Influence of the Indian Ocean Dipole on the Southern Oscillation.

Behera, Swadhin K.; Yamagata, Toshio

doi:10.2151/jmsj.81.169

Cited by 200 publications

(99 citation statements)

References 18 publications

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“…In contrast, the pattern of correlations for September is quite different, and that for December is statistically insignificant. In October and November, the co-occurrence of anomalies over the east equatorial pacific and Indian Oceans (Black et al 2003), and the Zonal Dipole Mode over the Indian Ocean (IOD) (Saji et al 1999;Behera and Yamagata 2003;Saji and Yamagata 2003;Marchant et al 2006) are known to affect the equatorial east African Short rains, and here we show there are also significant correlations with southern Ethiopia. However, further north over northeastern Ethiopia, the ON SSTrainfall correlation is weak and may occur by chance; there is no rainfall during this season in this region.…”

Section: Definition Of the Rainfall Seasonssupporting

confidence: 50%

“…Only Diro et al (2008) has used the SST anomalies from the Atlantic, Indian and Pacific Oceans to predict the MAM rainfall. Although no study has been conducted for the southern Ethiopian September-November season, available studies conducted for the wider region of Equatorial East Africa (Saji et al 1999;Behera and Yamagata 2003;Black et al 2003;Marchant et al 2006;Saji and Yamagata 2003) show that anomalous warming (cooling) over the equatorial East Pacific and Indian Ocean are associated with enhanced (suppressed) rainfall amounts in this wider region. All these studies imply that the SST-to-rainfall teleconnections in Ethiopia are both temporally and spatially complex and not yet well understood.…”

Section: Introductionmentioning

confidence: 99%

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Teleconnections between Ethiopian rainfall variability and global SSTs: observations and methods for model evaluation

Degefu

Rowell

Bewket

2016

Meteorol Atmos Phys

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Rainfall variability in Ethiopia has significant effects on rainfed agriculture and hydropower, so understanding its association with slowly varying global sea surface temperatures (SSTs) is potentially important for prediction purposes. We provide an overview of the seasonality and spatial variability of these teleconnections across Ethiopia. A quasi-objective method is employed to define coherent seasons and regions of SST-rainfall teleconnections for Ethiopia. We identify three seasons (March-May, MAM; July-September, JAS; and OctoberNovember, ON), which are similar to those defined by climatological rainfall totals. We also identify three new regions (Central and western Ethiopia, CW-Ethiopia; Southern Ethiopia, S-Ethiopia; and Northeast Ethiopia, NE-Ethiopia) that are complementary to those previously defined here based on distinct SST-rainfall teleconnections that are useful when predicting interannual anomalies. JAS rainfall over CW-Ethiopia is negatively associated with SSTs over the equatorial east Pacific and Indian Ocean. New regional detail is added to that previously found for the whole of East Africa, in particular that ON rainfall over S-Ethiopia is positively associated with equatorial east Pacific SSTs and with the Indian Ocean Dipole (IOD). Also, SST-to-rainfall correlations for other season-regions, and specifically for MAM in all regions, are found to be negligible. The representation of these teleconnections in the HadGEM2 and HadGEM3-GA3.0 coupled climate models shows mixed skill. Both models poorly represent the statistically significant teleconnections, except that HadGEM2 and the low resolution (N96) version of Had-GEM3-GA3.0 better represent the association between the IOD and S-Ethiopian ON rainfall. Additionally, both models are able to represent the lack of SST-rainfall correlation in other seasons and other parts of Ethiopia.

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Section: Definition Of the Rainfall Seasonssupporting

confidence: 50%

Section: Introductionmentioning

confidence: 99%

Teleconnections between Ethiopian rainfall variability and global SSTs: observations and methods for model evaluation

Degefu

Rowell

Bewket

2016

Meteorol Atmos Phys

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“…The value for the former association is −0.48 for the period SON while that for latter is −0.40 for the period NDJ. These periods of strongest correlations are consistent with the periods of their maximum activity in their respective oceans (Reason and Mulenga, 1999;Behera and Yamagata, 2003). SON is then adopted for the construction of the IODZM index while NDJ is used for the ENSO index.…”

Section: Progressive Association Of Enso and Iodzm With Zim Spimentioning

confidence: 81%

“…While on the other hand, others like Webster et al (1999) ;Iizuka et al (2000); Rao et al (2002); Yamagata et al (2002); Ashok et al (2003); Gualdi et al (2003); Lau and Nath (2004); Behera et al (2005) contradict these findings by presenting the independence of the IODZM mode from ENSO. At the same time, Behera and Yamagata (2003); Saji and Yamagata (2003); Ashok et al (2004a); Yamagata et al (2004) also further acknowledged that both phenomena interact with each other.…”

Section: Introductionmentioning

confidence: 91%

The impact of the positive Indian Ocean dipole on Zimbabwe droughts

Manatsa

Chingombe

Matarira

2008

Intl Journal of Climatology

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A comparative study of the impact of the anomalous positive Indian Ocean SST gradient, referred to as the Indian Ocean Dipole/Zonal Mode (IODZM), and El Niño-Southern Oscillation (ENSO) on Zimbabwe seasonal rainfall variability for the period 1940-1999, is documented. Composite techniques together with simple and partial correlation analyses are employed to segregate the unique association related to IODZM/ENSO with respect to the Zimbabwe seasonal rainfall.The analysis reveals that the IODZM impact on the country's summer rainfall is overwhelming as compared to that of ENSO when the two are in competition. The IODZM influence remains high (significant above 99% confidence level), even after the influence of ENSO has been removed, while that of ENSO collapses to insignificance (even at 90% confidence level) when the IODZM contribution is eliminated. The relationship between ENSO and Zimbabwe seasonal rainfall seems to be sustained through El Niño occurring in the presence of positive IODZM events. However, when the co-occurring positive IODZM and El Niño events are removed from the analysis, it is apparently clear that ENSO has little to do with the country's rainfall variability. On the other hand, positive IODZM is mostly associated with the rainfall deficits, whether or not it co-occurs with El Niño. However, the co-occurrence of the two events does not necessarily suggest that El Niño influences droughts through the positive IODZM events. The El Niño event components during co-occurrence seem to be unrelated (at least linearly) to the droughts, while the positive IODZM events display a relatively strong relationship that is significant above the 95% confidence level. It thus becomes important to extend the study of this nature to cover the whole of southern Africa, so that the extent of the impact of the phenomena can be realized over the whole region.

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“…Study by Mapande and Reason [8] suggest this anticyclonic circulation feature in November and February to be possibly part of the local atmospheric response of cool SST anomaly in the tropical south Indian Ocean. Moreover, tropical Indian Ocean is seen to be dominated by easterlies during this peak season as the result of warming of the SST in the west and cooling in the East Indian Ocean [28]. Taken together with this, the extreme continental southward location of ITCZ between Tanzania and central Mozambique during December and February [3,4,6,7], suggests a substantial rainfall over southern Tanzania during this period.…”

Section: Wind Flow Pattern At 850 Hpa Level and Sst Anomalymentioning

confidence: 82%

Climate Characteristics over Southern Highlands Tanzania

Mbululo¹,

Nyihirani²

2012

ACS

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This study was conducted to examine the climate characteristic of southern highland Tanzania (Latitude 6˚S -12˚S and Longitude 29˚E -38˚E). The study findings reveal that rainfall over the region is linked with SST over the Indian Ocean, where warmer (cooler) western Indian Ocean is accompanied by high (low) amount of rainfall over Tanzania. During wet (dry) years, weaker (stronger) equatorial westerlies and anticyclone (cyclonic) anomaly over the southern tropics act to reduce (enhance) the export of equatorial moisture away from East Africa. The wettest (driest) season was found to be 1978/79 (1999/00) which can be classified as the severely wet (moderate drought). Two different modes of rainfall have been identified at time scale of 1.5 and 6 years which have been associated with the quasi biennial oscillation (QBO) and El Nino Southern Oscillation (ENSO), respectively.

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Influence of the Indian Ocean Dipole on the Southern Oscillation.

Cited by 200 publications

References 18 publications

Teleconnections between Ethiopian rainfall variability and global SSTs: observations and methods for model evaluation

Teleconnections between Ethiopian rainfall variability and global SSTs: observations and methods for model evaluation

The impact of the positive Indian Ocean dipole on Zimbabwe droughts

Climate Characteristics over Southern Highlands Tanzania

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