scholarly journals Variabilitas Curah Hujan Indonesia dan Hubungannya dengan ENSO/IOD: Estimasi Menggunakan Data JRA-25/JCDAS

Agromet ◽  
2018 ◽  
Vol 28 (1) ◽  
pp. 1
Author(s):  
Rahmat Hidayat ◽  
Kentaro Ando
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Dry Season ◽  
Japan Meteorological Agency ◽  
Climate Data ◽  
Wet Season ◽  
Indonesian Rainfall ◽  
The Impact

Rainfall variability over Indonesia and its relation to El Niño – Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) events were investigated using the Japanese 25-year reanalysis/Japan Meteorological Agency (JMA) Climate Data Assimilation System (JRA-25/ JCDAS). The JRA-25 data consistently depicts seasonal variation of Indonesian rainfall with a wet season that peaks at December-January and a dry season that peaks in July-August when the convection belt moved northward. Composite analysis of rainfall, sea surface temperature and low-level wind anomalies have shown that the impact of ENSO/IOD on rainfall variations in Indonesia is clearly dominant during dry season. Drought conditions typically occur during El Niño years when SST anomalies surrounding Indonesia are cool and walker circulation is weakened, resulting in anomalous surface easterlies across Indonesia. In contrast, in the wet season, the weakening of the relationship between ENSO and Indonesian rainfall is linked to the transition between surface southeasterlies to northwesterlies. At this time persistent surface easterly anomalies across Indonesia superimposed on the climatological mean winds during a warm phase of ENSO event acts to reduce the wind speed resulting reduced the negative DJF rainfall anomalies.

scholarly journals El Niño–Southern Oscillation Impacts on Rice Production in Luzon, the Philippines

2009 ◽  
Vol 48 (8) ◽  
pp. 1718-1724 ◽  
Author(s):  
Martha G. Roberts ◽  
David Dawe ◽  
Walter P. Falcon ◽  
Rosamond L. Naylor
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
The Philippines ◽  
Dry Season ◽  
Rice Production ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Yield Production ◽  
The Impact

Abstract This study uses regression analysis to evaluate the relationships among sea surface temperature anomalies (SSTA) averaged over the Niño-3.4 region (5°N–5°S, 120°–170°W), rainfall, and rice production, area harvested, and yield in Luzon, the large island on which most Philippine rice is grown. Previous research on Philippine rice production and El Niño–Southern Oscillation (ENSO) has found negative associations between El Niño events and rice yields in rainfed systems. This analysis goes further and shows that both irrigated and rainfed ecosystems are impacted. It also compares impacts on area harvested and yield. Variations in average July–September Niño-3.4 SSTAs explain approximately 29% of the interannual variations in the deviations of total January–June (dry season) rice production from a polynomial trend for 1970–2005. In contrast, no impact was found on July–December production in either year t or t + 1. The impact of ENSO on dry-season rice production in Luzon appears to be primarily due to changes in area harvested rather than yield. Production declines for rainfed ecosystems are relatively larger than for irrigated ecosystems: a 1°C increase in average July–September Niño-3.4 SSTA is associated with a 3.7% decrease in irrigated dry-season production but with a 13.7% decline in rainfed dry-season production.

Seasonal–Interannual Variation and Prediction of Wet and Dry Season Rainfall over the Maritime Continent: Roles of ENSO and Monsoon Circulation

2016 ◽  
Vol 29 (10) ◽  
pp. 3675-3695 ◽  
Author(s):  
Tuantuan Zhang ◽  
Song Yang ◽  
Xingwen Jiang ◽  
Ping Zhao
Keyword(s):  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Dry Season ◽  
La Niña ◽  
Monsoon Circulation ◽  
Wet Season ◽  
Maritime Continent ◽  
La Nina

Abstract The authors analyze the seasonal–interannual variations of rainfall over the Maritime Continent (MC) and their relationships with El Niño–Southern Oscillation (ENSO) and large-scale monsoon circulation. They also investigate the predictability of MC rainfall using the hindcast of the U.S. National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). The seasonal evolution of MC rainfall is characterized by a wet season from December to March and a dry season from July to October. The increased (decreased) rainfall in the wet season is related to the peak-decaying phase of La Niña (El Niño), whereas the increased (decreased) rainfall in the dry season is related to the developing phase of La Niña (El Niño), with an apparent spatial incoherency of the SST–rainfall relationship in the wet season. For extremely wet cases of the wet season, local warm SST also contributes to the above-normal rainfall over the MC except for the western area of the MC due to the effect of the strong East Asian winter monsoon. The CFSv2 shows high skill in predicting the main features of MC rainfall variations and their relationships with ENSO and anomalies of the large-scale monsoon circulation, especially for strong ENSO years. It predicts the rainfall and its related circulation patterns skillfully in advance by several months, especially for the dry season. The relatively lower skill of predicting MC rainfall for the wet season is partly due to the low prediction skill of rainfall over Sumatra, Malay, and Borneo (SMB), as well as the unrealistically predicted relationship between SMB rainfall and ENSO.

scholarly journals The impact of El Niño Southern Oscillation on cropping season rainfall variability across Central Brazil

2020 ◽  
Author(s):  
Alexandre Bryan Heinemann ◽  
Julian Ramirez‐Villegas ◽  
Luís Fernando Stone ◽  
Ana Paula Garcia Abreu Silva ◽  
David Henriques da Matta ◽  
...  
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Central Brazil ◽  
Cropping Season ◽  
The Impact

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 The Impact of Obliquity Change on El Niño Southern Oscillation (ENSO) and La Niña Climate Episodes

2022 ◽  
Author(s):  
Paul C. Rivera
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
Global Climate Model ◽  
La Niña ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
La Nina ◽  
The Impact

An alternative physical mechanism is proposed to describe the occurrence of the episodic El Nino Southern Oscillation (ENSO) and La Nina climatic phenomena. This is based on the earthquake-perturbed obliquity change (EPOCH) model previously discovered as a major cause of the global climate change problem. Massive quakes impart a very strong oceanic force that can move the moon which in turn pulls the earth’s axis and change the planetary obliquity. Analysis of the annual geomagnetic north-pole shift and global seismic data revealed this previously undiscovered force. Using a higher obliquity in the global climate model EdGCM and constant greenhouse gas forcing showed that the seismic-induced polar motion and associated enhanced obliquity could be the major mechanism governing the mysterious climate anomalies attributed to El Nino and La Nina cycles.

scholarly journals EL NINO, LA NINA, DAN PENAWARAN PANGAN DI JAWA, INDONESIA

2011 ◽  
Vol 12 (2) ◽  
pp. 257
Author(s):  
Arini Wahyu Utami ◽  
Jamhari Jamhari ◽  
Suhatmini Hardyastuti
Keyword(s):  
El Niño ◽  
Time Series Data ◽  
El Nino ◽  
Southern Oscillation ◽  
Regression Function ◽  
La Niña ◽  
Series Data ◽  
Cross Sectional ◽  
La Nina ◽  
The Impact

Paddy and maize are two important food crops in Indonesia and mainly produced in Java Island. This research aimed to know the impact of El Nino and La Nina on paddy and maize farmer’s supply in Java. Cross sectional data from four provinces in Java was combined with time series data during 1987-2006. Paddy supply was estimated using log model, while maize supply used autoregressive model; each was estimated using two types of regression function. First, it included dummy variable of El Nino and La Nina to know their influence into paddy and maize supply. Second, Southern Oscillation Index was used to analyze the supply changing when El Nino or La Nina occur. The result showed that El Nino and La Nina did not influence paddy supply, while La Nina influenced maize supply in Java. Maize supply increased when La Nina occurred.

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