Modulation of East African boreal fall rainfall: combined effects of the Madden Julian Oscillation (MJO) and El Niño Southern Oscillation (ENSO)

2021 ◽  
pp. 1-42
Keyword(s):  
East Africa ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Combined Effects ◽  
Madden Julian Oscillation ◽  
East African

Abstract Climate variabilities can have significant impacts on rainfall in East Africa, leading to disruption in natural and human systems and affecting the lives of tens of millions of people. Subseasonal and interannual variabilities are critical components of total rainfall variability in the region. The goal of this study is to examine the combined effects of the Madden Julian Oscillation (MJO), operating at subseasonal timescale, and the El Niño Southern Oscillation (ENSO), operating at an interannual scale, on the modulation of East African boreal fall (October-November-December; OND) rainfall, commonly called the short rains. Composite analysis shows that daily rainfall responses depend on MJO phase and its interaction with ENSO state. In particular, MJO modulation of rainfall is generally stronger under El Niño conditions relative to ENSO neutral and La Niña conditions, leading to increased potential for daily precipitation excesses during wet MJO phases under El Niño. There is evidence for both dynamic and thermodynamic mechanisms associated with these impacts, including an increase in westerly moisture transport and easterly advection of temperature and moist static energy. Seasonal analysis shows that the frequency and intensity of wet MJO phases during an El Niño contribute notably to the seasonal total precipitation anomaly. This suggests that MJO can mediate El Niño’s impact on OND rainfall in East Africa.

scholarly journals An Analysis of Anomalous Winter and Spring Tornado Frequency by Phase of the El Niño/Southern Oscillation, the Global Wind Oscillation, and the Madden-Julian Oscillation

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Todd W. Moore ◽  
Jennifer M. St. Clair ◽  
Tiffany A. DeBoer
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
La Niña ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Madden Julian Oscillation ◽  
La Nina ◽  
Upper Level ◽  
Favorable Conditions

Winter and spring tornado activity tends to be heightened during the La Niña phase of the El Niño/Southern Oscillation and suppressed during the El Niño phase. Despite these tendencies, some La Niña seasons have fewer tornadoes than expected and some El Niño seasons have more than expected. To gain insight into such anomalous seasons, the two La Niña winters and springs with the fewest tornadoes and the two El Niño winters and springs with the most tornadoes between 1979 and 2016 are identified and analyzed in this study. The relationships between daily tornado count and the Global Wind Oscillation and Madden-Julian Oscillation in these anomalous seasons are also explored. Lastly, seasonal and daily composites of upper-level flow, low-level flow and humidity, and atmospheric instability are generated to describe the environmental conditions in the anomalous seasons. The results of this study highlight the potential for large numbers of tornadoes to occur in a season if favorable conditions emerge in association with individual synoptic-scale events, even during phases of the El Niño/Southern Oscillation, Global Wind Oscillation, and Madden-Julian Oscillation that seem to be unfavorable for tornadoes. They also highlight the potential for anomalously few tornadoes in a season even when the oscillations are in favorable phases.

Modulation of the Global Atmospheric Circulation by Combined Activity in the Madden–Julian Oscillation and the El Niño–Southern Oscillation during Boreal Winter

2010 ◽  
Vol 23 (15) ◽  
pp. 4045-4059 ◽  
Author(s):  
Paul E. Roundy ◽  
Kyle MacRitchie ◽  
Jonas Asuma ◽  
Timothy Melino
Keyword(s):  
North Atlantic ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Boreal Winter ◽  
Madden Julian Oscillation ◽  
The North ◽  
The North Atlantic

Abstract Composite global patterns associated with the El Niño–Southern Oscillation (ENSO) and the Madden–Julian oscillation (MJO) are frequently applied to help make predictions of weather around the globe at lead times beyond a few days. However, ENSO modulates the background states through which the MJO and its global response patterns propagate. This paper explores the possibility that nonlinear variations confound the combined use of composites based on the MJO and ENSO separately. Results indicate that when both modes are active at the same time, the associated patterns in the global flow are poorly represented by simple linear combinations of composites based on the MJO and ENSO individually. Composites calculated by averaging data over periods when both modes are present at the same time more effectively describe the associated weather patterns. Results reveal that the high-latitude response to the MJO varies with ENSO over all longitudes, but especially across the North Pacific Rim, North America, and the North Atlantic. Further analysis demonstrates that the MJO influence on indexes of the North Atlantic Oscillation is greatest during La Niña conditions or during periods of rapid adjustment in the phase of ENSO.

scholarly journals Faktor Osean – Atmosfer untuk Memprediksi Titik Panas (Hostspot) di Wilayah Asia Tenggara Bagian Selatan

2021 ◽  
pp. 116-130
Author(s):  
Santriwati Santriwati ◽  
Halmar Halide ◽  
Hasanuddin Hasanuddin
Keyword(s):  
Indian Ocean ◽  
Multiple Regression ◽  
El Niño ◽  
Indian Ocean Dipole ◽  
El Nino ◽  
Southern Oscillation ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Madden Julian Oscillation

Penelitian ini bertujuan untuk membuat pemodelan prediksi titik panas (hotspot) di wilayah Asia Tenggara bagian Selatan dengan sejumlah prediktor signifikan menggunakan Model Multiple Regression (MR) dan untuk melakukan verifikasi prediksi model tersebut. Data yang digunakan dalam penelitian ini yaitu data observasi titik panas (hotspot) di Wilayah Indonesia yakni di Pulau Kalimantan dan Sumatera dan di Wilayah Semenanjung Malaysia serta Sabah-Sarawak. Kemudian data indeks El Nino Southern Oscillation (ENSO), Madden-Julian Oscillation (MJO), Indian Ocean Dipole (IOD) dan Monsun selama 6 tahun mulai dari tahun 2013 hingga 2018 sebagai data prediktor. Metode yang digunakan yaitu Model Multiple Regression dengan Metode Regresi Stepwise dan verifikasi skill model prediksi yang digunakan yaitu Korelasi Pearson dan RMSE. Berdasarkan hasil pemodelan dan verifikasi prediksi terbaiknya, diperoleh nilai Korelasi Pearson sebesar 0,698 dan nilai RMSE-nya sebanyak 908 hotspot. Untuk model prediksi di wilayah Sumatera oleh 7 prediktor signifikan yang terkait dengan kejadian hotspot yaitu, IOD 0 (IOD pada bulan munculnya hotspot), MJO 0, MJO 9, MJO 10, Mons 1, MJO 8, dan MJO 5. Untuk wilayah Kalimantan nilai Korelasi Pearson sebesar 0,795 dan nilai RMSE-nya sebanyak 1150 hotspot oleh 4 prediktor signifikan, MJO 9 (MJO pada 9 bulan sebelum munculnya hotspot), Mons 1, Mons 0, dan ENSO 3. Untuk wilayah Semenanjung Malaysia diperoleh nilai Korelasi Pearson sebesar 0,145 dan nilai RMSE-nya sebanyak 135 hotspot oleh 2 prediktor signifikan, Mons 2 (Mons pada 2 bulan sebelum munculnya hotspot) dan MJO 0. Kemudian untuk wilayah Sabah dan Sarawak diperoleh nilai Korelasi Pearson sebesar 0,242 dan nilai RMSE-nya sebanyak 113 hotspot oleh 2 prediktor signifikan, IOD 2 (IOD pada 2 bulan sebelum munculnya hotspot) dan MJO 0. Untuk wilayah Sumatera prediktor yang paling berpengaruh yaitu IOD 0, yakni fenomena IOD khususnya fenomena IOD (+) penyebab terjadinya musim kering ini beberapa kali terjadi di wilayah Pulau Sumatera karena letaknya berdekatan langsung dengan Samudera Hindia sehingga iklimnya juga dipengaruhi oleh lautan di dekatnya. Untuk fenomena MJO dan Monsun yang paling berpengaruh di Wilayah Kalimantan (MJO 9), Semenanjung Malaysia (Mons 2) serta Sabah - Sarawak (MJO 0). Kedua fenomena tersebut secara periodik selalu melintas di ketiga wilayah tadi khususnya berkontribusi pada bulan-bulan terjadinya musim kering, sehingga diindikasikan dapat mempengaruhi munculnya hotspot.

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