The accurate simulation of the equatorial sea surface temperature(SST) variability is crucial for a proper representation or prediction of the El Ni?o-Southern Oscillation(ENSO). This paper describes the tropical variability simulated by the Max Planck Institute(MPI) for meteorology coupled atmosphere-ocean general circulation model(CGCM). A control simulation with pre-industrial greenhouse gases is analyzed, and the simulation of key oceanic features, such as SST, is compared with observations. Results from the 400-yr control simulation show that the model's ENSO variability is quite realistic in terms of structure, strength, and period. Also, two related features(the annual cycle of SST and the-phase locking of ENSO events), which are significant in determining the model's performance of realistic ENSO prediction, are further validated to be well reproduced by the MPI climate model, which is an atmospheric model ECHAM5(which fuses the EC for European Center and HAM for Hamburg) coupled to an MPI ocean model(MPI-OM), ECHAM5/MPI-OM.
Collaboration of interannual variabilities and the climate mean state determines the type of El Nio. Recent studies highlight the impact of a La Nia-like mean state change, which acts to suppress the convection and low-level convergence over the central Pacific, on the predominance of central Pacific(CP) El Nio in the most recent decade. However, how interannual variabilities affect the climate mean state has been less thoroughly investigated. Using a linear shallow-water model, the effect of decadal changes of air-sea interaction on the two types of El Nio and the climate mean state over the tropical Pacific is examined. It is demonstrated that the predominance of the eastern Pacific(EP) and CP El Nio is dominated mainly by relationships between anomalous wind stresses and sea surface temperature(SST). Furthermore, changes between air-sea interactions from 1980–98 to 1999–2011 prompted the generation of the La Nialike pattern, which is similar to the background change in the most recent decade.
Within the frame of the Zebiak-Cane model,the impact of the uncertainties of the Madden-Julian Oscillation(MJO) on ENSO predictability was studied using a parameterized stochastic representation of intraseasonal forcing.The results show that the uncertainties of MJO have little effect on the maximum prediction error for ENSO events caused by conditional nonlinear optimal perturbation(CNOP);compared to CNOP-type initial error,the model error caused by the uncertainties of MJO led to a smaller prediction uncertainty of ENSO,and its influence over the ENSO predictability was not significant.This result suggests that the initial error might be the main error source that produces uncertainty in ENSO prediction,which could provide a theoretical foundation for the data assimilation of the ENSO forecast.
Recent progress in the study of nonlinear atmospheric dynamics and related predictability of weather and climate in China (2007-2011) are briefly introduced in this article. Major achievements in the study of nonlinear atmospheric dynamics have been classified into two types:(1) progress based on the analysis of solutions of simplified control equations, such as the dynamics of NAO, the optimal precursors for blocking onset, and the behavior of nonlinear waves, and (2) progress based on data analyses, such as the nonlinear analyses of fluctuations and recording-breaking temperature events, the long-range correlation of extreme events, and new methods of detecting abrupt dynamical change. Major achievements in the study of predictability include the following:(1) the application of nonlinear local Lyapunov exponents (NLLE) to weather and climate predictability; (2) the application of condition nonlinear optimal perturbation (CNOP) to the studies of El Nin o-Southern Oscillation (ENSO) predictions, ensemble forecasting, targeted observation, and sensitivity analysis of the ecosystem; and (3) new strategies proposed for predictability studies. The results of these studies have provided greater understanding of the dynamics and nonlinear mechanisms of atmospheric motion, and they represent new ideas for developing numerical models and improving the forecast skill of weather and climate events.
El Nio events in the central equatorial Pacific (CP) are gaining increased attention,due to their increasing intensity within the global warming context.Various physical processes have been identified in the climate system that can be responsible for the modulation of El Nio,especially the effects of interannual salinity variability.In this work,a comprehensive data analysis is performed to illustrate the effects of interannual salinity variability using surface and subsurface salinity fields from the Met Office ENSEMBLES (EN3) quality controlled ocean dataset.It is demonstrated that during the developing phase of an El Nio event,a negative sea surface salinity (SSS) anomaly in the western-central basin acts to freshen the mixed layer (ML),decrease oceanic density in the upper ocean,and stabilize the upper layers.These related oceanic processes tend to reduce the vertical mixing and entrainment of subsurface water at the base of the ML,which further enhances the warm sea surface temperature (SST) anomalies associated with the El Nio event.However,the effects of interannually variable salinity are much more significant during the CP-El Nio than during the eastern Pacific (EP) El Nio,indicating that the salinity effect might be an important contributor to the development of CP-El Nio events.
ZHENG Fei 1,WAN Li-Ying 2,and WANG Hui 3 1 International Center for Climate and Environment Science (ICCES),Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China 2 Key Laboratory of Research on Marine Hazards Forecasting,National Marine Environmental Forecasting Center,Beijing 100081,China 3 National Meteorological Center,Beijing 100081,China
