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Register a new userA Multiscale Model for El Ni~no Complexity
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El Ni~no-Southern Oscillation (ENSO) exhibits diverse characteristics in spatial pattern, peak intensity, and temporal evolution. Here we develop a three-region multiscale stochastic model to show that the observed ENSO complexity can be explained by combining intraseasonal, interannual, and decadal processes. The model starts with a deterministic three-region system for the interannual variabilities. Then two stochastic processes of the intraseasonal and decadal variation are incorporated. The model can reproduce not only the general properties of the observed ENSO events, but also the complexity in patterns (e.g., Central Pacific vs. Eastern Pacific events), intensity (e.g., 10-20 year reoccurrence of extreme El Ni~nos), and temporal evolution (e.g., more multi-year La Ni~nas than multi-year El Ni~nos). While conventional conceptual models were typically used to understand the dynamics behind the common properties of ENSO, this model offers a powerful tool to understand and predict ENSO complexity that challenges our understanding of the 21st-century ENSO.
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Although anomalous episodical warming of the eastern equatorial Pacific, dubbed El Ni~no by Peruvian fishermen, has major (and occasionally devastating) impacts around the globe, robust forecasting is still limited to about six months ahead. A significant extension of the pre-warming time would be instrumental for avoiding some of the worst damages such as harvest failures in developing countries. Here we introduce a novel avenue towards El Ni~no-prediction based on network methods inspecting emerging teleconnections. Our approach starts from the evidence that a large-scale cooperative mode - linking the El Ni~no-basin (equatorial Pacific corridor) and the rest of the ocean - builds up in the calendar year before the warming event. On this basis, we can develop an efficient 12 months-forecasting scheme, i.e., achieve some doubling of the early-warning period. Our method is based on high-quality observational data as available since 1950 and yields hit rates above 0.5, while false-alarm rates are below 0.1.
We study the relationship between the El Ni~no--Southern Oscillation (ENSO) and the Indian summer monsoon in ensemble simulations from state-of-the-art climate models, the Max Planck Institute Earth System Model (MPI-ESM) and the Community Earth System Model (CESM). We consider two simple variables: the Tahiti--Darwin sea-level pressure difference and the Northern Indian precipitation. We utilize ensembles converged to the systems snapshot attractor for analyzing possible changes (i) in the teleconnection between the fluctuations of the two variables, and (ii) in their climatic means. (i) With very high confidence, we detect an increase in the strength of the teleconnection, as a response to the forcing, in the MPI-ESM under historical forcing between 1890 and 2005, concentrated to the end of this period. We explain that our finding does not contradict instrumental observations, since their existing analyses regarding the nonstationarity of the teleconnection are either methodologically unreliable, or consider an ill-defined teleconnection concept. In the MPI-ESM we cannot reject stationarity between 2006 and 2099 under the Representative Concentration Pathway 8.5 (RCP8.5), and in a 110-year-long 1-percent pure CO2 scenario; neither can we in the CESM between 1960 and 2100 with historical forcing and RCP8.5. (ii) In the latter ensembles, the climatic mean is strongly displaced in the phase space projection spanned by the two variables. This displacement is nevertheless linear. However, the slope exhibits a strong seasonality, falsifying a hypothesis of a universal, emergent relationship between these two climatic means, excluding applicability in an emergent constraint.
We construct and analyze a climate network which represents the interdependent structure of the climate in different geographical zones and find that the network responds in a unique way to El-Ni~{n}o events. Analyzing the dynamics of the climate network shows that when El-Ni~{n}o events begin, the El-Ni~{n}o basin partially loses its influence on its surroundings. After typically three months, this influence is restored while the basin loses almost all dependence on its surroundings and becomes textit{autonomous}. The formation of an autonomous basin is the missing link to understand the seemingly contradicting phenomena of the afore--noticed weakening of the interdependencies in the climate network during El-Ni~{n}o and the known impact of the anomalies inside the El-Ni~{n}o basin on the global climate system.
The temperatures in different zones in the world do not show significant changes due to El-Nino except when measured in a restricted area in the Pacific Ocean. We find, in contrast, that the dynamics of a climate network based on the same temperature records in various geographical zones in the world is significantly influenced by El-Nino. During El-Nino many links of the network are broken, and the number of surviving links comprises a specific and sensitive measure for El-Nino events. While during non El-Nino periods these links which represent correlations between temperatures in different sites are more stable, fast fluctuations of the correlations observed during El-Nino periods cause the links to break.
In this paper, authors focus effort on improving the conventional discrete velocity method (DVM) into a multiscale scheme in finite volume framework for gas flow in all flow regimes. Unlike the typical multiscale kinetic methods unified gas-kinetic scheme (UGKS) and discrete unified gas-kinetic scheme (DUGKS), which concentrate on the evolution of the distribution function at the cell interface, in the present scheme the flux for macroscopic variables is split into the equilibrium part and the nonequilibrium part, and the nonequilibrium flux is calculated by integrating the discrete distribution function at the cell center, which overcomes the excess numerical dissipation of the conventional DVM in the continuum flow regime. Afterwards, the macroscopic variables are finally updated by simply integrating the discrete distribution function at the cell center, or by a blend of the increments based on the macroscopic and the microscopic systems, and the multiscale property is achieved. Several test cases, involving unsteady, steady, high speed, low speed gas flows in all flow regimes, have been performed, demonstrating the good performance of the multiscale DVM from free molecule to continuum Navier-Stokes solutions and the multiscale property of the scheme is proved.
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