Teleconnections between Ethiopian summer rainfall and sea surface temperature: part I—observation and modelling

Diro, G. T.; Grimes, D. I. F.; Black, Emily

doi:10.1007/s00382-010-0837-8

Cited by 136 publications

(159 citation statements)

References 27 publications

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“…8b). The warming over the tropical Eastern Pacific tends to reduce Ethiopian precipitation (Segele et al 2009a;Diro et al 2011a). Thus the SSTA pattern in the eastern tropical Pacific is unlikely to explain the projected precipitation changes (Fig.…”

Section: Future Changes To the Nashmentioning

confidence: 99%

“…These systems directly influence precipitation over Ethiopia (Nicholson and Grist 2003;Segele and Lamb 2005), and the impact of SSTA modes on Ethiopian precipitation is primarily driven by modifications to the abovementioned systems (e.g. Rowell 2003;Segele and Lamb 2005;Shanahan et al 2009;Ummenhofer et al 2009;Diro et al 2011a). Figure 5 summarizes the observed and modeled relationships among the three large-scale circulation systems and Ethiopian precipitation in the Kiremt season.…”

Section: Factors Contributing To Kiremt-season Precipitationmentioning

confidence: 99%

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CMIP5 model simulations of Ethiopian Kiremt-season precipitation: current climate and future changes

Ballard

et al. 2015

Clim Dyn

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over central Highlands and northern Great Rift Valley in Ethiopia, but a decrease in precipitation over the southern part of the country. Such a dipole pattern is attributable to the intensification of the North Atlantic subtropical high (NASH) in a warmer climate, which influences Ethiopian Kiremt-season precipitation mainly by modulating atmospheric vertical motion. Diagnosis of the omega equation demonstrates that an intensified NASH increases (decreases) the advection of warm air and positive vorticity into the central Highlands and northern Great Rift Valley (southern part of the country), enhancing upward motion over the northern Rift Valley but decreasing elsewhere. Under the RCP 4.5 scenario, the high-resolution models project an intensification of the NASH by 15 (3 × 10 5 m 2 s −2 ) geopotential meters (stream function) at the 850-hPa level, contributing to the projected precipitation change over Ethiopia. The influence of the NASH on Kiremtseason precipitation becomes more evident in the future due to the offsetting effects of two other major circulation systems: the East African Low-level Jet (EALLJ) and the Tropical Easterly Jet (TEJ). The high-resolution models project a strengthening of the EALLJ, but a weakening of the TEJ. Future changes in the EALLJ and TEJ will drive this precipitation system in opposite directions, leading to small or no net changes in precipitation in Ethiopia.

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Section: Future Changes To the Nashmentioning

confidence: 99%

Section: Factors Contributing To Kiremt-season Precipitationmentioning

confidence: 99%

CMIP5 model simulations of Ethiopian Kiremt-season precipitation: current climate and future changes

Ballard

et al. 2015

Clim Dyn

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“…For group B, it is also shown from Table 4 that influences also are obtained from Niño 3, the Indian Ocean and as far as the extra-tropical Southern Hemisphere. The annual rainfall in Sudan and Ethiopia (group B) has been shown in a number of studies to be influenced by the El Niño-Southern Oscillation (ENSO); see Osman and Shamseldin (2002) for Sudan; Fontaine and Janicot (1992), and Grist and Nicholson (2001) for the Sahel belt; Abtew et al (2009), Beltrando andCamberlin (1993), Diro et al (2010), Korecha and Barnston (2007), Seleshi and Demarée (1995), Segele and Lamb (2005), and Seleshi and Zanke (2004) for Ethiopia.…”

Section: Identification Of Drivers For the Rainfall Variabilitymentioning

confidence: 99%

Spatial and temporal variability of rainfall in the Nile Basin

Onyutha

Willems

2015

Hydrol. Earth Syst. Sci.

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Abstract. Spatiotemporal variability in annual and seasonal rainfall totals were assessed at 37 locations of the Nile Basin in Africa using quantile perturbation method (QPM). To get insight into the spatial difference in rainfall statistics, the stations were grouped based on the pattern of the long-term mean (LTM) of monthly rainfall and that of temporal variability. To find the origin of the driving forces for the temporal variability in rainfall, correlation analyses were carried out using global monthly sea level pressure (SLP) and sea surface temperature

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“…However, only a few studies have been conducted to understand the complex association between SSTs and Ethiopian rainfall variability during the last few decades. Most of these have focused on the predictability of June-September rainfall (Gissila et al 2004;Korecha and Barnston 2007;Diro et al 2011a). These and other related studies, such as Segele et al (2009a, b);and Diro et al (2011a) suggest that the interannual rainfall variability during this season is ultimately controlled by large-scale SST anomalies over the equatorial east Pacific (the El Niño-Southern Oscillation; ENSO) and the Indian Ocean, where warming/cooling events are associated with deficit/excess of rainfall over the central and northern half of the country.…”

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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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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Teleconnections between Ethiopian summer rainfall and sea surface temperature: part I—observation and modelling

Cited by 136 publications

References 27 publications

CMIP5 model simulations of Ethiopian Kiremt-season precipitation: current climate and future changes

CMIP5 model simulations of Ethiopian Kiremt-season precipitation: current climate and future changes

Spatial and temporal variability of rainfall in the Nile Basin

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

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