El Niño Southern Oscillation (ENSO) is the Earth's strongest source of interannual climate variability. Although its center of action is in the tropical Pacific, it has significant influences on the climate at the planetary scale. ENSO is sustained by a feedback process between equatorial winds, vertical displacements of the thermocline, and sea surface temperature (SST) anomaly gradients. This produces an oscillation in the SST anomaly between a warm (El Niño) and a cold phase (La Niña). While the natural time-scale of ENSO variability is interannual, variations in its behavior and characteristics have been observed over longer time scales, including decadal and interdecadal. Here, we use the Helmholtz decomposition to break down the wind stress into two components: irrotational (curl free) and solenoidal (divergence free). We show that the irrotational component of the wind stress drives the dynamics of the thermocline on the interannual time-scale, while the solenoidal component, whose action is influenced by the stratification of the water column, affects the variability of the thermocline over decadal or interdecadal time-scales. Furthermore, we develop an integral relation that links the variability of the thermocline depth anomaly across the entire tropical Pacific to the variability of the average SST anomaly in the central tropical Pacific (known as the Niño-3.4 index) and conclude that the irrotational component of the wind stress determines the interannual variability of the Niño-3.4 index, while the solenoidal component determines its long-term variability.
A non-autonomous stochastic dynamical model approach is developed to describe the seasonal to interannual variability of the El Niño-Southern Oscillation (ENSO). We determine the model coefficients by systematic statistical estimations using partial observations involving only sea surface temperature data. Our approach reproduces the observed seasonal phase locking and its uncertainty, as well as the highly non-Gaussian statistics of ENSO. Finally, we recover the intermittent time series of the hidden processes, including the thermocline depth and the wind bursts.
The El Nino-Southern Oscillation (ENSO) is one of the most important phenomena in climate. By studying the fluctuations of surface air temperature within one year between 1979-01-01 and 2016-12-31 of the region (30S-30N, 0E-360E) with eigen-decomposition, we find that the temperature fluctuations are dominated by the two principal modes whose temporal evolutions respond significantly to the ENSO variability. According to introduce a micro-correlation, we find that the coupling between the first principal mode and the temperature fluctuations in the El Nino region could result in different ENSO…
Contributions of El Niño Southern Oscillation (ENSO) Diversity to Low-Frequency Changes in ENSO Variance
University of Tübingen（蒂宾根大学）；Cooperative Institute for Research in Environmental Sciences（合作环境科学研究所）；University of Colorado（科罗拉多大学）；NOAA/Physical Sciences Laboratory（美国国家海洋和大气管理局物理科学实验室）
The El Niño Southern Oscillation (ENSO) is the most important driver of interannual global climate variability and can trigger extreme weather events and disasters in various parts of the globe. Recently, we have developed two approaches for the early forecasting of El Niño. The climate network-based approach allows forecasting the onset of an El Niño event about 1 year ahead. The complexity-based approach allows additionally to forecast the magnitude of an upcoming El Niño event in the calendar year before. Here we communicate the forecasts of both methods for 2022.
The El Niño Southern Oscillation (ENSO) is the most important driver of climate variability and can trigger extreme weather events and disasters in various parts of the globe. Recently we have developed a network approach, which allows forecasting an El Niño event about 1 year ahead. Here we communicate that since 2012 this network approach, which does not involve any fit parameter, correctly predicted the absence of El Niño events in 2012, 2013 and 2017 as well as the onset of the large El Niño event that started in 2014 and ended in 2016. Our model also correctly forecasted the onset of the …
The importance of the sea ice retreat in the polar regions for the global warming and the role of ice-albedo feedback was recognized by various authors [1,2]. Similar to a recent study of the phenomenon in the Arctic [3] we present a semi-quantitative estimate of the mechanism for the Southern Hemisphere (SH). Using a simple model, we estimate the contribution of ice-albedo feedback to the mean temperature increase in the SH to be 0.5 +/- 0.1 K in the years 1955 to 2015, while from the simultaneous growth of the greenhouse gases (GHG) we derive a direct warming of only 0.2 +/- 0.05 K in the sa…
A Hybrid Deep-Learning Model for El Niño Southern Oscillation in the Low-Data Regime
University of Tübingen（图宾根大学）；European Centre for Medium Range Weather Forecasts（欧洲中期天气预报中心）；NOAA Physical Sciences Laboratory（国家海洋大气管理局物理科学实验室）；Cooperative Institute for Research in Environmental Sciences（环境科学联合研究所）；University of Colorado（科罗拉多大学）；Data Science Department（数据科学系）
Long-term prediction of El Niño-Southern Oscillation using reservoir computing with data-driven realtime filter
Faculty of Sustainable Design, University of Toyama（富山大学可持续设计学部）；The Graduate School of Environment, Life, Natural Science and Technology, Okayama University（冈山大学环境、生命、自然科学及技术研究生院）；Graduate School of Business Administration, Hitotsubashi University（立正大学商学院）；Graduate School of Economics, Hitotsubashi University（立正大学经济学研究生院）
We study the relationship between the El Niño--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 system's 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…
The El Nino Southern Oscillation (ENSO) is one of the most prominent interannual climate phenomena. An early and reliable ENSO forecasting remains a crucial goal, due to its serious implications for economy, society, and ecosystem. Despite the development of various dynamical and statistical prediction models in the recent decades, the ``spring predictability barrier'' (SPB) remains a great challenge for long (over 6-month) lead-time forecasting. To overcome this barrier, here we develop an analysis tool, the System Sample Entropy (SysSampEn), to measure the complexity (disorder) of the system…
Many phenomena in the climate system lie in the gray zone between weather and climate: they are not amenable to deterministic forecast, but they still depend on the initial condition. A natural example is medium-range forecasting, which is inherently probabilistic because it lies beyond the deterministic predictability time of the atmosphere, but for which statistically significant prediction can be made which depend on the current state of the system. Similarly, one may ask the probability of occurrence of an El Niño event several months ahead of time. In this paper, we introduce a quantity w…
El Niño-Southern Oscillation (ENSO) is the most prominent interannual climate variability in the tropics and exhibits diverse features in spatiotemporal patterns. In this paper, a simple multiscale intermediate coupled stochastic model is developed to capture the ENSO diversity and complexity. The model starts with a deterministic and linear coupled interannual atmosphere, ocean and sea surface temperature (SST) system. It can generate two distinct dominant linear solutions that represent the eastern Pacific (EP) and the central Pacific (CP) El Niños, respectively. In addition to adopting a st…
Comments on the Regional Climate Variability Driven by Foehn Winds in the McMurdo Dry Valleys, Antarctica
主要反对Speirs，McGowan，Steinhoff和Bromwich [Int. J. Climatol.三十三：945-958]的工作是由于缺乏对导致风形成的基本过程的概率分布函数的分析，而风的速度是由自动气象站测量的，并在论文中报告。在数学上，计算平均值的相关系数（皮尔逊积差相关系数）的严格定义并不存在。因此，表II中给出的作者数字代表了一组随机计算的数字。作者认为其中一些随机数在95%水平上具有统计学显著性，这是错误的，因为平均值的相关系数与统计学显著性之间不存在关系。因此，Speirs等人关于厄尔尼诺南方涛动（ENSO）和南方环形模态显著影响麦克默多干谷焚风频率的主要结论完全没有根据。
The El Nino southern oscillation (ENSO) behavior can be effectively modeled as a response to a 2nd-order Mathieu/Hill differential equation with periodic coefficients describing sloshing of a volume of water. The forcing of the equation derives from QBO, angular momentum changes synchronized with the Chandler wobble, and solar insolation variations. One regime change was identified in 1980. (See floating note)
The relation between El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) perplexes the researchers. Probably, this is due to the default choice on empirical orthogonal function (EOF) method whose outputs are merely static maps without evolution characteristics. To change this situation, the new extreme-point symmetric mode decomposition (ESMD) method is tried. It reveals that: (1) As the ENSO concerned, the key modes are the quarter-decadal and half-decadal ones; (2) As the PDO concerned, the key modes are the half-decadal, decadal and interdecadal ones; (3) The half-deca…
The impact of the El Niño-Southern Oscillation (ENSO) on the extratropics is investigated in an idealized, reduced-order model that has a tropical and an extratropical module. Unidirectional ENSO forcing is used to mimick the atmospheric bridge between the tropics and the extratropics. The variability of the coupled ocean-atmosphere extratropical module is then investigated through the analysis of its pullback attractors (PBAs). This analysis focuses on two types of ENSO forcing generated by the tropical module, one periodic and the other aperiodic. For a substantial range of the ENSO forcing,…
The Earth's climate system is a classical example of a multiscale, multiphysics dynamical system with an extremely large number of active degrees of freedom, exhibiting variability on scales ranging from micrometers and seconds in cloud microphysics, to thousands of kilometers and centuries in ocean dynamics. Yet, despite this dynamical complexity, climate dynamics is known to exhibit coherent modes of variability. A primary example is the El Niño Southern Oscillation (ENSO), the dominant mode of interannual (3-5 yr) variability in the climate system. The objective and robust characterization …
Spectral PCA (sPCA), in contrast to classical PCA, offers the advantage of identifying organized spatio-temporal patterns within specific frequency bands and extracting dynamical modes. However, the unavoidable tradeoff between frequency resolution and robustness of the PCs leads to high sensitivity to noise and overfitting, which limits the interpretation of the sPCA results. We propose herein a simple non-parametric implementation of the sPCA using the continuous analytic Morlet wavelet as a robust estimator of the cross-spectral matrices with good frequency resolution. To improve the interp…
