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Journal articles on the topic 'El Nino and Southern Oscillation'

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Published: 6 September 2023

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1

Nicholls, Neville. "El Nino—Southern Oscillation Impact Prediction." Bulletin of the American Meteorological Society 69, no. 2 (February 1988): 173–76. http://dx.doi.org/10.1175/1520-0477(1988)069<0173:enoip>2.0.co;2.

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2

Muhammad, Fadhlil Rizki, Yudha Kristanto, and Imam Wahyu Amanullah. "Karakteristik Madden-Julian Oscillation (MJO) Ketika El-Nino Southern Oscillation (ENSO)." Wahana Fisika 2, no. 2 (December 28, 2017): 76. http://dx.doi.org/10.17509/wafi.v2i2.9376.

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Perkembangan peristiwa El-Nino Southern Oscillation (ENSO) menunjukkan peran penting bagi Madden-Julian Oscillation (MJO). Variasi angin permukaan (UWND) dan konveksi (OLR) intramusiman yang merupakan komponen dari variabilitas MJO sangat berinteraksi dengan komponen ENSO dalam skala waktu dan ruang. Penelitian ini menggunakan Diagram Hovmueller untuk melihat perambatan konveksi, analisis spektral untuk melihat frekuensi MJO, analisis spektral bilangan gelombang-frekuensi untuk melihat perambatan dan bilangan gelombang zonal, serta analisis spektral silang untuk melihat koherensi serta fase dari konveksi dan angin zonal dengan band-pass filter 20-100 hari. Secara keseluruhan, hasil analisis spektral menunjukkan MJO memiliki frekuensi 30-60 harian. Hasil analisis diagram Hovmueller ketika peristiwa El-Nino lemah (tahun 2004-2005) menjelaskan bahwa ada perambatan konveksi ke timur tetapi hanya terjadi pada awal tahun sangat cepat atau tidak beraturan dan kemudian hilang. Konveksi menunjukkan bilangan gelombang zonal 1 ketika bulan Mei-Okt dan bilangan zonal 1-4 ketika bulan Nov-Apr. Spektrum silang menunjukkan angin zonal mendahului konveksi 1/8 putaran yang berarti ada hubungan fisis antara UWND dan OLR dengan koherensi 0.65 di bilangan zonal 1-2. Ketika peristiwa El-Nino sangat kuat (tahun 1997-1998), diagram Hovmueller menunjukkan tidak adanya perambatan konveksi dari Samudera Hindia ke Pasifik bagian barat. Anomali dan perambatan konveksi sangat kuat pada awal tahun 1997 ketika fase normal dan melemah pada bulan Juli hingga hilang sama sekali seiring meningkatnya El-Nino. konveksi menunjukkan bulan Nov-Apr memiliki nilai spektral yang lebih kuat daripada bulan Mei-Okt. Koherensi menjukkan nilai yang tinggi pada bilangan zonal 1-2 dengan range 0.35-0.65, begitupula angin zonal juga mendahului konveksi sebesar 1/8 putaran. Perubahan signifikan pada MJO terlihat pada perambatan konveksi yang menghilang ketika semakin kuatnya El-Nino. melemahnya MJO, dan frekuensi dari MJO yang menjadi lebih tinggi. Kata Kunci : band-pass filter; Diagram Hovmueller; konveksi; spektrum silang; angin zonal The development of ENSO (El-Nino Southern Oscillation) events hows an important role for MJO (Madden Julian Oscillation). Variation of intraseasonal zonal wind and convection (OLR) are important components of MJO variability which interact with ENSO components in space-time scale. Before processing, data are filtered with Lanczos bandpass filter 20-100 days. This research using Hovmueller diagram to see the propagation of convection and zonal wind, spectral analysis to see MJO frequency, wavenumber-frequency spectra to see propagation of MJO and its zonal wavenumber, and cross-spectrum analysis to see coherence and phase lag between convection and zonal wind. Spectral analysis have shown that MJO have frequency of 30-60 days. During weak El-Nino event (1991-1992), Hovmueller diagram have discovered that there is eastward propagation of convection in the early years but occurs very quickly or irregularly and than dissipated. Convection have zonal wavenumber of 1 when May-Oct and zonal wavenumber of 1-4 when Nov-Apr. Cross-spectrum shows that zonal wind leads convection by 1/8 cycle with coherence 0.65 in zonal wavenumber 1-2. Hovmueller diagram have shown that there are no eastward propagation from Indian Ocean to Western Pacific during strong El-Nino event (1997-1998). Convection and propagation were very strong in early 1997 then weakened in July to disappear altogether as El-Nino strenghtened. Wavenumber-frequency spectra have shown that Nov-Apr convection has weaker value than May-Oct convection. Cross-spectrum shows large coherence in zonal wavenumber 1-2 with range of 0.35-0.65 and zonal wind leads convection by 1/8 cycle. Significant changes in MJO are seen in the disappearance of propagation of convection, weakening of MJO, and higher observed frecuency of MJO as El-Nino activity strengthened. Keywords : band-pass filter; Hovmueller diagram; convection; cross-spectrum; zonal wind

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3

Pascual, M. "Cholera Dynamics and El Nino-Southern Oscillation." Science 289, no. 5485 (September 8, 2000): 1766–69. http://dx.doi.org/10.1126/science.289.5485.1766.

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4

Yasunari, Tetsuzo. "Global Structure of the El Nino/Southern Oscillation." Journal of the Meteorological Society of Japan. Ser. II 65, no. 1 (1987): 67–80. http://dx.doi.org/10.2151/jmsj1965.65.1_67.

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5

Yasunari, Tetsuzo. "Global Structure of the El Nino/Southern Oscillation." Journal of the Meteorological Society of Japan. Ser. II 65, no. 1 (1987): 81–102. http://dx.doi.org/10.2151/jmsj1965.65.1_81.

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6

Muza, Olivia. "El Nino-Southern Oscillation Influences on Food Security." Journal of Sustainable Development 10, no. 5 (September 29, 2017): 268. http://dx.doi.org/10.5539/jsd.v10n5p268.

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El-Nino Southern Oscillation (ENSO) is the most recurrent change in climate impacting agriculture productivity and food security. This study investigates ENSO impacts on four cereal crops (maize, millet, sorghum and wheat) using crop production and climate datasets spanning the years 1960-2015. The results of this study reveal that during El Nino (La Nina) maize, sorghum and wheat production decreases (increases) while that of millet increases (decreases). Even though, the correlation is statistically significant for maize only, the outcome is a call to review the macro-food policy taking into account ENSO-related phase effects to redress food insecurity. The study recommends incentives for agricultural productivity including irrigation intensification and small grain value chain development, trade and food security arrangements, income generation opportunities and strategic partnerships for improved food and nutrition security.

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7

Latif, M., and N. S. Keenlyside. "El Nino/Southern Oscillation response to global warming." Proceedings of the National Academy of Sciences 106, no. 49 (December 5, 2008): 20578–83. http://dx.doi.org/10.1073/pnas.0710860105.

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8

Ahn, J. H., and H. S. Kim. "Nonlinear Modeling of El Nino/Southern Oscillation Index." Journal of Hydrologic Engineering 10, no. 1 (January 2005): 8–15. http://dx.doi.org/10.1061/(asce)1084-0699(2005)10:1(8).

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9

Lou, Ying Jun, Li Na Lu, and Li Jie Zhu. "The Effect of ENSO on Wheat Futures Based on EMD and GARCH Model." Applied Mechanics and Materials 40-41 (November 2010): 866–72. http://dx.doi.org/10.4028/www.scientific.net/amm.40-41.866.

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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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10

Aprilia, Bunga, Marzuki Marzuki, and Imam Taufiq. "Prediksi El Nino Southern Oscillation (ENSO) Menggunakan Jaringan Saraf Tiruan (JST)-Backpropagation." Jurnal Fisika Unand 9, no. 4 (January 25, 2021): 421–27. http://dx.doi.org/10.25077/jfu.9.4.421-427.2020.

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Penelitian ini bertujuan untuk memprediksi nilai indeks ENSO yaitu Sea Surface Temperature (Nino 1.2, Nino 3, Nino 3.4 dan Nino 4), Southern Oscillation Index (SOI) dan Multivariate ENSO Index versi 2 (MEI.v2) yang diambil dari tahun 1979-2018. Prediksi dilakukan dengan menggunakan metode JST-backpropagation dengan memvariasikan learning rate dan momentum. Semua indeks menghasilkan nilai akurasi prediksi ENSO yang tinggi, namun indeks Nino 4 merupakan indeks yang memiliki akurasi tertinggi karena nilai Mean Square Error (MSE) pelatihan dan pengujiannya yang relatif lebih kecil dibandingkan dengan indeks lainnya. Indeks Nino 4 memiliki MSE pelatihan 0,0072739 yang berhenti pada epoch ke-69 dan MSE pengujian 0,0085917 dengan akurasi prediksi 99,9989%. Hasil ini diperoleh dari arsitektur JST-backpropagation 12-10-1 dengan nilai learning rate 0,10 dan momentum 0,40. Prediksi ENSO berdasarkan indeks Nino 4 untuk tahun 2021 menunjukkan keadaan iklim dunia dalam kondisi normal. This study aims to predict ENSO index using Sea Surface Temperature (Nino 1.2, Nino 3, Nino 3.4 and Nino 4 indexes), Southern Oscillation Index (SOI), and Multivariate ENSO Index version 2 (MEI.v2) during 1979 - 2018. The prediction was carried out using the ANN-backpropagation method by varying the learning rate and momentum. All indices produce high ENSO prediction accuracy values, but the Nino 4 index is the best one because the Mean Square Error (MSE) for training and testing steps are relatively smaller than other indexes. The Nino 4 index has a training MSE of 0.0072739 which stops at the 69th epoch and a testing MSE of 0.0085917 with a predictive accuracy of 99.9989%. These results were obtained from the back-propagation architecture ANN 12-10-1 with a learning rate of 0.10 and a momentum of 0.40. The prediction of ENSO in 2021 based on the Nino 4 index shows that the world climate condition is under normal conditions.

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11

AHMED, A. S. M. SABBIR, A. A. MUNIM, Q. N. BEGUM, and A. M. Choudhury. "EI-Nino southern oscillation and rainfall varIation over Bangladesh." MAUSAM 47, no. 2 (December 15, 2021): 157–62. http://dx.doi.org/10.54302/mausam.v47i2.3713.

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In the present study, an attempt has been made to examine the variations of rainfall over Bangladesh and to find possible correlation with EI-Nino/Southern Oscillation (ENSO). Four stations have been chosen from four different climatic regions of Bangladesh for this purpose, namely Jessore, Dhaka. Barisal and Srimangal. The regions have been classified according to annual rainfall amounts. The rainfall data for forty three years, (1950-1992) have been analysed. The yearly mean rainfall shows a distinct negative decreasing tendency with the occurrence of ENSO.The seasonal rainfall analysis shows a somewhat better correlation.

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12

CANE, M. A., and S. E. ZEBIAK. "A Theory for El Nino and the Southern Oscillation." Science 228, no. 4703 (May 31, 1985): 1085–87. http://dx.doi.org/10.1126/science.228.4703.1085.

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13

Pasha, Wanda Avia, Amron Amron, and Widodo Setiyo Pranowo. "Pengaruh Enso (El Nino Southern Oscillation) Terhadap Suhu Dan Salinitas di Perairan Utara Aceh." Jurnal Hidropilar 8, no. 2 (December 9, 2022): 61–72. http://dx.doi.org/10.37875/hidropilar.v8i2.247.

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Suhu dan salinitas merupakan faktor oseanografi yang berperan dalam proses fisika maupun biologi diperairan. Massa air dapat diketahui dengan menganalisis distribusi suhu dan salinitas. Variabilitas iklim di Indonesia salah satunya di pengaruhi oleh ENSO. Tujuan dari penelitian ini untuk mengetahui kondisi umum perairan utara Aceh, mengetahui variabilitas suhu dan salinitas saat fenomena ENSO terjadi dan korelasi antara suhu dan salinitas terhadap SOI. Data yang digunakan adalah suhu dan salinitas pada tahun 2011, 2012 dan 2015 dari website HYCOM. Metode yang digunakan adalah asimilasi hasil model dengan menggunakan software Ocean Data View 4 untuk variabilitas spasial dan Microsoft Excel untuk variabilitas temporal. Hasil penelitian menunjukkan bahwa kondisi umum di perairan utara Aceh saat fenomena ENSO tidak mengalami perubahan suhu dan salinitas yang signifikan. Variabilitas suhu laut pada kondisi La Nina lebih tinggi daripada kondisi El Nino sedangkan variabilitas salinitas yang terjadi pada kondisi El Nino lebih tinggi daripada La Nina. Hasil korelasi menunjukkan saat kondisi La Nina terhadap SOI tidak mempengaruhi variabilitas suhu, namun saat kondisi El Nino SOI dapat mempengaruhi suhu dengan tingkat hubungan kuat dan saat La Nina cenderung lemah. Saat kondisi La Nina dan El Nino terhadap SOI tidak mempengaruhi variabilitas salinitas.

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14

Utami, Arini Wahyu, Jamhari Jamhari, and Suhatmini Hardyastuti. "EL NINO, LA NINA, DAN PENAWARAN PANGAN DI JAWA, INDONESIA." Jurnal Ekonomi Pembangunan: Kajian Masalah Ekonomi dan Pembangunan 12, no. 2 (December 1, 2011): 257. http://dx.doi.org/10.23917/jep.v12i2.197.

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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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15

Chung, Christine T. Y., and Scott B. Power. "The non-linear impact of El Nino, La Nina and the Southern Oscillation on seasonal and regional Australian precipitation." Journal of Southern Hemisphere Earth Systems Science 67, no. 1 (2017): 25. http://dx.doi.org/10.1071/es17004.

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The relationship between El Niño-Southern Oscillation (ENSO) indices and precipitation (P) in some parts of Australia has previously been shown to be non-linear on annual and seasonal time scales. Here we examine the relationship between P and the Southern Oscillation Index (SOI) at all Australian locations and in all seasons. We show that in many Australian regions, there is more-than-expected P during strong La Niña years (SOI>13), but less-than-expected drying during strong El Niño years (SOI

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16

Voskresenskaya, E. N., and V. N. Maslova. "Winter-spring cyclonic variability in the Mediterranean-Black Sea region associated with global processes in the ocean-atmosphere system." Advances in Science and Research 6, no. 1 (August 30, 2011): 237–43. http://dx.doi.org/10.5194/asr-6-237-2011.

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Abstract. Using global NCEP/NCAR reanalysis data set on 1000 hPa geopotential height (1948–2006), cyclones in the Mediterranean and Black Sea regions were detected and their main characteristics (frequency, depth, integrated area) were calculated. Analysis of their interannual-multidecadal variability in January-March associated with global processes in the ocean-atmosphere system was done. It was shown that North Atlantic Oscillation (NAO) manifests in the Black Sea region mainly in the variability of frequency of cyclones while in the Mediterranean – in the interannual anomalies of cyclones' depth and area. Joint NAO and El Nino – Southern Oscillation (ENSO) influence is responsible for about 20–45% of cyclones' frequency variance in the Black Sea region, and in the Mediterranean region for up to 10–25 and 20–30% of the depth and area variance, accordingly. As a result of using a new approach to study ENSO manifestations based on El Nino classification, correlation coefficients between characteristics of cyclones and Southern Oscillation index (SOI) increase at least twice. The influence of the Pacific Decadal and Atlantic Multidecadal Oscillations on variability of cyclonic activity in the Mediterranean-Black Sea region manifests in considerable differences of cyclones' characteristics and their typical location.

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17

Koem, S., R. J. Lahay, and S. K. Nasib. "The sensitivity of meteorological drought index towards El Nino-Southern Oscillation." IOP Conference Series: Earth and Environmental Science 1089, no. 1 (November 1, 2022): 012005. http://dx.doi.org/10.1088/1755-1315/1089/1/012005.

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Abstract El Nino-Southern Oscillation (ENSO) contributes to the regional climates, such as precipitation and droughts. The objectives of the present work were to: (1) identify the severity index; (2) analyze the correlation of SPI and RDI, and; (3) identify the response of SPI and RDI towards ENSO. SPI and RDI were calculated for time scales (3, 6, and 12 months), and these represented the seasonal and annual drought. The identification of the responses of the drought severity index, based on ENSO, consisted of several thresholds, namely weak, moderate, and strong. The correlational value and RMSE only represented the performance of SPI and RDI on different time scales. The drought severity index would decline along with an increase in the time scales. The strong El Nino phase could be significant to the seasonal and annual drought. In other words, ENSO was impactful on the precipitation and dynamics of drought. Drought periods were due to the moderate and strong El Nino phase, while the weak phase led to a normal condition. For this reason, ENSO could be functioned as an indicator to predict drought.

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18

Yananto, Ardila, and Rini Mariana Sibarani. "ANALISIS KEJADIAN EL NINO DAN PENGARUHNYA TERHADAP INTENSITAS CURAH HUJAN DI WILAYAH JABODETABEK (Studi Kasus : Periode Puncak Musim Hujan Tahun 2015/2016)." Jurnal Sains & Teknologi Modifikasi Cuaca 17, no. 2 (December 27, 2016): 65. http://dx.doi.org/10.29122/jstmc.v17i2.541.

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IntisariBeberapa lembaga riset dunia dan badan-badan meteorologi beberapa negara di dunia menyatakan adanya kejadian El Nino Tahun 2015 terus berlanjut hingga tahun 2016. Adanya kejadian El Nino tersebut secara umum akan mempengarui intensitas curah hujan di sebagian besar wilayah Indonesia termasuk wilayah Jabodetabek. Analisis kejadian El Nino Tahun 2015/2016 dilakukan dengan menganalisis nilai NINO 3.4 SST Index, Southern Oscillation Index (SOI), Indian Ocean Dipole (IOD), pola sebaran suhu permukaan laut (Sea Surface Temperature) dan juga gradient wind di Samudra Pasifik Tropis. Sedangkan Analisis Curah Hujan dilakukan dengan menggunakan data TRMM (Tropical Rainfall Measuring Mission). Dari penelitian ini dapat diketahui bahwa berdasarkan parameter NINO 3.4 SST Index dan Southern Oscillation Index (SOI) pada pertengahan Tahun 2015 hingga awal Tahun 2016 telah terjadi fenomana El Nino pada level kuat, adanya peningkatan suhu permukaan laut di sebagian besar wilayah Indonesia sejak Bulan November 2015 yang diikuti dengan penurunan indeks Dipole Mode hingga menjadi bernilai negatif (-) sejak awal Tahun 2016 serta dengan adanya peralihan Angin Muson Timur ke Angin Muson Barat di wilayah Indonesia telah menyebabkan peningkatan curah hujan yang cukup signifikan dalam batas normal di wilayah Jabodetabek pada puncak musim hujan Tahun 2015/2016 (November 2015 - Februari 2016) walaupun pada Bulan November 2015 hingga Februari 2016 tersebut masih berada pada level El Nino kuat. AbstractVarious research institutions in the world that work in the field of Meteorology and Climatology predicted an El Nino events in 2015 continued into 2016. The El Nino events phenomenon in general will affect to intensity of the rainfall in most parts of Indonesia, including the Greater Jakarta area. El Nino events phenomenon Analysis by Nino 3.4 SST index, Southern Oscillation Index (SOI), Indian Ocean Dipole (IOD), Sea Surface Temperature (SST) and gradient wind in the Tropical Pacific Ocean. While rainfall intensity analysis using TRMM (Tropical Rainfall Measuring Mission) data. From this research it is known that based on the parameters NINO 3.4 SST index and the Southern Oscillation Index (SOI), it is known that there was a strong El Nino event occurred in mid-2015 to early 2016, the increase of sea surface temperature in most parts of Indonesia since November 2015 followed by declines Dipole Mode Index to be negative (-) since the beginning 2016 as well as the shift East monsoon to West monsoon in Indonesia has led to significant rainfall increased within normal limits in the Greater Jakarta area at the peak period of the rainy season 2015/2016 (November 2015 - February 2016) although in November 2015 until February 2016 El Nino event is still at the strong level.

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19

Ford, H. L., A. C. Ravelo, and P. J. Polissar. "Reduced El Nino-Southern Oscillation during the Last Glacial Maximum." Science 347, no. 6219 (January 15, 2015): 255–58. http://dx.doi.org/10.1126/science.1258437.

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20

Hsieh, WW, and BV Hamon. "The El Nino-Southern Oscillation in south-eastern Australian waters." Marine and Freshwater Research 42, no. 3 (1991): 263. http://dx.doi.org/10.1071/mf9910263.

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Using four decades of hydrographic data collected off the coast near Sydney, New South Wales, and sea-level data at Sydney, we studied the interannual variability in south-eastern Australian shelf waters. The first two empirical orthogonal function (EOF) modes of the band-pass-filtered 50-m-depth hydrographic data (temperature, T; salinity, S; nitrate, N; inorganic phosphate, P; and oxygen, O) and the sea level (SL) and adjusted sea level (ASL) data accounted respectively for 51 and 27% of the total variance. Both modes were significantly correlated with the Southern Oscillation Index (SOI). The first mode, with T, S, O and ASL varying in opposition to N and P, represented the internal or baroclinic response, associated with vertical displacements of the isopycnals. The second mode, with large in-phase fluctuations in SL and ASL but small changes in the hydrographic variables, represented mainly the external or barotropic response during the El Niiio-Southern Oscillation (ENSO). Three-year composites centred around seven ENSO warm episodes revealed that T, S, O and ASL were generally low and N, P, SL and SO1 were high in the year before each ENSO warm episode, but the former group rose while the latter group dropped in the year of the warm episode. The changes in the hydrographic variables at 50 m depth were consistent with relatively shallow isopycnals in the year before the ENSO warm episode, followed by a deepening of the isopycnals during the warm episode. Estimates of this downward displacement of isopycnals, as determined from T, N, P and O, were in the range 7-10 m. The geostrophic wind arising from the pressure fluctuations during ENSO is proposed as a probable cause for the vertical displacement of the isopycnals. In the year before the warm episode, the low air pressure over Australia would produce a clockwise geostrophic wind around south-eastern Australia, generating offshore Ekman transport and coastal upwelling. During the warm episode, air pressure over Australia rises, the geostrophic wind reverses, and downward movement of the isopycnals would occur off south-eastern Australia.

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21

Fu, Congbin, Dongfeng Dong, Slutz Ralph, and Fletcher Joseph. "El Nino/Southern oscillation signals in the global tropical ocean." Advances in Atmospheric Sciences 5, no. 1 (February 1988): 35–45. http://dx.doi.org/10.1007/bf02657344.

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22

Chao, B. F. "Length-of-Day Variations Caused by El Nino-Southern Oscillation and Quasi-Biennial Oscillation." Science 243, no. 4893 (February 17, 1989): 923–25. http://dx.doi.org/10.1126/science.243.4893.923.

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23

Tongkukut, Seni Herlina J. "El-NINO DAN PENGARUHNYA TERHADAP CURAH HUJAN DI MANADO SULAWESI UTARA." JURNAL ILMIAH SAINS 11, no. 1 (April 1, 2011): 102. http://dx.doi.org/10.35799/jis.11.1.2011.51.

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Telah dilakukan analisis El-Nino dan pengaruhnya terhadap curah hujan di Manado Sulut dengan menggunakan data curah hujan bulanan dan Southern Oscillation Index SOI selama thn 1999-2009. Data curah hujan diperoleh dari BMKG Kayuwatu Manado Sulut dan data SOI diunduh dari website Biro Meteorologi Australia BoM. Analisis dilakukan dengan analisis regresi linear sederhana. Diperoleh hasil bahwa curah hujan kota Manado secara umum dari thn 1999-2008 dipengaruhi oleh SOI namun pada thn 2009 ketika terjadi El-nino, curah hujan bulanan Manado tidak dipengaruhi oleh efek El-nino. Hal ini karena pada saat yang sama suhu muka laut perairan Indonesia juga menghangat. EL-NINO AND ITS EFFECT ON RAINFALL IN MANADONORTH SULAWESIABSTRACTAnalysis of El-Nino and its effect on rainfall in Manado, North Sulawesi, using monthly rainfall data and the Southern Oscillation Index SOI during the years 1999-2009 has been carried out. Rainfall data obtained from BMKG Kayuwatu Manado and SOI data downloaded from the website of Australian Bureau of Meteorology (BoM). The analysis was performed with simple linear regression analysis. The results obtained indicate that rainfall in Manado , in general, was influenced by SOI from the years 1999-2008, but when there is an El-Nino in 2009, monthly rainfall in Manado is not affected by the El-Nino effect. This is due to, at the same time, sea surface temperature in Indonesian territory are also warm.

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24

Mahmud, Mastura, and Nur Hidayah Ahmad. "Peristiwa El Nino, keragaman hujan dan potensi Southern Oscillation Index untuk peramalan kualiti udara di Malaysia." Malaysian Journal of Society and Space 14, no. 2 (May 29, 2018): 13–25. http://dx.doi.org/10.17576/geo-2018-1402-02.

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25

Hashidu, U. S., and S. I. Badaru. "Relationship between El-Niño southern oscillation and rainfall in Sudano-Sahelian Region of Northern Nigeria." JOURNAL OF AGRICULTURAL ECONOMICS, ENVIRONMENT AND SOCIAL SCIENCES 7, no. 2 (November 28, 2021): 211–16. http://dx.doi.org/10.56160/jaeess202172019.

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El Nino Southern-Oscillation (ENSO) refers to the cycle of coherent and sometimes very strong variations in the sea surface temperature (SST), convective rainfall, surface pressure and atmospheric circulation across the equatorial Pacific Ocean. The research investigated the relationship between ENSO and rainfall across the Sudano-Sahelian region of northern Nigeria. Rainfall data for seven (7) locations were sourced from the Nigerian Meteorological Agency (NIMET) covering the period from 1950 to 2019 and El-Nino Southern Oscillation (ENSO) data which comprised of Southern Oscillation Index (SOI) covering the same period. The Southern Oscillation Index (SOI) data was obtained from National Oceanographic Atmospheric Administration (NOAA) Climate Prediction Centre. A bivariate correlation analysis between rainfall and SOI were computed for all the seven locations to determine the relationship between ENSO and Sudano-Sahelian rainfall. The result shows a significant relationship for Potiskum, Maiduguri and Katsina with correlation coefficient (r) values of 0.25, 0.26 and 0.27 respectively while Kano Gusau Nguru and Sokoto show no significant relationship. It is therefore concluded that there is no strong relationship between rainfall and ENSO in Sudano-Sahelian part of northern Nigeria. It is recommended that further research could be carried out to investigate the influence of ENSO on other climate parameters such as temperature, humidity and evapotranspiration in the study area.

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Rejeki, Hasti Amrih, B. Betsi, and Yogi Muhammad Andariwan. "VARIATIONS OF INDONESIAN TRHOUGHFLOW TRANSPORT IN MALUKU AND HALMAHERA SEA RELATED TO THE OCCURRENCE OF EL NINO SOUTHERN OSCILLATION." Jurnal Kelautan: Indonesian Journal of Marine Science and Technology 14, no. 3 (February 3, 2022): 243–53. http://dx.doi.org/10.21107/jk.v14i3.12083.

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ABSTRACTMaluku and Halmahera Sea are the entry paths for the Indonesian Throughflow (ITF). This study examined the variation of their current speed, current direction, and transport during the ENSO phases on La Nina in 2010-2011 and El Nino in 2015-2016. The data used were the Marine Copernicus reanalysis data of u and v components of current velocity at 155 m and 266 m of depth. The data were processed by using GrADS to see the direction and speed of the current as well as by calculating the ITF transport. During La Nina, both at 155 m and 266 m of depths were found the eddy patterns. When El Nino occurred, the direction of currents in Maluku Sea was different from La Nina conditions, while the direction of currents in Halmahera Sea had no differences. Current velocity in both oceans at each depth was lower during El Nino than La Nina. The condition of ITF transport in the Maluku Sea during La Nina was dominated by southward movement with a smaller value than during El Nino which generally moved northward meanwhile in the Halmahera Sea had the opposite condition.Keywords: current speed, current direction, ENSO, ITF, transport

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27

Oladejo, K. M. "RELATIONSHIP OF EL NINO/SOUTHERN OSCILLATION TO RAINFALL PATTERNS IN NIGERIA." Open Journal of Environmental Research (ISSN: 2734-2085) 1, no. 1 (March 10, 2020): 1–20. http://dx.doi.org/10.52417/ojer.v1i1.68.

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This paper examines the relationship between El Nino/Southern Oscillation (ENSO) and rainfall patterns in Nigeria. Annual rainfall totals, growing season rainfall totals and annual raindays of 27 Nigerian meteorological stations with varying lengths of records from 1903 to 2012 were collected from the Nigerian Meteorological Agency (NIMET). Monthly Sea Surface Temperatures (SSTs) anomalies data over Atlantic and Pacific Oceans and Southern Oscillation Index (SOI) were obtained from Climatic Prediction Centre (CPC). Kendall tau statistics and Step-Wise Multiple Regression model were used for data analyses. Results from this study showed that annual rainfall totals, growing season rainfall and annual raindays series exhibited a significant downward trend at most of the stations over the period of the study. It was observed that annual rainfall pattern changed from a positive pattern within 1931- 1960 period to a negative pattern within 1961-1990 period and then, to a positive pattern within 1991-2012 period. It was concluded that he alternating wet and dry patterns in inter-annual rainfall fluctuations and by extension, the droughts and floods over Nigeria within the study period, were caused by sea surface temperature anomalies over the Atlantic and Pacific Oceans. The paper therefore concludes that SSTs should be integrated in the seasonal rainfall prediction models in Nigeria for an improved forecast. Oladejo, K. M. | Department of Geography, Usmanu Danfodiyo University, Sokoto, Nigeria

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Bailey, R., and P. W. Glynn. "Global Ecological Consequences of the 1982-83 El Nino Southern Oscillation." Journal of Ecology 79, no. 2 (June 1991): 562. http://dx.doi.org/10.2307/2260738.

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Skidmore, A. K. "Predicting bushfire activity in Australia from El Nino/Southern Oscillation events." Australian Forestry 50, no. 4 (January 1987): 231–35. http://dx.doi.org/10.1080/00049158.1987.10676021.

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GUALDI, SILVIO, ANDREA ALESSANDRI, and ANTONIO NAVARRA. "Impact of atmospheric horizontal resolution on El Nino Southern Oscillation forecasts." Tellus A 57, no. 3 (May 2005): 357–74. http://dx.doi.org/10.1111/j.1600-0870.2005.00108.x.

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Deng, Xiangzheng, Jikun Huang, Fangbin Qiao, Rosamond L. Naylor, Walter P. Falcon, Marshall Burke, Scott Rozelle, and David Battisti. "Impacts of El Nino-Southern Oscillation events on China’s rice production." Journal of Geographical Sciences 20, no. 1 (February 2010): 3–16. http://dx.doi.org/10.1007/s11442-010-0003-6.

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Bi, Peng, Kevin A. Parton, and Shilu Tong. "El Nino–Southern Oscillation and Vector-Borne Diseases in Anhui, China." Vector-Borne and Zoonotic Diseases 5, no. 2 (June 2005): 95–100. http://dx.doi.org/10.1089/vbz.2005.5.95.

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TORRENCE, CHRISTOPHER, and PETER J. WEBSTER. "The annual cycle of persistence in the El Nino/Southern Oscillation." Quarterly Journal of the Royal Meteorological Society 124, no. 550 (July 15, 1998): 1985–2004. http://dx.doi.org/10.1256/smsqj.55009.

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Vakulenko, N. V., and D. M. Sonechkin. "Evidence of the solar Activity’s effect on El Nino Southern Oscillation." Oceanology 51, no. 6 (December 2011): 935–39. http://dx.doi.org/10.1134/s0001437011060208.

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35

Ling, R., C. Logar-Henderson, and D. Fisman. "El Nino southern oscillation predicts vibriosis risk in the United States." International Journal of Infectious Diseases 79 (February 2019): 18. http://dx.doi.org/10.1016/j.ijid.2018.11.060.

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Revadekar, J. V., and Ashwini Kulkarni. "The El Nino-Southern Oscillation and winter precipitation extremes over India." International Journal of Climatology 28, no. 11 (September 2008): 1445–52. http://dx.doi.org/10.1002/joc.1639.

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Ham, Yoo-Geun, In-Sik Kang, Daehyun Kim, and Jong-Seong Kug. "El-Nino Southern Oscillation simulated and predicted in SNU coupled GCMs." Climate Dynamics 38, no. 11-12 (August 26, 2011): 2227–42. http://dx.doi.org/10.1007/s00382-011-1171-5.

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RAJEEVAN, M. "Post monsoon tropical cyclone activity in the north Indian Ocean in relation to the El Nion / southern Oscillation phenomenon." MAUSAM 40, no. 1 (April 28, 2022): 55–58. http://dx.doi.org/10.54302/mausam.v40i1.1934.

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In this paper the relationship between post monsoon (Oct-Dec) tropical cyclone activity in the north Indian Ocean and El Nino Southern Oscillation (ENSO) is discussed. The study uses a 83-year {1901-1983) time series or number of storm days for preliminary analysis. On an average the number of storm days during El Nina year is not departed from the normal. Usin9 the 48-year. (1935-1982) time series of number of storm days correlations were calculated with southern oscillation index (mean sea level pressure difference between Tahiti and Darwin) before, during and after the season: A weak negative correlation is seen between the storm activity and SOI before the season. Stability of correlations is examined by recalculating correlations using four 12-year data subsets. Magnitude of correlations is found to vary significantly in the subsets. There is no appreciable difference between the strike rate (number of storm crossing the coast/total number of storms) per El Nina year and strike rate per non El Nina year. There is no marked shift in the area of formation of storms during El Nino years from the climatologically favourable area:

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Dewi, Sri Mai, and Marzuki Marzuki. "Analisis Pengaruh Pergeseran Lokasi ENSO terhadap Curah Hujan di Indonesia." Jurnal Fisika Unand 9, no. 2 (November 9, 2020): 176–82. http://dx.doi.org/10.25077/jfu.9.2.176-182.2020.

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ENSO (El Nino Southern Oscillation) merupakan gejala penyimpangan suhu permukaan laut di Samudera Pasifik bagian timur dari kondisi normal. Penelitian ini menganalisis dampak dari perbedaan posisi pusat ENSO terhadap curah hujan di Indonesia. Posisi pusat ENSO ditentukan berdasarkan indeks terbesar dari empat indeks Nino selama tahun 1982-2016. Posisi pusat ENSO didefinisikan jauh, menengah dan dekat dari Indonesia ketika indek Nino yang terbesar berturut-turut adalah Nino 1+2, Nino 3 dan Nino 3,4, serta Nino 4. Intensitas curah hujan di setiap posisi ENSO diamati menggunakan data Global Precipitation Climatology Centre (GPCC). Rata-rata curah hujan bulanan pada saat pusat El Nino jauh dari Indonesia lebih tinggi di kawasan Indonesia bagian timur. Selain itu, selama pusat El Nino jauh dari Indonesia, kondisi yang lebih kering teramati di sebagian besar wilayah Indonesia bagian barat dan tengah. Pada sisi lain, rata-rata intensitas curah hujan bulanan pada saat La Nina menengah lebih tinggi dibandingkan La Nina jauh. Perbedaan intensitas curah hujan dari setiap posisi ENSO ini selaras dengan perbedaan pergerakan udara ke atas yang tergambar dari nilai omega dari data reanalisis NCEP dan NCAR. Dengan demikian, posisi ENSO mempengaruhi curah hujan di Indonesia walaupun dampaknya tidak seragam. ENSO (El Nino Southern Oscillation) is a periodic fluctuation in sea surface temperature and other meteorological parameters across the equatorial Pacific Ocean. This study investigates the impact of ENSO's central position on rainfall pattern in Indonesia. The location of the ENSO was determined by the largest index of four Nino indexes during 1982-2016 and itis defined far, medium and close to Indonesia when the largest Nino indexes are Nino 1+2, Nino 3 and Nino 3.4, and Nino 4. Rainfall intensity at each ENSO position was observed using Global Precipitation Climatology Centre (GPCC) data. Average monthly rainfall when the El Nino central position is far from Indonesia is higher in the eastern part of Indonesia. In addition, when the El Nino central position is far from Indonesia, drier conditions are observed in large parts of western and central Indonesia. On the other hand, the average intensity of monthly rainfall during medium position of La Nina is higher than that for La Nina cases with the central position being far from Indonesia. The difference in rainfall intensity from each ENSO position coincides with the difference in upward air movement which is reflected by the omega values from the NCEP and NCAR. reanalysis data. Thus, the position of ENSO influences rainfall in Indonesia even though the impact is not uniform.

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Wang, B., J. Liu, H. J. Kim, P. J. Webster, S. Y. Yim, and B. Xiang. "Northern Hemisphere summer monsoon intensified by mega-El Nino/southern oscillation and Atlantic multidecadal oscillation." Proceedings of the National Academy of Sciences 110, no. 14 (March 18, 2013): 5347–52. http://dx.doi.org/10.1073/pnas.1219405110.

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41

Hasudungan, P., I. Irham, and A. W. Utami. "The impact of el niño southern oscillation and covid-19 on the rice price dynamics in Indonesia: the vector error correction model approach." IOP Conference Series: Earth and Environmental Science 883, no. 1 (October 1, 2021): 012061. http://dx.doi.org/10.1088/1755-1315/883/1/012061.

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Abstract Half of the world's population makes rice a crop of focus because it has many opportunities in the future. However, there are disruptors for rice development in 2020, which are climate variability and COVID-19 Pandemics. El Nino-Southern Oscillation (ENSO) is a climate variability that can threaten the rice price dynamics. Besides that, COVID-19 also has implications for rice price dynamics. The objectives of this paper are: (1) to empirically study the impact of the El Nino-Southern Oscillation on rice price dynamics and (2) to analyze the effect of COVID-19 pandemics on rice price in Indonesia. The study utilized the vector error correction model (VECM) estimation method and the variables used were sea surface temperature (SST), COVID-19 daily cases, rice price, rice production, and rice price regulation. The result is that El Nino has a positive effect on rice prices, which can increase the price level. The opposite is true also for a La Nina shock. COVID-19 also has a positive impact on the daily cost of rice. The results of this study ought to be of interest to rice producers in Indonesia, as well as processors and intermediaries in the rice markets.

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Abdulla, Cheriyeri P., and Abdullah M. Al-Subhi. "Is the Red Sea Sea-Level Rising at a Faster Rate than the Global Average? An Analysis Based on Satellite Altimetry Data." Remote Sensing 13, no. 17 (September 2, 2021): 3489. http://dx.doi.org/10.3390/rs13173489.

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Satellite altimetry sea-level data was taken for nearly three decades (1993–2020) and is used to understand the variability and associated dynamics in the Red Sea sea-level. Seasonally, the sea-level is higher during December–January and lower during August, with a consistent pattern from south to north. The interannual fluctuations in sea-level have a close agreement with the variability in the global climate modes, i.e., El-Nino Southern Oscillation events, East Atlantic-West Russian oscillation, and the Indian Ocean Dipole. The impact of the El-Nino Southern Oscillation mode on sea-level is higher than other climate modes. The Red Sea sea-level was seen to rise at a rate of 3.88 mm/year from 1993–present, which was consistent with the global rate of 3.3 ± 0.5 mm/year. However, a noticeably faster rate of 6.40 mm/year was observed in the Red Sea sea-level from 2000-present.

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43

Mo, Jiaqi, Hui Wang, and Wantao Lin. "PERTURBED SOLUTION OF SEA-AIR OSCILLATOR FOR THE EL NIÑO/LA NINO-SOUTHERN OSCILLATION MECHANISM." Acta Mathematica Scientia 25, no. 4 (October 2005): 710–14. http://dx.doi.org/10.1016/s0252-9602(17)30211-4.

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44

Atmadipoera, Agus S., Agitha Saverti Jasmine, Mulia Purba, and Anastasia R. T. D. Kuswardani. "UPWELLING CHARACTERISTICS IN THE SOUTHERN JAVA WATERS DURING STRONG LA NINA 2010 AND SUPER EL NINO 2015." Jurnal Ilmu dan Teknologi Kelautan Tropis 12, no. 1 (April 27, 2020): 257–76. http://dx.doi.org/10.29244/jitkt.v12i1.28977.

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Seasonal coastal upwelling in the Southern Java waters is considered to be modulated by interannual ocean-atmosphere variability of El Nino Southern Oscillation (ENSO). This study aims to investigate a contrast in seasonal upwelling characteristics during the La Nina 2010 and El Nino 2015 events, by using multi-datasets from INDESO model output and satellite-derived datasets. Distinct characteristics of seasonal upwelling was clearly seen. In La Nina, surface ocean-atmosphere variables were much lower than that observed in El Nino, except for precipitation rate, sea surface temperature, and sea surface height. In La Nina, warmer (27-28°C) and a very freshwater (<33.80psu) were predominant in the upper 45m depth, concealing upwelling cooler water at subsurface. In contrast, in the El Nino, a drastic upwelled subsurface water of isotherms of 25-26°C and isohalines of 34.24-34.44psu were outcropped at the sea surface. Temperature-based upwelling index is -2°C and +4°C, demonstrating the ENSO has strongly modulated the upwelling intensity. A strong eastward South Java Coastal Current (SJCC) was found only in La Nina event. Persistent westward Indonesian Throughflow south of 9.5°S were visible both in different ENSO events. Estimate of Ekman transport derived from model meridional current was intervened strongly by the presence of the SJCC and the ITF.

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45

Nagaraj, Meghana, and Roshan Srivastav. "Spatial multivariate selection of climate indices for precipitation over India." Environmental Research Letters 17, no. 9 (August 26, 2022): 094014. http://dx.doi.org/10.1088/1748-9326/ac8a06.

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Abstract Large-scale interdependent teleconnections influence precipitation at various spatio-temporal scales. Selecting the relevant climate indices based on geographical location is important. Therefore, this study focuses on the spatial multivariate selection of climate indices influencing precipitation variability over India, using the partial least square regression and variable importance of projection technique. 17 climate indices and gridded precipitation dataset (0.25 × 0.25°) from the Indian Meteorological Department for 1951–2020 at a monthly scale are considered. Results show that among all the indices, Nino 4, Nino 1 + 2, Trans Nino Index, Atlantic Multidecadal Oscillation (AMO), quasi-biennial oscillation (QBO), Arctic oscillation (AO), and North Atlantic Oscillation (NAO) have a significant influence on precipitation over India. Further, within homogenous regions, it is found that the Southern Oscillation Index and Nino 3.4 are selected majorly in the South Peninsular compared to other regions. The NAO/AO show a similar pattern and was found to be relevant in the Northeast region (>89%). AMO is selected mainly in Northwest, and West Central (>80%), AMO and QBO at about 70% of grid locations over Central Northeast India. It is to be noted that the number of climate indices identified varies spatially across the study region. Overall, the study highlights identifying the relevant climate indices would aid in developing improved predictive and parsimonious models for agriculture planning and water resources management

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Pillai, Prasanth A., and K. Mohankumar. "Tropospheric biennial oscillation of the Indian summer monsoon with and without the El Nino-Southern Oscillation." International Journal of Climatology 27, no. 15 (2007): 2095–101. http://dx.doi.org/10.1002/joc.1503.

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47

Athirah Suhailah Jalil and Yan-Ling Tan. "Impacts of El Nino and La Nina on Palm Oil Production: Evidence from Selected Palm Oil Producing Countries." Insight Journal 8 (April 7, 2021): 108–19. http://dx.doi.org/10.24191/ij.v8i0.107.

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Palm oil is one of the most important edible oils commercialized in world oils and fats market. However, agriculture is highly vulnerable to climate change. For instance, El Nino is the warm phase of El Nino Southern Oscillation (ENSO) while La Nina is the opposite of El Nino, the cold phase of ENSO. Strong El Nino and La Nina events cause global changes especially in temperature and rainfall, subsequently affect agricultural areas and causing considerable economic losses. Therefore, the objective of this study is to explore the impacts of El Nino and La Nina on palm oil production in selected palm oil producing countries namely Indonesia, Malaysia and Thailand from 1980 to 2019 using the Ordinary Least Square (OLS) multiple regression analysis. The results revealed that area harvested and palm oil price affect palm oil production significantly in all palm oil producing countries. Nevertheless, the ENSO effects are not apparent. Only the El Nino dummy coefficients are negative and statistically significant in Thailand, suggesting that the occurrence of El Nino events is more pronounced than the La Nina events on palm oil production in Thailand. Hence, this study suggests that a good water management system is needed to allow the palm oil to achieve optimum production.

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Chu, Hyun-Jae, Tae-Woong Kim, Jong-Kyu Lee, and Jae-Hong Lee. "Seasonal Relationship between El Nino-Southern Oscillation and Hydrologic Variables in Korea." Journal of Korea Water Resources Association 40, no. 4 (April 30, 2007): 299–311. http://dx.doi.org/10.3741/jkwra.2007.40.4.299.

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Guerra, Carlos G., Lloyd C. Fitzpatrick, Roberto Aguilar, and Barney J. Venables. "Reproductive Consequences of El Nino-Southern Oscillation in Gray Gulls (Larus modestus)." Colonial Waterbirds 11, no. 2 (1988): 170. http://dx.doi.org/10.2307/1520997.

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Shaman, J., and M. Lipsitch. "The El Nino-Southern Oscillation (ENSO)-pandemic Influenza connection: Coincident or causal?" Proceedings of the National Academy of Sciences 110, Supplement_1 (January 17, 2012): 3689–91. http://dx.doi.org/10.1073/pnas.1107485109.

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