scholarly journals The El Niño–Southern Oscillation and the Transatlantic Slave Trade

2021 ◽  
Keyword(s):  
El Niño ◽  
Slave Trade ◽  
El Nino ◽  
Southern Oscillation ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Transatlantic Slave Trade ◽  
African Rainfall ◽  
Induced Changes ◽  
Enso Index

Abstract The relationship between the El Niño-Southern Oscillation (ENSO) and the Transatlantic Slave Trade (TAST) is examined using the Slave Voyages dataset and a reconstructed ENSO index. The ENSO index is used as a proxy for West African rainfall and temperature. In the Sahel, the El Niño (warm) phase of ENSO is associated with less rainfall and warmer temperatures, whereas the La Niña (cold) phase of ENSO is associated with more rainfall and cooler temperatures. The association between ENSO and the TAST is weak but statistically significant at a two-year lag. In this case, El Niño (drier and warmer) years are associated with a decrease in the export of enslaved Africans. The response of the TAST to El Niño is explained in terms of the societal response to agricultural stresses brought on by less rainfall and warmer temperatures. ENSO-induced changes to the TAST are briefly discussed in light of climate-induced movements of peoples in centuries past, and in the drought-induced movement of peoples in the Middle East today.

The El Niño Southern Oscillation index and wildfire prediction in British Columbia

2014 ◽  
Vol 90 (05) ◽  
pp. 592-598
Author(s):  
Zhen Xu ◽  
G. Cornelis van Kooten
Keyword(s):  
El Niño ◽  
Negative Binomial ◽  
El Nino ◽  
Southern Oscillation ◽  
Positive Influence ◽  
Mean Value ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Area Burned ◽  
Enso Index

This study investigates the potential to predict monthly wildfires and area burned in British Columbia's interior using El Niño Southern Oscillation (ENSO). The zero-inflated negative binomial (ZINB) and the generalized Pareto (GP) distributions are used, respectively, to account for uncertainty in wildfire frequency and area burned. Results indicate that a four-month lag of the ENSO index has a strong positive influence on monthly wildfire occurrence. Upon fitting the GP distribution with a logit model regressed on the ENSO index, we predict the probabilities that monthly area burned exceeds 1700 ha and find that risks of large fires are significantly higher in northwestern BC. However, the ENSO is likely unable to provide consistent predictions of the total area burned in any month. Sensitivity analysis indicates that increases in the mean value of the monthly ENSO index result in a small increase in the predicted number of fires and an increase in the probability of large burns. This study has several implications for decision-making regarding firefighting budget planning and insurance for firefighting expenditures.

ACTUARIAL IMPLICATIONS OF STRUCTURAL CHANGES IN EL NIÑO-SOUTHERN OSCILLATION INDEX DYNAMICS

2014 ◽  
Vol 09 (02) ◽  
pp. 1440007 ◽  
Author(s):  
SHU-LING CHEN ◽  
YU-LIEH HUANG
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
El Niño Southern Oscillation ◽  
Economic Losses ◽  
El Nino Southern Oscillation ◽  
Index Insurance ◽  
Time Invariant ◽  
Over Time ◽  
Enso Index

The influence of climate variability on agricultural production and financial risks faced by an individual or an institution has been the center of the public discussion in the recent years. The changing weather patterns and environmental conditions could cause substantial unpredicted economic losses. Failure to capture such changes would underestimate the insurance contract's expected indemnity and further create a major obstacle for insurance sectors. In this paper, we undertake a case study of El Niño-Southern Oscillation (ENSO) Index insurance for coastal Peru proposed by Skees. We examined the behavior of El Niño index and uncovered the evidence that the conditional volatility of El Niño index has changed over time. A fractionally integrated GARCH (FIGARCH) process that captures long memory behavior for conditional variance and allows the disturbance variance to vary over time is used to design and rate the ENSO Index insurance contract. Our results show that, with the time-invariant AR(2) model serving as a benchmark, the AR(2)-FIGARCH(1, d, 1) model outperforms the AR(2) model in both in-sample fit and out-of-sample forecast for El Niño index. Moreover, the time-invariant model could underestimate the premium rates, exposing the insurer to undesired underwriting risk and ultimately causing the index insurance market to collapse.

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.

The Effect of ENSO on Wheat Futures Based on EMD and GARCH Model

2010 ◽  
Vol 40-41 ◽  
pp. 866-872
Author(s):  
Ying Jun Lou ◽  
Li Na Lu ◽  
Li Jie Zhu
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Negative Relationship ◽  
Practical Significance ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Futures Prices ◽  
The Impact ◽  
Enso Index

At present, most of the studies on the relationship between El Nino Southern Oscillation and agricultural futures focus on perceptual analyses and directly data analysis, and these discussions are usually limited to futures price. This article uses EMD algorithm to decompose Wheat futures prices and denoised ENSO index, and finally gets the negative relationship between El Nino Southern Oscillation and wheat Futures prices. Then, this article conducts the comparative analysis of operation performance based on El Niño Southern Oscillation, finding that this mode of operation can greatly increase yields, which further explains the practical significance of ENSO. In order to explore the impact of El Nino Southern Oscillation on wheat futures yields, use classic GARCH models, transform ENSO index into virtual variables, respectively introduce them into the mean value equation and conditional variance equation. After analysis, the conclusion shows that the impact is mainly on the volatility of return rate, which reminds traders of considering risk management first.

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