scholarly journals Role of subsurface entrainment temperature (Te) in the onset of El Niño events, as represented in an intermediate coupled model

2015 ◽  
Vol 46 (5-6) ◽  
pp. 1417-1435 ◽  
Author(s):  
Rong-Hua Zhang ◽  
Chuan Gao
Author(s):  
Eric Hackert ◽  
Joaquim Ballabrera-Poy ◽  
Antonio J. Busalacchi ◽  
Rong-Hua Zhang ◽  
Ragu Murtugudde

2018 ◽  
Vol 31 (4) ◽  
pp. 1315-1335 ◽  
Author(s):  
Samantha Ferrett ◽  
Matthew Collins ◽  
Hong-Li Ren

The rate of damping of tropical Pacific sea surface temperature anomalies (SSTAs) associated with El Niño events by surface shortwave heat fluxes has significant biases in current coupled climate models [phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. Of 33 CMIP5 models, 16 have shortwave feedbacks that are weakly negative in comparison to observations, or even positive, resulting in a tendency of amplification of SSTAs. Two biases in the cloud response to El Niño SSTAs are identified and linked to significant mean state biases in CMIP5 models. First, cool mean SST and reduced precipitation are linked to comparatively less cloud formation in the eastern equatorial Pacific during El Niño events, driven by a weakened atmospheric ascent response. Second, a spurious reduction of cloud driven by anomalous surface relative humidity during El Niño events is present in models with more stable eastern Pacific mean atmospheric conditions and more low cloud in the mean state. Both cloud response biases contribute to a weak negative shortwave feedback or a positive shortwave feedback that amplifies El Niño SSTAs. Differences between shortwave feedback in the coupled models and the corresponding atmosphere-only models (AMIP) are also linked to mean state differences, consistent with the biases found between different coupled models. Shortwave feedback bias can still persist in AMIP, as a result of persisting weak shortwave responses to anomalous cloud and weak cloud responses to atmospheric ascent. This indicates the importance of bias in the atmosphere component to coupled model feedback and mean state biases.


2018 ◽  
Vol 31 (2) ◽  
pp. 555-574 ◽  
Author(s):  
Tao Zhang ◽  
Martin P. Hoerling ◽  
Klaus Wolter ◽  
Jon Eischeid ◽  
Linyin Cheng ◽  
...  

The failed Southern California (SCAL) winter rains during the 2015/16 strong El Niño came as a surprise and a disappointment. Similarities were drawn to very wet winters during several historical strong El Niño events, leading to heightened expectations that SCAL’s multiyear drought would abate in 2016. Ensembles of atmospheric model simulations and coupled model seasonal forecasts are diagnosed to determine both the potential predictability and actual prediction skill of the failed rains, with a focus on understanding the striking contrast of SCAL precipitation between the 2016 and 1998 strong El Niño events. The ensemble mean of simulations indicates that the December–February 2016 winter dryness was not a response to global boundary forcings, which instead generated a wet SCAL signal. Nor was the extreme magnitude of observed 1998 wetness entirely reconcilable with a boundary-forced signal, indicating it was not a particularly precise analog for 2016. Furthermore, model simulations indicate the SCAL 2016 wet signal was 20%–50% less intense than its simulated 1998 counterpart. Such a weaker signal was captured in November 2015 initialized seasonal forecasts, indicating dynamical model skill in predicting a less prolific 2016 rainy season and a capability to forewarn that 2016 would not likely experience the flooding rains of 1998. Analysis of ensemble spread indicates that 2016 dryness was an extreme climate event having less than 5% likelihood in the presence of 2016 global forcings, even though its probability of occurrence was 3–4 times greater in 2016 compared to 1998. Therefore, the failed seasonal rains themselves are argued to be primarily a symptom of subseasonal variability unrelated to boundary forcings whose predictability remains to be explored.


2018 ◽  
Vol 31 (5) ◽  
pp. 1943-1962 ◽  
Author(s):  
Ruihuang Xie ◽  
Fei-Fei Jin

Modern instrumental records reveal that El Niño events differ in their spatial patterns and temporal evolutions. Attempts have been made to categorize them roughly into two main types: eastern Pacific (EP; or cold tongue) and central Pacific (CP; or warm pool) El Niño events. In this study, a modified version of the Zebiak–Cane (MZC) coupled model is used to examine the dynamics of these two types of El Niño events. Linear eigenanalysis of the model is conducted to show that there are two leading El Niño–Southern Oscillation (ENSO) modes with their SST patterns resembling those of two types of El Niño. Thus, they are referred to as the EP and CP ENSO modes. These two modes are sensitive to changes in the mean states. The heat budget analyses demonstrate that the EP (CP) mode is dominated by thermocline (zonal advective) feedback. Therefore, the weak (strong) mean wind stress and deep (shallow) mean thermocline prefer the EP (CP) ENSO mode because of the relative dominance of thermocline (zonal advective) feedback under such a mean state. Consistent with the linear stability analysis, the occurrence ratio of CP/EP El Niño events in the nonlinear simulations generally increases toward the regime where the linear CP ENSO mode has relatively higher growth rate. These analyses suggest that the coexistence of two leading ENSO modes is responsible for two types of El Niño simulated in the MZC model. This model result may provide a plausible scenario for the observed ENSO diversity.


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