The trivariate seasonal analysis of couplings between El Niño,North Atlantic Oscillation,and Indian monsoon

Interdependencies between the El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and Indian monsoon (IM) phenomena are investigated from data over the period of 1871-2013. Along with the bivariate analysis of directional couplings between ENSO, NAO, and IM, their trivariate analysis was carried out. To detect the seasonal features of directional couplings using Wiener-Granger causality, various temporal resolutions of the data ranging from a month to a half-year are used. Taking into account the seasonality of the processes, the influence of ENSO on NAO is detected which has different signs in winter and summer. The influence of NAO on ENSO is revealed only in the trivariate analysis. The strongest couplings are observed between ENSO and IM. All the detected couplings can be divided into two groups: the "fast" (with the characteristic time from a month to several months) and "slow" (with the characteristic time of a half-year or longer) ones. The fast couplings include bidirectional couplings between IM and ENSO in summer and autumn when the summer pattern of NAO influences the patterns of ENSO and IM in the next season. The slow couplings include the effects of ENSO on NAO and on the winter pattern of IM as well as the influence of IM on the summer pattern NAO.     

Statistical simulations of the future 50-year statistics of cold-tongue El Niño and warm-pool El Niño

Recent extensive studies have suggested that the occurrence of warm-pool El Niño has increased since the late 1970s and will increase in future climate. Occurrence frequencies of cold-tongue and warm-pool El Niño have been investigated in the observational record (1980–2006) and in the future 50 years (2007–2056) based on 100 synthetic SST datasets with estimates of statistical confidence. In the observational record, 80% of the warm-pool El Niño occurred since 1980 over a period of 27 years; only 20% of the warm-pool El Niño occurred prior to 1980 over a period of 110 years. The 100 synthetic datasets, on average, produce 142 months of cold-tongue El Niño in 2007–2056 as opposed to an average 107 months in the same length of the observational data; this is a 20.7% increase in the occurrence of cold-tongue El Niño compared with the observational period. Warm-pool El Niño occurred for 112 months in 2007–2056 as opposed to an average occurrence of 42 months in the observational record; this is 2.5 times the occurrence frequency in the 1980–2006 period in the synthetic datasets. As a result, occurrence frequencies of cold-tongue and warm-pool El Niño in the period of 2007–2056 become quite comparable to each other in the synthetic datasets. It is expected in the next 50 years that warm-pool El Niño will be nearly as frequent as cold-tongue El Niño.     

The El Niño stochastic oscillator

A stochastic model is fitted to the observed NINO3.4 time series between 1951–1995. The model is nothing more than the complex version of a first-order autoregressive process. The autocorrelation of this stochastic oscillator model is an exponentially decaying cosine, specified by three parameters: a period, a decay time, and a phase shift. It fits the observed NINO3.4 autocorrelation quite well. Anomalies during an El Niño can be characterized to a large extent by a single, irregularly oscillating, index. Equatorial wave dynamics and delayed-oscillator models have been used to explain this behaviour, and it has been suggested that El Niño might be a stable phenomenon excited by weather noise. Assuming this is the case, the stochastic oscillator has a direct physical interpretation: the parameters of the oscillation can be linked to dynamical models of the delayed-oscillator type, and the noise terms represent random influences, such as intraseasonal oscillations. Long Monte Carlo simulations with the stochastic oscillator show substantial decadal variability and variation in predictability. The observed decadal variability is comparable, except for the rather large rise in the long-term mean around 1980. The observed seasonal dependence of El Niño behaviour is not compatible with the natural variability of a stationary stochastic oscillator. Formulating the model in terms of standardized anomalies takes into account some of the seasonal dependence. A stochastic oscillator forecast model has a skill approaching that of more comprehensive statistical models and may thus serve as an appropriate baseline for the skill of El Niño forecasting systems.     

Anomalous winter climate conditions in the Pacific rim during recent El Niño Modoki and El Niño events

Present work compares impacts of El Niño Modoki and El Niño on anomalous climate in the Pacific rim during boreal winters of 1979–2005. El Niño Modoki (El Niño) is associated with tripole (dipole) patterns in anomalies of sea-surface temperature, precipitation, and upper-level divergent wind in the tropical Pacific, which are related to multiple “boomerangs” of ocean-atmosphere conditions in the Pacific. Zonal and meridional extents of those “boomerangs” reflect their independent influences, which are seen from lower latitudes in the west to higher latitudes in the east. In the central Pacific, more moisture is transported from the tropics to higher latitudes during El Niño Modoki owing to displacement of the wet “boomerang” arms more poleward toward east. Discontinuities at outer “boomerang” arms manifest intense interactions between tropical and subtropical/extratropical systems. The Pacific/North American pattern and related climate anomalies in North America found in earlier studies are modified in very different ways by the two phenomena. The seesaw with the dry north and the wet south in the western USA is more likely to occur during El Niño Modoki, while much of the western USA is wet during El Niño. The moisture to the southwestern USA is transported from the northward shifted ITCZ during El Niño Modoki, while it is carried by the storms traveling along the southerly shifted polar front jet during El Niño. The East Asian winter monsoon related anticyclone is over the South China Sea during El Niño Modoki as compared to its position over the Philippine Sea during El Niño, causing opposite precipitation anomalies in the southern East Asia between the two phenomena.     

Forecasting El Niño and La Niña events using decision tree classifier

Theoretical and Applied Climatology - The El Niño-Southern Oscillation (ENSO) phenomenon affects the global climate by changing temperature and precipitation patterns mainly in tropical...     

Impact of El Niño onset timing on the Indian Ocean: Pacific coupling and subsequent El Niño evolution

A relation between the timing of the El Niño onset and its subsequent evolution is examined by emphasizing its association with the Indian Ocean (IO) SST variation. Two types of El Niño events based on the timing of their onset are classified and their characteristics are examined and compared. In general, spring onset (SP) events grow greater in magnitude and their evolutions have a faster transition. On the contrary, summer onset (SU) events are relatively weaker in magnitude and have a slower transition. Moreover, in contrast to the SU events, the SP events have a strong tendency for accompanying an IO dipole and basin-wide type of warming pattern in the El Niño developing and mature phases, respectively. It is demonstrated here that the distinctive evolutions in transition phase of the two events are resulted from the difference in IO SST. The warm IO SST in the SP El Niño event, lead an anomalous easterlies over the western Pacific, which forces a fast termination of El Niño events.     

El Niño teleconnections in CMIP5 models

Teleconnections associated with warm El Niño/southern oscillation (ENSO) events in 20 climate model intercomparison project 5 (CMIP5) models have been compared with reanalysis observations. Focus has been placed on compact time and space indices, which can be assigned a specific statistical confidence. Nearly all of the models have surface temperature, precipitation and 250 hPa geopotential height departures in the Tropics that are in good agreement with the observations. Most of the models also have realistic anomalies of Northern Hemisphere near-surface temperature, precipitation and 500 hPa geopotential height. Model skill for these variables is significantly related to the ability of a model to accurately simulate Tropical 250 hPa height departures. Additionally, most models have realistic temperature and precipitation anomalies over North America, which are linked to a model’s ability to simulate Tropical 250 hPa and Northern Hemisphere 500 hPa height departures. The skills of temperature and precipitation departures over the Northern Hemisphere and North America are associated with the ability to realistically simulate realistic ENSO frequency and length. Neither horizontal nor vertical resolution differences for either the model atmosphere or ocean are significantly related at the 95 % level to variations in El Niño simulation quality. Overall, recent versions of earlier models have improved in their ability to simulate El Niño teleconnections. For instance, the average model skills of temperature and precipitation for the Tropics, Northern Hemisphere and North America for 11 CMIP5 models are all larger than those for prior versions.     

Indices of El Nio and El Nio Modoki:An Improved El Nio Modoki Index

In recent years, El Nio Modoki (a type of pseudo-El Nio) has been distinguished as a unique large-scale ocean warming phenomenon happening in the central tropical Pacific that is quite different from the traditional El Nio. In this study, EOF analysis was used to successfully separate El Nio and El Nio Modoki. The abilities of the NINO3 index, NINO3.4 index, NINO1+2 index and NINO4 index in characterizing El Nio were explored in detail. The resulting suggestion was that, comparatively, NINO3 is the op...     

Similarities between optimal precursors for ENSO events and optimally growing initial errors in El Niño predictions

With the Zebiak–Cane model, the relationship between the optimal precursors (OPR) for triggering the El Niño/Southern Oscillation (ENSO) events and the optimally growing initial errors (OGE) to the uncertainty in El Niño predictions is investigated using an approach based on the conditional nonlinear optimal perturbation. The computed OPR for El Niño events possesses sea surface temperature anomalies (SSTA) dipole over the equatorial central and eastern Pacific, plus positive thermocline depth anomalies in the entire equatorial Pacific. Based on the El Niño events triggered by the obtained OPRs, the OGE which cause the largest prediction errors are computed. It is found that the OPR and OGE share great similarities in terms of localization and spatial structure of the SSTA dipole pattern over the central and eastern Pacific and the relatively uniform thermocline depth anomalies in the equatorial Pacific. The resemblances are possibly caused by the same mechanism of the Bjerknes positive feedback. It implies that if additional observation instruments are deployed to the targeted observations with limited coverage, they should preferentially be deployed in the equatorial central and eastern Pacific, which has been determined as the sensitive area for ENSO prediction, to better detect the early signals for ENSO events and reduce the initial errors so as to improve the forecast skill.     

Epochal changes in the seasonal evolution of tropical Indian Ocean warming associated with El Niño

The epochal changes in the seasonal evolution of El Niño induced tropical Indian Ocean (TIO) warming in the context of mid-1970s regime shift is investigated in this study. El Niño induced warming is delayed by one season in the northern TIO during epoch-2 (post mid-1970) and southern TIO during epoch-1 (pre mid-1970). Significant spatiotemporal changes in TIO (especially in the north) warming are apparent during the developing phase of El Niño. The ocean dynamics is the major driver in the basin wide warming during epoch-2 whereas heat fluxes are the dominant processes during epoch-1. Strong coupling between thermocline and sea surface temperature (SST) in epoch-2 indicates that El Niño induced oceanic changes are very significant in the seasonal evolution of basin-wide warming. The thermocline-SST coupling is strengthened by the upward propagating subsurface warming in epoch-2. The westward propagating barrier layer over southern TIO supports persistence of warm SST (over southwest TIO in epoch-2), which in turn induce spring asymmetric mode in winds and precipitation. The asymmetric wind pattern and persistent subsidence over maritime continent are primarily responsible for stronger spring warming in epoch-2. The strong east equatorial Indian Ocean cooling in epoch-2 is mainly driven by coastal upwelling over Java–Sumatra coast, whereas in epoch-1 the weak cooling is controlled by the latent heat flux. The spatiotemporal changes in TIO SST warming and their evolution have strong impact on atmospheric circulation and rainfall distribution over the Indian Oceanic rim through local air–sea interaction.     

Statistical relationship between two types of El Niño events and climate variation over the Korean Peninsula

Recently, a new type of El Niño (Warm-Pool El Niño) is more often observed than the conventional El Niño (Cold-Tongue El Niño); each has a distinctive spatial pattern. The two types of El Niño have different teleconnections; therefore their impacts on a specific region can be considerably different. In this study, we focus on statistical relationship between climate variation in Korea and the two types of El Niño. When the two types of El Niño are not separately considered, the statistical relation between climate variables in Korea and the El Niño events is weak in general. When the two types of El Niño are separately considered, however, each type exhibits significant relationship with climate variation in Korea. Therefore, consideration of two types of El Niño separately can potentially improve climate prediction over the Korean Peninsula.     

On the association between the recent episode of the quasi-biennial oscillation and the strong El Niño event

Theoretical and Applied Climatology - Andean tropical glaciers have shown a clear shrinkage throughout the last few decades. However, it is unclear how this general retreat is associated with...     

The El Niño Southern Oscillation and economic growth in the developing world

The El Niño Southern Oscillation (ENSO) affects weather around the globe, particularly in regions where developing countries typically lie. These countries are known to be most vulnerable to weather anomalies, and ENSO thereby has the potential to influence their economic growth. In this study, we investigate the effect of ENSO on economic growth in 69 developing countries, using annual data from 1961 to 2015. We find regime-dependent nonlinearity in the growth response to ENSO shocks. An El Niño event, equivalent to a 1 °C deviation in sea surface temperatures in the Niño3.4 region of the equatorial Pacific, results in one-to-two percent annual growth reduction during the El Niño regime, but the effect is absent during the La Niña regime. In addition, we find that the effect of El Niño is twice-as-large in the tropics relative to temperate areas, and particularly pronounced in Africa and Asia-Pacific. The findings of this study have two important implications. From the modeling standpoint, we find that the growth impacts of ENSO shocks are nonlinear, and vary across regions and climatic zones. From the policy-making standpoint, our findings suggest opportunities for short-term adjustments to climate shock management and international aid programs, depending on the existing state and the intermediate-term patterns of the ENSO cycle.     

Nonlinear precipitation response to El Niño and global warming in the Indo-Pacific

Precipitation changes over the Indo-Pacific during El Niño events are studied using an Atmospheric General Circulation Model forced with sea-surface temperature (SST) anomalies and changes in atmospheric CO₂ concentrations. Linear increases in the amplitude of the El Niño SST anomaly pattern trigger nonlinear changes in precipitation amounts, resulting in shifts in the location and orientation of the Intertropical Convergence Zone (ITCZ) and the South Pacific Convergence Zone (SPCZ). In particular, the maximum precipitation anomaly along the ITCZ and SPCZ shifts eastwards, the ITCZ shifts south towards the equator, and the SPCZ becomes more zonal. Precipitation in the equatorial Pacific also increases nonlinearly. The effect of increasing CO₂ levels and warming SSTs is also investigated. Global warming generally enhances the tropical Pacific precipitation response to El Niño. The precipitation response to El Niño is found to be dominated by changes in the atmospheric mean circulation dynamics, whereas the response to global warming is a balance between dynamic and thermodynamic changes. While the dependence of projected climate change impacts on seasonal variability is well-established, this study reveals that the impact of global warming on Pacific precipitation also depends strongly on the magnitude of the El Niño event. The magnitude and structure of the precipitation changes are also sensitive to the spatial structure of the global warming SST pattern.     

Factor analysis for El Niño signals in sea surface temperature and precipitation

Maximum likelihood factor analysis (MLFA) is applied to investigate the variables of monthly Tropical Pacific sea surface temperatures (SST) from Niño 1+2, Niño 3, Niño 3.4, and Niño 4 and precipitation over New South Wales and Queensland of eastern Australia, Kalimantan Island of Indonesia, and California and Oregon of the west coast of the United States. The monthly data used were from 1950 to 1999. The November-February SST with time leads of 0, 1, 2, and 3 months to precipitation are considered for both El Niño warm phases and non El Niño seasons. Interpretations of the factor loadings are made to diagnose relationships between the SST and precipitation variables. For El Niño signals, the rotated FA loadings can efficiently group the SST and precipitation variables with interpretable physical meanings. When the time lag is 0 or 1 month, the November–February El Niño SST explains much of the drought signals over eastern Australia and Kalimantan. However, when the time lag is 2 or 3 months, the same SST cannot adequately explain the precipitation during January–May over the two regions. Communality results of five factors for precipitation indicate nearly 100% explanation of variances for Queensland and California, but the percentages are reduced to only about 30% for Oregon and Kalimantan. Factor scores clearly identify the strongest El Niño relevant to precipitation variations. Principal component factor analysis (PCFA) is also investigated, and its results are compared with MLFA. The comparison indicates that MLFA can better group SST data relevant to precipitation. The residuals of MLFA are always smaller than the PCFA. Thus, MLFA may become a useful tool for improving potential predictability of precipitation from SST predictors.