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 Streamflow Variability in Colombian Pacific Basins and Their Teleconnections with Climate Indices

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 526 ◽  
Author(s):  
Teresita Canchala ◽  
Wilmar Loaiza Cerón ◽  
Félix Francés ◽  
Yesid Carvajal-Escobar ◽  
Rita Andreoli ◽  
...  
Keyword(s):  
River Basin ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Wavelet Coherence ◽  
Climate Indices ◽  
Decadal Scale ◽  
Streamflow Variability ◽  
Wavelet Coherence Analysis ◽  
Colombian Pacific

Oceanic-atmospheric phenomena of different time scales concurrently might affect the streamflow in several basins around the world. The Atrato River Basin (ARB) and Patía River Basin (PRB) of the Colombian Pacific region are examples of such basins. Nevertheless, the relations between the streamflows in the ARB and PRB and the oceanic-atmospheric factors have not been examined considering different temporal scales. Hence, this article studies the relations of the climate indices and the variability of the streamflows in the ARB and PRB at interannual and decadal timescales. To this, the streamflow variability modes were obtained from the principal component analysis (PCA); furthermore, their linear dependence with indices of the El Niño/Southern Oscillation (ENSO), precipitation (PRP), the Choco low-level jet (CJ), and other indices were quantified through (a) Pearson and Kendall’s tau correlations, and (b) wavelet transform. The PCA presented a single significant mode for each basin, with an explained variance of around 80%. The correlation analyses between the PC1s of the ARB and PRB, and the climate indices showed significant positive (negative) high correlations with PRP, CJ, and Southern Oscillation Index (SOI) (ENSO indices). The wavelet coherence analysis showed significant coherencies between ENSO and ARB: at interannual (2–7 years) and decadal scale (8–14), preferably with the sea surface temperature (SST) in the east and west Tropical Pacific Ocean (TPO). For PRB with the SST in the central and western regions of the TPO in the interannual (4–8 years) and decadal (8–14 years) scales, the decreases (increases) in streamflow precede the El Niño (La Niña) events. These results indicate multiscale relations between the basins’ streamflow and climate phenomena not documented in previous works, relevant to forecast the extreme flow events in the Colombian Pacific rivers and for planning and implementing strategies for the sustainable use of water resources in the basins studied.

scholarly journals Spatio-Temporal Variability of Malaria Infection in Chahbahar County, Iran: Association with the ENSO and Rainfall Variability

2020 ◽  
Author(s):  
S. M. J Nazemosadat ◽  
R Shafiei ◽  
H Ghaedamini ◽  
M Najjari ◽  
Z Nazemosadat ◽  
...  
Keyword(s):  
El Niño ◽  
Urban Areas ◽  
El Nino ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Health Indicators ◽  
Climate Indices ◽  
Patient Number ◽  
Significant Difference ◽  
Spatio Temporal

Abstract Background: Malaria is one of the most widespread communicable diseases in the southeast of Iran particularly in Chahbahar County. Comprehensive understanding of the influence of climate on this disease is a key element for success in the environmental-based malaria elimination programs. After analyzing the spatio-temporal distribution of the disease, the relationships between the infection statistics and some important climate indices particularly the El Niño-Southern Oscillation (ENSO) and rainfall were investigated.Methods: The malaria statistics collected from various health centers were composited with the corresponding data of Southern Oscillation Index (SOI), ground-based meteorological records and satellite-based rainfall data. Non-parametric Mann-whitely test was applied to detect the significant difference between patient number between El Niño and La Niña and between the adopted wet and dry episodes.Findings: Patient number from highest to lowest was associated to summer, autumn, spring and winter, respectively. Plasmodium falciparum, Plasmodium vivax and other species were responsible for 22%, 75% and 3% of the sickness, respectively. While the outbreak of P. falciparum is in autumn; P. vivax is erupted in summer. When the epidemic statistics were collected from rural rather than urban areas, the effect of climate on the infection statistic was more obvious.Interpretation: For rural / urban areas, the infection statistics exhibited a significant decline / increase during El Niño episodes. In autumn, spring and winter, patient number has significantly increased / decreased during the dry / wet epochs, respectively. These relationships were, however, reversed during summertime of health indicators are rarely available for every population and period of interest, and available data.Funding: Shiraz University of Medical Sciences

scholarly journals Spatio-Temporal Variability of Malaria Infection in Chahbahar County, Iran: Association with the ENSO and Rainfall Variability

2021 ◽  
Author(s):  
Seyed Mohammad Jafar Nazemosadat ◽  
Reza Shafiei ◽  
Habib Ghaedamini ◽  
Mohsen Najjari ◽  
Zahra Nazemosadat ◽  
...  
Keyword(s):  
El Niño ◽  
Urban Areas ◽  
El Nino ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Health Indicators ◽  
Climate Indices ◽  
Patient Number ◽  
Significant Difference ◽  
Spatio Temporal

Abstract Malaria is one of the most widespread communicable diseases in the southeast of Iran particularly in Chahbahar County. Comprehensive understanding of the influence of climate on this disease is a key element for success in the environmental-based malaria elimination programs. After analyzing the spatio-temporal distribution of the disease, the relationships between the infection statistics and some important climate indices particularly the El Niño-Southern Oscillation (ENSO) and rainfall were investigated.The malaria statistics collected from various health centers were composited with the corresponding data of Southern Oscillation Index (SOI), ground-based meteorological records and satellite-based rainfall data. Non-parametric Mann-whitely test was applied to detect the significant difference between patient number between El Niño and La Niña and between the adopted wet and dry episodes. Patient number from highest to lowest was associated to summer, autumn, spring and winter, respectively. Plasmodium falciparum, Plasmodium vivax and other species were responsible for 22%, 75% and 3% of the sickness, respectively. While the outbreak of P. falciparum is in autumn; P. vivax is erupted in summer. When the epidemic statistics were collected from rural rather than urban areas, the effect of climate on the infection statistic was more obvious. Interpretation: For rural / urban areas, the infection statistics exhibited a significant decline / increase during El Niño episodes. In autumn, spring and winter, patient number has significantly increased / decreased during the dry / wet epochs, respectively. These relationships were, however, reversed during summertime of health indicators are rarely available for every population and period of interest, and available data.

Classification of El Niño and La Niña years for water resources management in Alberta

2018 ◽  
Vol 45 (12) ◽  
pp. 1093-1098
Author(s):  
Zahidul Islam
Keyword(s):  
Water Resources ◽  
Water Resources Management ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
La Niña ◽  
Simple Method ◽  
Resources Management ◽  
La Nina

Classification of El Niño and La Niña years in a historical time period is necessary to analyze their impacts on hydrology and water resources management. In this study, various El Niño-Southern Oscillation (ENSO) indices, and how they are used to classify El Niño or La Niña years have been reviewed. Based on the review, a simple method of classifying El Niño or La Niña years has been proposed.

scholarly journals The influence of El Niño–Southern Oscillation regimes on eastern African vegetation and its future implications under the RCP8.5 warming scenario

2017 ◽  
Vol 14 (18) ◽  
pp. 4355-4374 ◽  
Author(s):  
Istem Fer ◽  
Britta Tietjen ◽  
Florian Jeltsch ◽  
Christian Wolff
Keyword(s):  
Climate Change ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Future Climate ◽  
Future Climate Change ◽  
El Nino Southern Oscillation ◽  
Vegetation Response ◽  
African Rainfall

Abstract. The El Niño–Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature–eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.

scholarly journals El Niño Southern Oscillation as an early warning tool for dengue outbreak in India

2020 ◽  
Author(s):  
Malay K. Pramanik ◽  
Poonam Singh ◽  
Gaurav Kumar ◽  
Vijay Prakash Ojha ◽  
Ramesh C. Dhiman
Keyword(s):  
Spatial Correlation ◽  
Negative Correlation ◽  
Early Warning ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
State Level ◽  
Monthly Rainfall ◽  
Dengue Case ◽  
Rainfall Index

Abstract Background: Dengue is rapidly expanding climate-sensitive mosquito-borne disease worldwide. Outbreaks of dengue occur in various parts of India as well but there is no tool to provide early warning. The current study was, therefore, undertaken to find out the link between El Niño, precipitation, and dengue cases, which could help in early preparedness for control of dengue.Methods: Data on Oceanic Niño Index (ONI) was extracted from CPC-IRI (USA) while the data on monthly rainfall was procured from India Meteorological Department. Data on annual dengue cases was taken from the website of National Vector Borne Disease Control Programme (NVBDCP). Correlation analysis was used to analyse the relationship between seasonal positive ONI, rainfall index and dengue case index based on past 20 years’ state-level data. The dengue case index representing ‘relative deviation from mean’ was correlated to the three months average ONI. The computed r values of dengue case index and positive ONI were further interpreted using GIS software to generate spatial correlation map. The short-term (1 year) prediction of dengue probability map has been prepared based on phase-wise (El Niño, La Niña, and Neutral) 20 years averaged ONI.Results: A high correlation between positive ONI and dengue incidence was found, particularly in the states of Arunachal Pradesh, Chhattisgarh, Haryana, Uttarakhand, Andaman and Nicobar Islands, Delhi, Daman and Diu. On the other hand, the states like Assam, Himachal Pradesh, Meghalaya, Manipur, Mizoram, Jammu & Kashmir, Uttar Pradesh, Orissa, and Andhra Pradesh shown negative correlation between summer El Niño and dengue incidence. Two –three month lag was found between monthly ‘rainfall index’ and dengue cases at local-scale analysis.Conclusion: The generated map signifies the spatial correlation between positive ONI and dengue case index, indicating positive correlation in the central part, while negative correlation in some coastal, northern, and north-eastern part of India. The findings offer a tool for early preparedness for undertaking intervention measures against dengue by the national programme at state level. For further improvement of results, study at micro-scale (district) for finding month-wise association with Indian Ocean Dipole and local weather variables is desired for better explanation of dengue outbreaks in the states with ‘no association’.

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