The Effect of the El Nino Southern Oscillation on U.S. Corn Production and Downside Risk

El Nino Southern Oscillation (ENSO) teleconnections imply anomalous weather conditions around the globe, causing yield shortages, price changes, and even civil unrests. Extreme ENSO events may cause catastrophic damages to crop yields, thus amplifying downside risk for producers. This study presents a framework for quantifying the effects of climate on crop yield distributions. An empirical application provides estimates of the effect that ENSO events have on the means of U.S. county-level corn yield distributions, as well as the probabilities of catastrophic crop loss. Our findings demonstrate that ENSO events strongly influence these probabilities systematically over large production regions, which has important implications for research and policy analysis in the production, risk management, climate change, and civil unrest literatures.Climate, El Nino Southern Oscillation, Maximum Entropy, Risk Management, Yield Distribution, Crop Production/Industries, Environmental Economics and Policy, Production Economics,

The ENSO Impact on Predicting World Cocoa Prices

Cocoa beans are produced in equatorial and sub-equatorial regions of West Africa, Southeast Asia and South America. These are also the regions most affected by El Nino Southern Oscillation (ENSO) -- a climatic anomaly affecting temperature and precipitation in many parts of the world. Thus, ENSO, has a potential of affecting cocoa production and, subsequently, prices on the world market. This study investigates the benefits of using a measure of ENSO variable in world cocoa price forecasting through the application of a smooth transition autoregression (STAR) modeling framework to monthly data to examine potentially nonlinear dynamics of ENSO and cocoa prices. The results indicate that the nonlinear models appear to outperform linear models in terms of out-of-sample forecasting accuracy. Furthermore, the results of this study indicate evidence of Granger causality between ENSO and cocoa prices.Cocoa Prices, El Nino Southern Oscillation, Out-of-Sample Forecasting, Smooth Transition Autoregression, Demand and Price Analysis, Environmental Economics and Policy, Research Methods/ Statistical Methods, C32, Q11, Q54,

Analisa Fenomena ENSO di Perairan Indonesia Menggunakan Data Altimetri Topex/Poseidon dan Jason Series Tahun 1993-2018

ENSO (El Nino Southern Oscillation) adalah fenomena yang terjadi akibat adanya penyimpangan kondisi interaksi antara lautan dan atmosfer di sepanjang Samudera Pasifik sekitar ekuator dari keadaan normalnya. Salah satu wilayah yang terkena dampak dari fenomena El Nino Southern Oscillation adalah perairan Indonesia. Hal yang terpengaruh karena adanya fenomena El Nino Southern Oscillation selain cuaca adalah sea level. Untuk mengetahui wilayah perairan Indonesia mana saja yang terpengaruh fenomena tersebut maka dilakukan perhitungan korelasi antara nilai Sea Level Anomaly dari data satelit altimetri dengan indeks El Nino Southern Oscillation yaitu Multvariate ENSO Index, Southern Oscillation Index, Oscillation Nino Index. Nilai korelasi mean sea level anomaly dengan indeks Multvariate ENSO Index adalah -0,799. Pada korelasi mean sea level anomaly dengan indeks Oscillation Nino Index adalah -0,858. Sedangkan korelasi mean sea level anomaly dengan indeks Southern Oscillation Index adalah 0,698. Hal tersebut menunjukkan bahwa hubungan fenomena ENSO dengan sea level anomaly memiliki korelasi kuat. Hasil dari korelasi sea level anomaly dengan indeks El Nino Southern Oscillation secara spasial memiliki korelasi terkecil pada 90 BT, 17 LS sedangkan daerah yang memiliki korelasi terbesar terdapat pada 129 BT, 1 LU. Wilayah korelasi sea level anomaly dengan indeks ENSO yang memiliki hubungan kuat atau perubahan sea level anomaly yang terjadi ketika fenomena El Nino Southern Oscillation paling besar pada Laut Halmahera, perairan di Utara Papua, Laut Maluku, Laut Sulawesi dan periaran sekitar Nusa Tenggara Timur. Wilayah yang korelasi sea level anomaly dengan indeks ENSO rendah terdapat di sekitar perairan Sumatra, Laut Natuna, perairan Jawa Barat. Sedangkan perairan Jawa Timur, perairan Bali dan Nusa Tenggara Barat (Laut Flores) memiliki nilai korelasi sedang. ====================ENSO (El Nino Southern Oscillation) is a phenomenon that occurs due to the deviation of the condition of the interaction between oceans and the atmosphere along the Pacific Ocean around the equator from normal state. One of the areas affected by the impact of the El Nino Southern Oscillation phenomenon is the Indonesia sea. El Nino Southern Oscillation phenomenon was affected weather and other affected was to the sea level. To find out the territorial Indonesia waters which affected with ENSO then performed the calculation of correlation between the value of Sea Level Anomaly from satellite altimetri data with the index El Nino Southern Oscillation (Multvariate ENSO Index, Southern Oscillation Index, Nino Oscillation Index). The value of the correlation mean sea level anomaly with ENSO Index Multvariate index is -0.799, in correlation mean sea level anomaly with the Oscillation Nino Index is -0.858. While correlation mean sea level anomaly with the Southern Oscillation Index is 0.698. It shows that the relationship sea level anomaly with the ENSO phenomenon have a strong correlation. The result correlation of sea level anomaly with El Nino Southern Oscillation indices has the smallest value at 90 E, 17 S whereas has the greatest correlation found in 129 E, 1 N. The region of sea level anomaly correlation with ENSO indices that have strong relationships or most changes in sea level anomaly of the Halmahera sea, sea north of Papua, Maluku sea, Sulawesi sea and sea around East Nusa Tenggara. The area that the correlation of sea level anomaly with ENSO index is low is around the island of Sumatra, Natuna sea, and sea around West Java. While sea around East Java, sea around of Bali and West Nusa Tenggara (Flores sea) has the moderate value of the correlation

Sloshing Model for ENSO

The El Nino southern oscillation (ENSO) behavior can be effectively modeled as a response to a 2nd-order Mathieu/Hill differential equation with periodic coefficients describing sloshing of a volume of water. The forcing of the equation derives from QBO, angular momentum changes synchronized with the Chandler wobble, and solar insolation variations. One regime change was identified in 1980. (See floating note)Comment: 4 pages, 5 figure

The El Nino southern oscillation climate system

Includes bibliographical references.The El Nino Southern Oscillation climate system, ENSO, is the largest coherent climate system on Earth. The variability of ENSO effects climate and environmental conditions across the globe, impacting the daily lives of hundreds of millions of people. There has been intensive study on the behavior of this system. While the mechanisms that control ENSO are now largely understood, the variability of these mechanisms is unknown. It is also unknown how ENSO will respond to global warming. Currently there is a void of data on the history of ENSO over the past several thousand years. A comprehensive record of ENSO will provide a deeper understanding of the system and allow scientists to predict how ENSO may change as a result of global warming. My aim is to help fill the gap in history by working with two NIU senior faculty advisors on an integrated project involving archeology and paleoclimate science. I will be developing records of ENSO variability from 2,500 to 3,500 years before present using material from archeological sites on coastal Peru and geochemical analytical methods to reconstruct one of the key elements of ENSO, sea surface temperatures in the eastern equatorial Pacific. This work will benefit climate change research and help develop a body of data suitable for testing theories on ENSO response to global climate change.B.S. (Bachelor of Science

Tropical Atmospheric Circulations: Dynamic Stability and Transitions

In this article, we present a mathematical theory of the Walker circulation of the large-scale atmosphere over the tropics. This study leads to a new metastable state oscillation theory for the El Nino Southern Oscillation (ENSO), a typical inter-annual climate low frequency oscillation. The mathematical analysis is based on 1) the dynamic transition theory, 2) the geometric theory of incompressible flows, and 3) the scaling law for proper effect of the turbulent friction terms, developed recently by the authors

ENSO dynamics: low-dimensional-chaotic or stochastic?

We apply a test for low-dimensional, deterministic dynamics to the Nino 3 time series for the El Nino Southern Oscillation (ENSO). The test is negative, indicating that the dynamics is high-dimensional/stochastic. However, application of stochastic forcing to a time-delay equation for equatorial-wave dynamics can reproduce this stochastic dynamics and other important aspects of ENSO. Without such stochastic forcing this model yields low-dimensional, deterministic dynamics, hence these results emphasize the importance of the stochastic nature of the atmosphere-ocean interaction in low-dimensional models of ENSO

A teleconnection between the Southern Hemisphere mid-latitude and equatorial ocean (Abstract)

The sub-surface ocean is a pathway for climate anomalies which propagate away from high and mid-latitude water mass formation region and into the Equatorial ocean. Thus there is the potential that the existence of this sub-surface ocean pathway may lead to decadal variability of Equatorial sea surface temperature. This in turn leads to some influence upon the El Nino Southern Oscillation. In my talk, I will present some results from recent ocean modelling studies that investigate mid-latitude water mass formation processes and their passage throughout the interior of the upper ocean

Application of Differential Transform Method for El Nino Southern Oscillation (ENSO) Model with compared Adomian Decomposition and Variational Iteration Methods

We consider two nonlinear El Nino Southern Oscillation (ENSO) model to obtain approximate solutions with differential transform method for the first time. Efficiency, accuracy and error rates of solutions are compared with analytic solution, variational iteration and adomian decomposition solutions on the given tables and figures.Comment: 12 pages, 10 figure