scholarly journals A Hierarchy of Data-Based ENSO Models

2005 ◽  
Vol 18 (21) ◽  
pp. 4425-4444 ◽  
Author(s):  
D. Kondrashov ◽  
S. Kravtsov ◽  
A. W. Robertson ◽  
M. Ghil
Keyword(s):  
El Niño ◽  
Additive Noise ◽  
Polynomial Regression ◽  
El Nino ◽  
Southern Oscillation ◽  
Model Performance ◽  
Empirical Orthogonal Functions ◽  
Quadratic Model ◽  
Orthogonal Functions ◽  
Optimizing Model

Abstract Global sea surface temperature (SST) evolution is analyzed by constructing predictive models that best describe the dataset’s statistics. These inverse models assume that the system’s variability is driven by spatially coherent, additive noise that is white in time and are constructed in the phase space of the dataset’s leading empirical orthogonal functions. Multiple linear regression has been widely used to obtain inverse stochastic models; it is generalized here in two ways. First, the dynamics is allowed to be nonlinear by using polynomial regression. Second, a multilevel extension of classic regression allows the additive noise to be correlated in time; to do so, the residual stochastic forcing at a given level is modeled as a function of variables at this level and the preceding ones. The number of variables, as well as the order of nonlinearity, is determined by optimizing model performance. The two-level linear and quadratic models have a better El Niño–Southern Oscillation (ENSO) hindcast skill than their one-level counterparts. Estimates of skewness and kurtosis of the models’ simulated Niño-3 index reveal that the quadratic model reproduces better the observed asymmetry between the positive El Niño and negative La Niña events. The benefits of the quadratic model are less clear in terms of its overall, cross-validated hindcast skill; this model outperforms, however, the linear one in predicting the magnitude of extreme SST anomalies. Seasonal ENSO dependence is captured by incorporating additive, as well as multiplicative forcing with a 12-month period into the first level of each model. The quasi-quadrennial ENSO oscillatory mode is robustly simulated by all models. The “spring barrier” of ENSO forecast skill is explained by Floquet and singular vector analysis, which show that the leading ENSO mode becomes strongly damped in summer, while nonnormal optimum growth has a strong peak in December.

scholarly journals Association of Taiwan’s Rainfall Patterns with Large-Scale Oceanic and Atmospheric Phenomena

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Yi-Chun Kuo ◽  
Ming-An Lee ◽  
Mong-Ming Lu
Keyword(s):  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Geographic Location ◽  
Empirical Orthogonal Functions ◽  
Mountainous Area ◽  
Mountain Range ◽  
Spatial Variance ◽  
Orthogonal Functions

A 50-year (1960–2009) monthly rainfall gridded dataset produced by the Taiwan Climate Change Projection and Information Platform Project was presented in this study. The gridded data (5 × 5 km) displayed influence of topography on spatial variability of rainfall, and the results of the empirical orthogonal functions (EOFs) analysis revealed the patterns associated with the large-scale sea surface temperature variability over Pacific. The first mode (65%) revealed the annual peaks of large rainfall in the southwestern mountainous area, which is associated with southwest monsoons and typhoons during summertime. The second temporal EOF mode (16%) revealed the rainfall variance associated with the monsoon and its interaction with the slopes of the mountain range. This pattern is the major contributor to spatial variance of rainfall in Taiwan, as indicated by the first mode (40%) of spatial variance EOF analysis. The second temporal EOF mode correlated with the El Niño Southern Oscillation (ENSO). In particular, during the autumn of the La Niña years following the strong El Niño years, the time-varying amplitude was substantially greater than that of normal years. The third temporal EOF mode (7%) revealed a north-south out-of-phase rainfall pattern, the slowly evolving variations of which were in phase with the Pacific Decadal Oscillation. Because of Taiwan’s geographic location and the effect of local terrestrial structures, climate variability related to ENSO differed markedly from other regions in East Asia.

scholarly journals Prediction of Seasonal Forest Fire Severity in Canada from Large-Scale Climate Patterns

2011 ◽  
Vol 50 (4) ◽  
pp. 785-799 ◽  
Author(s):  
Amir Shabbar ◽  
Walter Skinner ◽  
Mike D. Flannigan
Keyword(s):  
Forest Fire ◽  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Fire Severity ◽  
Model Performance ◽  
Drought Severity ◽  
Percent Correct ◽  
Prairie Provinces

AbstractAn empirical scheme for predicting the meteorological conditions that lead to summer forest fire severity for Canada using the multivariate singular value decomposition (SVD) has been developed for the 1953–2007 period. The levels and sources of predictive skill have been estimated using a cross-validation design. The predictor fields are global sea surface temperatures (SST) and Palmer drought severity index. Two consecutive 3-month predictor periods are used to detect evolving conditions in the predictor fields. Correlation, mean absolute error, and percent correct verification statistics are used to assess forecast model performance. Nationally averaged skills are shown to be statistically significant, which suggests that they are suitable for application to forest fire prediction and for management purposes. These forecasts average a 0.33 correlation skill across Canada and greater than 0.6 in the forested regions from the Yukon, through northern Prairie Provinces, northern Ontario, and central Quebec into Newfoundland. SVD forecasts generally outperform persistence forecasts. The importance of the leading two SVD modes to Canadian summer forest fire severity, accounting for approximately 95% of the squared covariance, is emphasized. The first mode relates strongly to interdecadal trend in global SST. Between 1953 and 2007 the western tropical Pacific, the Indian, and the North Atlantic Oceans have tended to warm while the northeastern Pacific and the extreme Southern Hemisphere oceans have shown a cooling trend. During the same period, summer forest fire exhibited increased severity across the large boreal forest region of Canada. The SVD diagnostics also indicate that the El Niño–Southern Oscillation and the Pacific decadal oscillation play a significant role in Canadian fire severity. Warm episodes (El Niño) tend to be associated with severe fire conditions over the Yukon, parts of the northern Prairie Provinces, and central Quebec. The linearity of the SVD manifests opposite response during the cold (La Niña) events.

scholarly journals A Dynamically Consistent Reconstruction of Ocean Temperature

2017 ◽  
Vol 34 (5) ◽  
pp. 1061-1082 ◽  
Author(s):  
Samuel S. P. Shen ◽  
Gregory P. Behm ◽  
Y. Tony Song ◽  
Tangdong Qu
Keyword(s):  
El Niño ◽  
General Circulation ◽  
El Nino ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Empirical Orthogonal Functions ◽  
Global Ocean ◽  
Reconstruction Method ◽  
Ocean Temperature ◽  
Orthogonal Functions

AbstractThis paper provides a spectral optimal gridding (SOG) method to make a dynamically consistent reconstruction of water temperature for the global ocean at different depth levels. The dynamical consistency is achieved by using the basis of empirical orthogonal functions (EOFs) derived from NASA Jet Propulsion Laboratory (JPL) non-Boussinesq ocean general circulation model (OGCM) output at ¼° resolution from 1958 to 2013. A convenient singular value decomposition (SVD) method is used to calculate the EOFs, in order to enable efficient computing for a fine spatial grid globally. These EOFs are used as explainable variables and are regressed against the sparsely distributed in situ ocean temperature data at 33 standard depth levels. The observed data are aggregated onto a 1° latitude–longitude grid at each level from the surface to the 5500-m layer for the period 1950–2014. Three representative temperature reconstruction examples are presented and validated: two 10-m-layer (i.e., the second layer from the surface) reconstructions for January 2008 and January 1998, which are compared with independent sea surface temperature (SST) observations; and one 100-m-layer reconstruction for January 1998, which shows a strong cold anomaly El Niño signal in the western tropical Pacific up to −5°C from 150°E to 140°W. The SOG reconstruction can accurately locate the El Niño signal region in different ocean layers. The SOG reconstruction method is shown reliable and yields satisfactory accuracy even with sparse data. Validation and error analysis indicate that no systematic biases exist in the observed and reconstructed data.

VARIABILIDAD CLIMÁTICA, CAMBIO CLIMÁTICO Y PESQUERÍAS EN EL ECUADOR.

2012 ◽  
Vol 1 (1) ◽  
Author(s):  
Johnny Chavarría Viteri ◽  
Dennis Tomalá Solano
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Pacific Decadal Oscillation ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Current Action ◽  
Palabras Clave

La variabilidad climática es la norma que ha modulado la vida en el planeta. Este trabajo demuestra que las pesquerías y acuicultura costera ecuatorianas no son la excepción, puesto que tales actividades están fuertemente influenciadas por la variabilidad ENSO (El Niño-Oscilación del Sur) y PDO (Oscilación Decadal del Pacífico), planteándose que la señal del cambio climático debe contribuir a esta influencia. Se destaca también que, en el análisis de los efectos de la variabilidad climática sobre los recursos pesqueros, el esfuerzo extractivo también debe ser considerado. Por su parte, la acción actual de la PDO está afectando la señal del cambio climático, encontrándose actualmente en fases opuestas. Se espera que estas señales entren en fase a finales de esta década, y principalmente durante la década de los 20 y consecuentemente se evidencien con mayor fuerza los efectos del Cambio Climático. Palabras Clave: Variabilidad Climática, Cambio Climático, ENSO, PDO, Pesquerías, Ecuador. ABSTRACT Climate variability is the standard that has modulated life in the planet. This work shows that the Ecuadorian  fisheries and aquaculture are not the exception, since such activities are strongly influenced by ENSO variability (El Niño - Southern Oscillation) and PDO (Pacific Decadal Oscillation), considering that the signal of climate change should contribute to this influence. It also emphasizes that in the analysis of the effects of climate variability on the fishing resources, the extractive effort must also be considered. For its part, the current action of the PDO is affecting the signal of climate change, now found on opposite phases. It is hoped that these signals come into phase at the end of this decade, and especially during the decade of the 20’s and more strongly evidencing the effects of climate change. Keywords: Climate variability, climate change, ENSO (El Niño - Southern Oscillation) and PDO  (Pacific Decadal Oscillation); fisheries, Ecuador. Recibido: mayo, 2012Aprobado: agosto, 2012

Rendimento de grãos de soja e de milho, no Rio Grande do Sul, não difere entre eventos El Niño Oscilação Sul

Agrometeoros ◽  
2018 ◽  
Vol 26 (1) ◽  
Author(s):  
Ronaldo Matzenauer ◽  
Bernadete Radin ◽  
Alberto Cargnelutti Filho
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Rio Grande ◽  
La Niña ◽  
Rio Grande Do Sul ◽  
La Nina ◽  
Significant Difference ◽  
Income Data ◽  
The Relationship

O objetivo deste trabalho foi avaliar a relação entre o fenômeno El Niño Oscilação Sul - ENOS e o rendimento de grãos de soja e de milho no Rio Grande do Sul e verificar a hipótese de que os eventos El Niño são favoráveis e os eventos La Niña são prejudiciais ao rendimento de grãos das culturas. Foram utilizados dados de rendimento de grãos dos anos agrícolas de 1974/75 a 2016/17, e relacionados com as ocorrências de eventos ENOS. Foram analisados os dados de rendimento observados na colheita e os dados estimados com a remoção da tendência tecnológica. Os resultados mostraram que não houve diferença significativa do rendimento médio de grãos de soja e de milho na comparação entre os eventos ENOS. Palavras-chave: El Niño, La Niña, safras agrícolas. Abstract – The objective of this work was to evaluate the relationship between the El Niño Southern Oscillation (ENSO) phenomenon with the grain yield of soybean and maize in Rio Grande do Sul state, Brazil and to verify the hypothesis that the El Niño events are favorable and the La Niña events are harmful to the culture’s grain yields. Were used data from the agricultural years of 1974/75 to 2016/17, and related to the occurrence of ENOS events. We analyzed income data observed at harvest and estimated data with technological tendency was removed. The results showed that there was no significant difference in the average yield of soybeans and corn in the comparison between events.

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