scholarly journals Investigation of hydrological variability in the Korean Peninsula with the ENSO teleconnections

2016 ◽  
Vol 374 ◽  
pp. 165-173 ◽  
Author(s):  
Sunkwon Yoon ◽  
Taesam Lee
Keyword(s):  
El Niño ◽  
Korean Peninsula ◽  
El Nino ◽  
Southern Oscillation ◽  
Singular Spectrum Analysis ◽  
Warm Season ◽  
Principal Component ◽  
Lag Time ◽  
Climate Indices ◽  
Atmospheric Teleconnections

Abstract. This study analyzes nonlinear behavior links with atmospheric teleconnections between hydrologic variables and climate indices using statistical models during warm season (June to September) over the Korean Peninsula (KP). The ocean-related major climate factor, which is the El Niño-Southern Oscillation (ENSO) was used to analyze the atmospheric teleconnections by principal component analysis (PCA) and a singular spectrum analysis (SSA). The nonlinear lag time correlations between climate indices and hydrologic variables are calculated by Mutual Information (MI) technique. The nonlinear correlation coefficients (CCs) by MI were higher than linear CCs, and ENSO shows a few months of lag time correlation. The warm season hydrologic variables in KP shows a significant increasing tendency during the warm pool (WP), and the cold tongue (CT) El Niño decaying years shows a significant decreasing tendency, while the La Niña year shows slightly above normal conditions, respectively. A better understanding of the relationship between climate indices and streamflow, and their local impacts can help to prepare for the river discharge management by water managers and scientists. Furthermore, these results provide useful data for policy makers and end-users to support long-range water resources prediction and water-related policy.

scholarly journals Hydrometeorological Variability and Its Nonstationarity According to the Evolution Pattern of Indian Ocean Dipole over the East Asia Region

2020 ◽  
Author(s):  
Jong-Suk Kim ◽  
Sun-Kwon Yoon ◽  
Sang-Myeong Oh
Keyword(s):  
Indian Ocean ◽  
East Asia ◽  
Indian Ocean Dipole ◽  
Singular Spectrum Analysis ◽  
Warm Season ◽  
Principal Component ◽  
Lag Time ◽  
Meteorological Variables ◽  
Climate Indices ◽  
Atmospheric Teleconnections

In this study, we used statistical models to analyze nonlinear behavior links with atmospheric teleconnections between hydrometeorological variables and Indian Ocean Dipole (IOD) mode over the East Asia (EA) region. The analysis of atmospheric teleconnections was conducted using principal component analysis and singular spectrum analysis techniques. Moreover, the nonlinear lag-time correlations between climate indices and hydrological variables were calculated using mutual information (MI) techniques. The teleconnection-based nonlinear correlation coefficients (CCs) were higher than the linear CCs in each lag time. Additionally, we documented that the IOD has a direct influence on hydro-meteorological variables, such as precipitation within the Korean Peninsula (KP). Moreover, during the warm season (June to September) the variation of hydro-meteorological variables in the KP demonstrated significantly decreasing patterns during positive IOD years and they have neutral conditions during negative IOD years in comparison with long-term normal conditions. Finally, the revealed relationship between climate indices and hydro-meteorological variables and their possible changes will allow better understanding of stakeholder decision-making regarding to manage of freshwater management over the EA region. It can also provide useful data for long-range water resources prediction, to minimize hydrological uncertainties in a changing climate.

scholarly journals Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

2017 ◽  
Author(s):  
Eric Mortensen ◽  
Shu Wu ◽  
Michael Notaro ◽  
Steven Vavrus ◽  
Rob Montgomery ◽  
...  
Keyword(s):  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Local Level ◽  
Principal Component ◽  
Spatiotemporal Variability ◽  
Climate Indices ◽  
Southern Peru ◽  
Drought Prediction

Abstract. Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semi-arid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal drought. Droughts here are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region’s hydrologic cycle. An extensive season-ahead drought prediction model is developed to help bolster existing capacity of stakeholders to plan for and mitigate the deleterious impacts of this hydrologic extreme. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to eleven potential predictors to produce an ensemble forecast of January-March precipitation. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. Extending the lead time and spatially disaggregating precipitation predictions to the local level may further assist regional stakeholders and policymakers preparing for drought.

scholarly journals Teleconnections between Monthly Rainfall Variability and Large-Scale Climate Indices in Southwestern Colombia

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1863 ◽  
Author(s):  
Teresita Canchala ◽  
Wilfredo Alfonso-Morales ◽  
Wilmar Loaiza Cerón ◽  
Yesid Carvajal-Escobar ◽  
Eduardo Caicedo-Bravo
Keyword(s):  
Water Resources ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Monthly Rainfall ◽  
Wavelet Coherence ◽  
Climate Indices ◽  
Annual Scale ◽  
Wavelet Coherence Analysis

Given that the analysis of past monthly rainfall variability is highly relevant for the adequate management of water resources, the relationship between the climate-oceanographic indices, and the variability of monthly rainfall in Southwestern Colombia at different time scales was chosen as the research topic. It should also be noted that little-to-no research has been carried out on this topic before. For the purpose of conducting this research, we identified homogeneous rainfall regions while using Non-Linear Principal Component Analysis (NLPCA) and Self-Organizing Maps (SOM). The rainfall variability modes were obtained from the NLPCA, while their teleconnection in relation to the climate indices was obtained from Pearson’s Correlations and Wavelet Transform. The regionalization process clarified that Nariño has two regions: the Andean Region (AR) and the Pacific Region (PR). The NLPCA showed two modes for the AR, and one for the PR, with an explained variance of 75% and 48%, respectively. The correlation analyses between the first nonlinear components of AR and PR regarding climate indices showed AR high significant positive correlations with Southern Oscillation Index (SOI) index and negative correlations with El Niño/Southern Oscillation (ENSO) indices. PR showed positive ones with Niño1 + 2, and Niño3, and negative correlations with Niño3.4 and Niño4, although their synchronous relationships were not statistically significant. The Wavelet Coherence analysis showed that the variability of the AR rainfall was influenced principally by the Niño3.4 index on the 3–7-year inter-annual scale, while PR rainfall were influenced by the Niño3 index on the 1.5–3-year inter-annual scale. The El Niño (EN) events lead to a decrease and increase in the monthly rainfall on AR and PR, respectively, while, in the La Niña (LN) events, the opposite occurred. These results that are not documented in previous studies are useful for the forecasting of monthly rainfall and the planning of water resources in the area of study.

scholarly journals Precipitação na América do Sul: Médias Climáticas e Padrões da Variabilidade no Período entre 1979 e 2008

2016 ◽  
Vol 9 (1) ◽  
pp. 032
Author(s):  
Éder Leandro Maier ◽  
Juliana Costi ◽  
Sandra Barreira ◽  
Jefferson Cardia Simões
Keyword(s):  
South America ◽  
North Atlantic ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Principal Component ◽  
Monthly Precipitation ◽  
Tropical Regions ◽  
The North ◽  
North Atlantic Variability

Este artigo discute os principais padrões médios e anômalos da precipitação sobre a América do Sul no período 1979–2008. Para isso foram manipulados dados mensais da precipitação observada em 890 estações meteorológicas localizadas na Argentina, Bolívia, Brasil, Paraguai e Uruguai ao longo desse período de trinta anos. As médias climáticas foram subtraídas das amostras, originando as anomalias, as quais foram agrupadas por meio da Análise das Componentes Principais em dois modos. No modo T se identificou 6 componentes principais, que explicam 35% da variância e representam 12 padrões espaciais anômalos originados, principalmente, pelo fenômeno El Niño–Oscilação Sul (ENOS) e pela variabilidade do Atlântico Norte. No modo S foram identificadas 8 zonas em que a variabilidade temporal das séries anômalas é semelhante, sendo que o ENOS prevalece no controle das anomalias nas zonas situadas na região equatorial e extratropical, além disso, a variabilidade do Atlântico Norte pode maximizar ou minimizar os impactos do ENOS. A frequência de recorrência desses estresses hídrico variam entre 20 e 60 meses.  This article discusses mean and anomalous rainfall patterns over South America in the period 1979–2008. For that we handled monthly precipitation data observed at 890 meteorological stations located in Argentina, Bolivia, Brazil, Paraguay and Uruguay over this thirty years period. Climatic means were subtracted from the data, resulting in anomalies that were grouped by Principal Component Analysis in two modes. We identified 6 main components in the T mode, which explain 35% of the variance and represent 12 anomalous spatial patterns originated mainly by El Niño–Southern Oscillation (ENSO) phenomenon and the North Atlantic variability. In mode S, we identified eight zones where the series temporal variability is also anomalous, and the ENOS prevails as the anomalies controller in the equatorial and extra tropical regions. Further, North Atlantic variability may maximize or minimize the ENSO impact. The frequency of these recurrent water stresses range from 20 to 60 months. Keywords: Precipitation, South America, PCA  

scholarly journals Variation in Seasonal Precipitation over Gaza (Palestine) and Its Sensitivity to Teleconnection Patterns

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 667
Author(s):  
Salah Basem Ajjur ◽  
Sami G. Al-Ghamdi
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Winter Precipitation ◽  
Climate Indices ◽  
Seasonal Precipitation ◽  
Teleconnection Patterns ◽  
Mitigation And Adaptation ◽  
Set Up ◽  
Mitigation And Adaptation Strategies

The seasonal precipitation (SP) trend and its sensitivity to teleconnection patterns over the East Mediterranean (EM) region remain inconsistent. Based on rainfall records during 1974–2016 at seven meteorological stations in the Gaza region, this study aims to (1) analyze the observed SP trend over the Gaza region, and (2) examine the SP sensitivity to climate indices. Pearson and Spearman correlations between climate indices and SP in the current and following years were calculated, and the seasonal period (particular month) with the highest correlation was identified. Results show that the climate indices, with greater impact on SP over the Gaza region in the autumn and spring, were in the order; El Niño-Southern Oscillation (ENSO) > East Atlantic/Western Russia (EAWR) > North Atlantic Oscillation (NAO) > Arctic Oscillation (AO). The indices’ impact was minimal in the winter precipitation. ENSO types’ correlations (Southern Oscillation Index-SOI and Niño 3.4) were moderate and significant at α = 0.05. Rainfall at most stations positively correlates with AO and EAWR in spring and autumn. During the study period, warm phases of ENSO (i.e., El Niño) intensified autumn precipitation. Simultaneously with warm phases of EAWR or AO, more influence on autumn precipitation is exerted. Cold phases of ENSO (i.e., La Niña) have an adverse impact compared to El Niño. EAWR co-variation was evident only with the ENSO. Regarding AO, a non-meaningful action was noticed during the neutral phases of ENSO and EAWR. The findings of this study help understand and predict the seasonal trend of precipitation over the Gaza region. This is essential to set up climate change mitigation and adaptation strategies in the EM region.

scholarly journals Teleconnection Between ENSO and Wind-Wave Climate Under the Influence of Monsoon in the Bay of Bengal Region

2020 ◽  
Vol 15 (3) ◽  
pp. 463-469
Author(s):  
Mourani Sinha ◽  
Amitava Jana
Keyword(s):  
Bay Of Bengal ◽  
El Niño ◽  
Wind Wave ◽  
El Nino ◽  
Southern Oscillation ◽  
Function Analysis ◽  
Deep Ocean ◽  
Principal Component ◽  
Wavelet Coherence ◽  
Enso Indices

Wind-wave parameters like the significant wave height (SWH)impacts considerably deep ocean and maritime activities and lives of all those dwelling near the coast.Prediction of such a parameter has immense utility during extreme conditions. Teleconnection features are explored between the most widely studied climate mode, the El Niño-Southern Oscillation or ENSO and the SWHparameter in the Bay of Bengal (BB) region under the influence of monsoon in this study.In two separate experiments the SWH data of the BB region for the period 1958-2001 and the period 2006-2016 is subjected to empirical orthogonal function analysis to split the data into spatial and temporal parts.The temporal variations are of annual periodicity for both the data sets. On analysis teleconnection feature of lower (higher) SWH during El Niño (La Niña) episodes is observed in the BB region. Significant correlationis observed between SWH and the ENSO indices during the summer monsoon months.The continuous wavelet power spectrum is generated using the first principal component (PC1) extracted above. It exhibits significant regions in the 0.5-1 year band resembling the monsoon variability in the BB region. To determine how SWH is related to the ENSO indices wavelet coherence is applied for the BB region.The higher coherency regions are found in the 0.5-1 year band which maybe related to the monsoon oscillation having similar periodicity. Thus the SWH and ENSO relationship in the BB region is influenced by the monsoon significantly.

scholarly journals ENSO dynamics in current climate models: an investigation using nonlinear dimensionality reduction

2008 ◽  
Vol 15 (2) ◽  
pp. 339-363 ◽  
Author(s):  
I. Ross ◽  
P. J. Valdes ◽  
S. Wiggins
Keyword(s):  
Principal Component Analysis ◽  
Data Analysis ◽  
Dimensionality Reduction ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Principal Component ◽  
Component Analysis ◽  
Nonlinear Dimensionality Reduction ◽  
Climate Data

Abstract. Linear dimensionality reduction techniques, notably principal component analysis, are widely used in climate data analysis as a means to aid in the interpretation of datasets of high dimensionality. These linear methods may not be appropriate for the analysis of data arising from nonlinear processes occurring in the climate system. Numerous techniques for nonlinear dimensionality reduction have been developed recently that may provide a potentially useful tool for the identification of low-dimensional manifolds in climate data sets arising from nonlinear dynamics. Here, we apply Isomap, one such technique, to the study of El Niño/Southern Oscillation variability in tropical Pacific sea surface temperatures, comparing observational data with simulations from a number of current coupled atmosphere-ocean general circulation models. We use Isomap to examine El Niño variability in the different datasets and assess the suitability of the Isomap approach for climate data analysis. We conclude that, for the application presented here, analysis using Isomap does not provide additional information beyond that already provided by principal component analysis.

scholarly journals Functional Data Visualization and Outlier Detection on the Anomaly of El Niño Southern Oscillation

Climate ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 118
Author(s):  
Jamaludin Suhaila
Keyword(s):  
El Niño ◽  
Functional Data ◽  
El Nino ◽  
Southern Oscillation ◽  
Principal Component ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Sufficient Information ◽  
Main Research ◽  
Enso Index

The El Niño Southern Oscillation (ENSO) is a well-known cause of year-to-year climatic variations on Earth. Floods, droughts, and other natural disasters have been linked to the ENSO in various parts of the world. Hence, modeling the ENSO’s effects and the anomaly of the ENSO phenomenon has become a main research interest. Statistical methods, including linear and nonlinear models, have intensively been used in modeling the ENSO index. However, these models are unable to capture sufficient information on ENSO index variability, particularly on its temporal aspects. Hence, this study adopted functional data analysis theory by representing a multivariate ENSO index (MEI) as functional data in climate applications. This study included the functional principal component, which is purposefully designed to find new functions that reveal the most important type of variation in the MEI curve. Simultaneously, graphical methods were also used to visualize functional data and capture outliers that may not have been apparent from the original data plot. The findings suggest that the outliers obtained from the functional plot are then related to the El Niño and La Niña phenomena. In conclusion, the functional framework was found to be more flexible in representing the climate phenomenon as a whole.

scholarly journals Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

2018 ◽  
Vol 22 (1) ◽  
pp. 287-303 ◽  
Author(s):  
Eric Mortensen ◽  
Shu Wu ◽  
Michael Notaro ◽  
Stephen Vavrus ◽  
Rob Montgomery ◽  
...  
Keyword(s):  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Local Level ◽  
Spatiotemporal Variability ◽  
Semiarid Region ◽  
Climate Indices ◽  
Southern Peru ◽  
Drought Prediction

Abstract. Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semiarid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal meteorological drought. Meteorological droughts in this region are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region's hydrologic cycle. An extensive season-ahead precipitation prediction model is developed to help bolster the existing capacity of stakeholders to plan for and mitigate deleterious impacts of drought. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to 11 potential predictors to produce an ensemble forecast of regional January–March precipitation totals. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño–Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit–miss statistic. The information provided by the developed model and ancillary modeling efforts, such as extending the lead time of and spatially disaggregating precipitation predictions to the local level as well as forecasting the number of wet–dry days per rainy season, may further assist regional stakeholders and policymakers in preparing for drought.

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