Correction of biased climate simulated by biased physics through parameter estimation in an intermediate coupled model

2015 ◽  
Vol 47 (5-6) ◽  
pp. 1899-1912 ◽  
Author(s):  
Xuefeng Zhang ◽  
Shaoqing Zhang ◽  
Zhengyu Liu ◽  
Xinrong Wu ◽  
Guijun Han
2012 ◽  
Vol 40 (7-8) ◽  
pp. 1789-1798 ◽  
Author(s):  
Xinrong Wu ◽  
Shaoqing Zhang ◽  
Zhengyu Liu ◽  
Anthony Rosati ◽  
Thomas L. Delworth

2006 ◽  
Vol 19 (20) ◽  
pp. 5227-5252 ◽  
Author(s):  
Serena Illig ◽  
Boris Dewitte

Abstract The relative roles played by the remote El Niño–Southern Oscillation (ENSO) forcing and the local air–sea interactions in the tropical Atlantic are investigated using an intermediate coupled model (ICM) of the tropical Atlantic. The oceanic component of the ICM consists of a six-baroclinic mode ocean model and a simple mixed layer model that has been validated from observations. The atmospheric component is a global atmospheric general circulation model developed at the University of California, Los Angeles (UCLA). In a forced context, the ICM realistically simulates both the sea surface temperature anomaly (SSTA) variability in the equatorial band, and the relaxation of the Atlantic northeast trade winds and the intensification of the equatorial westerlies in boreal spring that usually follows an El Niño event. The results of coupled experiments with or without Pacific ENSO forcing and with or without explicit air–sea interactions in the equatorial Atlantic indicate that the background energy in the equatorial Atlantic is provided by ENSO. However, the time scale of the variability and the magnitude of some peculiar events cannot be explained solely by ENSO remote forcing. It is demonstrated that the peak of SSTA variability in the 1–3-yr band as observed in the equatorial Atlantic is due to the local air–sea interactions and is not a linear response to ENSO. Seasonal phase locking in boreal summer is also the result of the local coupling. The analysis of the intrinsic sustainable modes indicates that the Atlantic El Niño is qualitatively a noise-driven stable system. Such a system can produce coherent interdecadal variability that is not forced by the Pacific or extraequatorial variability. It is shown that when a simple slab mixed layer model is embedded into the system to simulate the northern tropical Atlantic (NTA) SST variability, the warming over NTA following El Niño events have characteristics (location and peak phase) that depend on air–sea interaction in the equatorial Atlantic. In the model, the interaction between the equatorial mode and NTA can produce a dipolelike structure of the SSTA variability that evolves at a decadal time scale. The results herein illustrate the complexity of the tropical Atlantic ocean–atmosphere system, whose predictability jointly depends on ENSO and the connections between the Atlantic modes of variability.


Ocean Science ◽  
2015 ◽  
Vol 11 (1) ◽  
pp. 187-194 ◽  
Author(s):  
F. Zheng ◽  
J. Zhu

Abstract. The 2006–2007 El Niño event, an unusually weak event, was predicted by most models only after the warming in the eastern Pacific had commenced. In this study, on the basis of an El Niño prediction system, roles of the initial ocean surface and subsurface states on predicting the 2006–2007 El Niño event are investigated to determine conditions favorable for predicting El Niño growth and are isolated in three sets of hindcast experiments. The hindcast is initialized through assimilation of only the sea surface temperature (SST) observations to optimize the initial surface condition, only the sea level (SL) data to update the initial subsurface state, or both the SST and SL data. Results highlight that the hindcasts with three different initial states can all successfully predict the 2006–2007 El Niño event 1 year in advance and that the hindcast initialized by both the SST and SL data performs best. A comparison between the various sets of hindcast results further demonstrates that successful prediction is more significantly affected by the initial subsurface state than by the initial surface condition. The accurate initial surface state can trigger the easier prediction of the 2006–2007 El Niño, whereas a more reasonable initial subsurface state can contribute to improving the prediction in the growth of the warm event.


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