Horizontal and Vertical Structure of the Lake Turkana Jet

Kinuthia, J. H.

doi:10.1175/1520-0450(1992)031<1248:havsot>2.0.co;2

Cited by 47 publications

(87 citation statements)

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“…It persists throughout the year, and is formed by orographic channeling of the flow (Kinuthia and Asnani 1982;Kinuthia 1992). A negative correlation between the strength of the Turkana jet and the Somali jet is found in regional model simulations (Vizy and Cook 2003), although the authors note that the Turkana jet should be investigated further with higher resolution simulations.…”

Section: Climate Variability: East Africamentioning

confidence: 99%

Sub-Saharan Northern African climate at the end of the twenty-first century: forcing factors and climate change processes

Patricola

Cook

2010

Clim Dyn

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A regional climate model, the Weather Research and Forecasting (WRF) Model, is forced with increased atmospheric CO 2 and anomalous SSTs and lateral boundary conditions derived from nine coupled atmosphere-ocean general circulation models to produce an ensemble set of nine future climate simulations for northern Africa at the end of the twenty-first century. A well validated control simulation, agreement among ensemble members, and a physical understanding of the future climate change enhance confidence in the predictions. The regional model ensembles produce consistent precipitation projections over much of northern tropical Africa. A moisture budget analysis is used to identify the circulation changes that support future precipitation anomalies. The projected midsummer drought over the Guinean Coast region is related partly to weakened monsoon flow. Since the rainfall maximum demonstrates a southward bias in the control simulation in July-August, this may be indicative of future summer drying over the Sahel. Wetter conditions in late summer over the Sahel are associated with enhanced moisture transport by the West African westerly jet, a strengthening of the jet itself, and moisture transport from the Mediterranean. Severe drought in East Africa during August and September is accompanied by a weakened Indian monsoon and Somali jet. Simulations with projected and idealized SST forcing suggest that overall SST warming in part supports this regional model ensemble agreement, although changes in SST gradients are important over West Africa in spring and fall. Simulations which isolate the role of individual climate forcings suggest that the spatial distribution of the rainfall predictions is controlled by the anomalous SST and lateral boundary conditions, while CO 2 forcing within the regional model domain plays an important secondary role and generally produces wetter conditions.

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Section: Climate Variability: East Africamentioning

confidence: 99%

Sub-Saharan Northern African climate at the end of the twenty-first century: forcing factors and climate change processes

Patricola

Cook

2010

Clim Dyn

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“…The main forcing of this strong, easterly, all-year wind is orographic, as the air is led between the mountains of southern Ethiopia and northern Kenya (Kinuthia and Asnani, 1982;Kinuthia, 1992;Indeje et al, 2001). In the summer season, the Turkana Jet may be considered a branch of the Somali Jet, though a full documentation of the relationship between the two systems is still lacking (Vizy and Cook, 2003;Riddle and Cook, 2008).…”

Section: The Summer Circulation Around Ethiopiamentioning

confidence: 99%

Moisture transport into the Ethiopian highlands

Viste

Sorteberg

2011

Intl Journal of Climatology

134

107

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ABSTRACT:The Ethiopian summer rains occur as air masses of various origins converge above the Ethiopian plateau. In this study, the relative importance of different moisture transport branches has been estimated using the Lagrangian trajectory model FLEXPART, and ERA-Interim reanalysis data, to backtrack air reaching the northern Ethiopian highlands in July-August 1998-2008. The Indian Ocean, the Congo Basin and the Red Sea were found to be important moisture source regions; for air from the Indian Ocean aided by a considerable moisture uptake along routes across the African continent. The following main transport branches were identified: (1) Flow from the Gulf of Guinea, (2) Flow from the Indian Ocean, and (3) Flow from the north; from the Mediterranean region across the Red Sea and the Arabian Peninsula. The largest contribution to the moisture transport into, and release of moisture within, the northern Ethiopian highlands, was associated with air traveling from the Indian Ocean and from the north. This was partly due to the relatively high mean specific humidity of this air, and partly because a large proportion of the air that reaches the highlands, follows these routes. As a total, the amount of moisture brought into the highlands from the north is 46% higher than from the south, whereas the contribution to moisture release within the highlands is about equal for air coming from the south and from the north. While previous studies have emphasized the importance of the Gulf of Guinea, we find that despite the high specific humidity of the low-level flow of air from the Gulf of Guinea, the amount of moisture carried into and released within the northern Ethiopian highlands through this branch, is much smaller than from the other branches -about 1/8 of that from the Indian Ocean. This is due to the fact that normally only a small proportion of the air reaching Ethiopia comes from the Gulf of Guinea.

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“…During this monsoon season, the southeast trade winds in the Southern Hemisphere are channeled by the east African highlands while crossing the Equator and become a southwest monsoon flow. They are further diverted by the Turkana Channel, enhancing convergence with the westerlies/southwesterlies above the western Ethiopian highlands and bringing moisture to the region (Kinuthia, 1992;Nicholson, 1996Nicholson, , 2014Camberlin, 1997;Slingo et al, 2005;Segele et al, 2009). In addition, the effect of other hydroclimate variables, such as Indian Ocean SST, local and regional atmospheric pressure systems (e.g., Azores High) also have notable influence on Ethiopia's precipitation variability (e.g., Kassahun, 1987;Tadesse, 1994;NMSA, 1996;Shanko and Camberlin, 1998;Goddard and Graham, 1999;Latif et al, 1999;Black et al, 2003;Segele and Lamb, 2005).…”

Section: Application To Western Ethiopia and Objectives Of The Studymentioning

confidence: 99%

Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

Zhang

Moges

Block

2018

Hydrol. Earth Syst. Sci.

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Abstract. Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills. Primer on prediction models and cluster analysisSeasonal precipitation prediction can provide potentially actionable information to guide management of various sectoral activities. For instance, precipitation prediction is often translated into a hydrological forecast, which can be used to optimize reservoir operations, provide early flood or drought warning, inform waterway navigation, etc. As a primary input to soil moisture, precipitation prediction is also essential to agricultural management -farmers can take advantage of anticipated preferable climatic conditions or avoid unnecessary costs under expected undesirable conditions. Two types of models are commonly used for seasonal precipitation prediction: statistical and dynamical. Dynamical models, such as general circulation models (GCMs), include complex physical climate processes, while statistical models are purely data driven, relating observations and hydroclimate variables directly.While both modeling approaches have produced skillful seasonal predictions for a variety of applications (e.g., Barrett, 1993;Hammer et al., 2000;Shukla et al., 2016), each has noteworthy drawbacks. Dynamical models often require a great amount of time to build and parameterize, whereas statistical models require c...

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Horizontal and Vertical Structure of the Lake Turkana Jet

Cited by 47 publications

References 0 publications

Sub-Saharan Northern African climate at the end of the twenty-first century: forcing factors and climate change processes

Sub-Saharan Northern African climate at the end of the twenty-first century: forcing factors and climate change processes

Moisture transport into the Ethiopian highlands

Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

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