽  
Zeng-Zhen Hu ◽  
Ping Liang ◽  
Jieshun Zhu

Abstract In this work, the roles of El Niño–Southern Oscillation (ENSO) in the variability and predictability of the Pacific–North American (PNA) pattern and precipitation in North America in winter are examined. It is noted that statistically about 29% of the variance of PNA is linearly linked to ENSO, while the remaining 71% of the variance of PNA might be explained by other processes, including atmospheric internal dynamics and sea surface temperature variations in the North Pacific. The ENSO impact is mainly meridional from the tropics to the mid–high latitudes, while a major fraction of the non-ENSO variability associated with PNA is confined in the zonal direction from the North Pacific to the North American continent. Such interferential connection on PNA as well as on North American climate variability may reflect a competition between local internal dynamical processes (unpredictable fraction) and remote forcing (predictable fraction). Model responses to observed sea surface temperature and model forecasts confirm that the remote forcing is mainly associated with ENSO and it is the major source of predictability of PNA and winter precipitation in North America.


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.


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