Observations of the Turkana Jet and the East African Dry Tropics: The RIFTJet Field Campaign

Munday, Callum; Engelstaedter, Sebastian; Ouma, Gilbert; Ogutu, Geoffrey; Olago, Daniel; Ong'ech, Dennis Onyango; Lees, Thomas; Wanguba, Bonface; Nkatha, Rose; Ogalo, Clinton; Gàlgalo, Roba Ali; Dokata, Abdi Jillo; Kirui, Erick; Hope, Robert; Washington, Richard

doi:10.1175/bams-d-21-0214.1

Cited by 10 publications

(21 citation statements)

References 39 publications

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“…Finally, it is noteworthy that the underestimation of the gap flow in the GRV in ERA5 agrees with the underestimation of the Turkana Jet recently found by Munday et al (2022) based on radiosonde observations. Similar to the gap flow in the GRV, the Turkana Jet does not only exhibit a strong diurnal cycle due to the thermal forcing (Munday et al, 2022) but is also affected by synoptic-scale pressure gradients associated with low-level ridging along the East African coast (Vizy and Cook, 2019).…”

Section: Discussionsupporting

confidence: 88%

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Dynamics of gap winds in the Great Rift Valley, Ethiopia: emphasis on strong winds at Lake Abaya

Weiß

Gohm

Rotach

et al. 2022

Weather Clim. Dynam.

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Abstract. Lake Abaya, located in the Great Rift Valley (GRV) in Ethiopia, is affected by regularly occurring strong winds that cause water waves, which in turn affect the lake's ecology and food web. The driving forces for these winds, however, are yet unexplained. Hence, the main goal of this study is to provide a physical explanation for the formation of these strong winds in the GRV and especially at Lake Abaya. To this aim, two case studies were performed based on measurements, ERA5 reanalysis data and mesoscale numerical simulations conducted with the Weather Research and Forecasting (WRF) model. The simulations revealed that in both cases a gap flow downstream of the narrowest and highest part of the GRV (i.e. the pass) led to high wind speeds of up to 25 m s−1. Two types of gap flow were identified: a north-eastern gap flow and a south-western gap flow. The wind directions are in line with the orientation of the valley axis and depend on the air mass distribution north and south of the valley and the resulting along-valley pressure gradient. The air mass distribution was determined by the position of the Intertropical Convergence Zone relative to the GRV. The colder air mass was upstream of the GRV in both case studies. During the day, the convective boundary layer in the warmer air mass on the downstream side heated up more strongly and quickly than in the colder air mass. The most suitable variable describing the timing of the gap flow was found to be the pressure gradient at pass height, which corresponds roughly to the 800 hPa pressure level. In both cases the gap flow exhibited a strong daily cycle, which illustrates the importance of the thermal forcing due to differential heating over complex terrain in addition to the large-scale forcing due to air mass differences. The start, strength, and the duration of the gap winds within the valley depended on location. For both cases, the strongest winds occurred after sunset and in the ongoing night downstream of the gap and on the corresponding lee slope. The ERA5 reanalysis captures both events qualitatively well but with weaker wind speeds than in the mesoscale numerical simulations. Hence, ERA5 is suitable for a future climatological analysis of these gap flows.

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Section: Discussionsupporting

confidence: 88%

“…Again, this led to differential air mass advection in the lower troposphere. Potentially warmer air from north-eastern Africa was advected towards the Afar Triangle, whereas the Turkana Jet (Nicholson, 2016;Munday et al, 2022) brought potentially colder air into the Turkana Channel and the region around Lake Abaya (Fig. 2b).…”

Section: Synoptic Conditionsmentioning

confidence: 99%

Dynamics of gap winds in the Great Rift Valley, Ethiopia: emphasis on strong winds at Lake Abaya

Weiß

Gohm

Rotach

et al. 2022

Weather Clim. Dynam.

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“…However, we note that differences in moisture convergence in the ERA5 reanalysis are not large enough to balance the precipitation differences observed in the IMERG dataset. This is perhaps unsurprising given that ERA5 underestimates the true strength of the Turkana jet (Munday et al ., 2022).…”

Section: Resultsmentioning

confidence: 99%

“…The orography of East Africa, shown in Figure 1a, influences the direction and strength of the low‐tropospheric wind (Kinuthia, 1992; Indeje et al ., 2001) and drives spatial rainfall variations (Nicholson, 2017; Vizy and Cook, 2019; Munday et al ., 2021). A key feature of the East African climate that is influenced by orography and has been observed by radiosondes (Kinuthia and Asnani, 1982; Kinuthia, 1992; Munday et al ., 2022) is the Turkana jet, a strong southeasterly low‐level jet at approximately 850 hPa between the Ethiopian Highlands and East African Highlands (Figure 1a). Modelling experiments (Indeje et al ., 2001) and observations of higher jet speeds across narrower parts of the channel (Kinuthia, 1992) suggest a Bernoulli forcing on jet characteristics and that the shape of the Turkana channel controls the low‐level jet's orientation and direction.…”

Section: Introductionmentioning

confidence: 99%

Surface‐driven amplification of Madden–Julian oscillation circulation anomalies across East Africa and its influence on the Turkana jet

Talib

Taylor

Harris

et al. 2023

Quart J Royal Meteoro Soc

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In semi‐arid environments, rainfall‐driven soil moisture fluctuations exert a strong influence on surface turbulent fluxes. Intraseasonal rainfall variability can therefore impact low‐level atmospheric temperatures and influence regional circulations. Using satellite observations and an atmospheric reanalysis, we investigate whether rainfall variability induced by the Madden–Julian oscillation (MJO) triggers land–atmosphere feedbacks across East Africa. We identify that surface fluxes during the East African wet seasons (March–May and October–December) are sensitive to MJO‐induced precipitation variations across low‐lying regions of South Sudan and highland regions of Uganda and southwest Kenya. For example, during MJO phases 6 to 8, when rainfall is suppressed, surface temperatures and sensible heat fluxes increase, whilst evapotranspiration decreases. Spatial variations in the surface flux response to rainfall variability feed back onto the atmosphere through amplifying MJO‐associated pressure anomalies. During dry MJO events for instance, surface warming across the exit region of the Turkana channel increases the low‐tropospheric along‐channel pressure gradient and intensifies the Turkana jet. We conclude that average surface‐driven temperature fluctuations during a single day are responsible for approximately 12% of MJO‐associated variability of the Turkana jet speed. However, we expect that the accumulation of heat over multiple days to the west of the East African Highlands further amplifies anomalies in the pressure gradient and jet intensity. Modelling experiments are required to quantify the accumulated impact of the surface forcing. Surface‐driven Turkana jet variations influence the East African moisture budget and affect the intensity and inland propagation of coastal convection. Not only is this the first study to investigate the importance of intraseasonal land–atmosphere feedbacks across East Africa, but it is also the first to show that Turkana jet characteristics are partly driven by surface conditions. This work motivates an investigation into whether subseasonal forecast models fully harness the predictability from surface‐induced jet variations.

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“…This may have some limitations, especially for wind power generation, as previous studies have highlighted potential issues with ERA5 (Bloomfield et al, 2020; Ramon et al, 2019). Using observed data of the Turkana Jet Munday et al, 2022 found that ERA5 underestimates low‐level wind speeds in the Turkana Jet region by around 30%. King et al (2021) shows three different reanalysis products perform quite differently over Kenya; however, the lack of available observational wind data makes it difficult to determine which is most accurate.…”

Section: Discussionmentioning

confidence: 99%

Characterizing the variability and meteorological drivers of wind power and solar power generation over Africa

Bloomfield

Wainwright

Mitchell

2022

Meteorological Applications

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Sub‐Saharan Africa (SSA) has the lowest energy access rates in the world, which poses a key barrier to power system development. Deployment of renewables, including wind and solar power, will play a key role in expanding electricity supply across SSA: distributed generation (enabling access for remote communities), cost‐effectiveness and low emissions are key advantages. However, renewable generation is weather dependent; therefore, including more renewables increases the amount of meteorologically driven variability in the power system. Two countries in SSA are chosen for detailed investigation of this meteorologically driven variability: Senegal in West Africa and Kenya in East Africa. These are chosen due to being areas of dense population, where there is operational wind and solar power, and plans for regional expansion. In Senegal, solar generation is fairly consistent throughout the year, while wind generation exhibits strong seasonality, with a peak in the boreal spring. Low wind and solar power generation days during the boreal summer are found to be related to the passage of African Easterly Waves. Over Kenya, both wind and solar generation exhibit seasonal variability, with wind generation peaking during boreal autumn, and solar generation at a minimum during boreal summer. Inter‐annual variability in generation is greater over Kenya than over Senegal; the El Nino Southern Oscillation is found to impact wind and solar generation over Kenya. El Nino phases are associated with lower wind and solar generation in October–December over Kenya, but higher generation in July–September. This improved understanding of variability will assist system planners in designing reliable future energy systems.

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Observations of the Turkana Jet and the East African Dry Tropics: The RIFTJet Field Campaign

Cited by 10 publications

References 39 publications

Dynamics of gap winds in the Great Rift Valley, Ethiopia: emphasis on strong winds at Lake Abaya

Dynamics of gap winds in the Great Rift Valley, Ethiopia: emphasis on strong winds at Lake Abaya

Surface‐driven amplification of Madden–Julian oscillation circulation anomalies across East Africa and its influence on the Turkana jet

Characterizing the variability and meteorological drivers of wind power and solar power generation over Africa

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