2009
DOI: 10.1007/s00704-009-0114-0
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Changing dependence of Zimbabwean rainfall variability on ENSO and the Indian Ocean dipole/zonal mode

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Cited by 15 publications
(15 citation statements)
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References 30 publications
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“…However, the presence of these significant and oppositely signed but similar correlation coefficients patterns for NESOR and SESOR in the Indo‐Pacific basin seem to stress that these rainfall anomalies are not only inversely related but strongly connected to the air sea coupling. Similar correlation structures to Figure 5(a) and (b) were obtained by Behera et al (2005) and Manatsa et al (2008) and Manatsa and Matarira (2009), when they studied the connection of the ‘short rains’ and Zimbabwe summer rainfall, respectively with the SSTs in the Indo‐Pacific basin. In both cases, relatively high correlation values are found in the tropical IO, with the highest values in the western part of the basin.…”
Section: Resultssupporting
confidence: 88%
See 1 more Smart Citation
“…However, the presence of these significant and oppositely signed but similar correlation coefficients patterns for NESOR and SESOR in the Indo‐Pacific basin seem to stress that these rainfall anomalies are not only inversely related but strongly connected to the air sea coupling. Similar correlation structures to Figure 5(a) and (b) were obtained by Behera et al (2005) and Manatsa et al (2008) and Manatsa and Matarira (2009), when they studied the connection of the ‘short rains’ and Zimbabwe summer rainfall, respectively with the SSTs in the Indo‐Pacific basin. In both cases, relatively high correlation values are found in the tropical IO, with the highest values in the western part of the basin.…”
Section: Resultssupporting
confidence: 88%
“…The threshold for El Niño (positive (p) IODZM) and La Niña (negative (n) IODZM) event is positive and negative 0.7σ, respectively. This threshold value, although not standard, has been deliberately chosen as it is the level that has been shown to trigger anomalous rainfall events over southern Africa (Manatsa et al , 2008; Manatsa and Matarira, 2009). At the same time, these event phases match closely those that are widely used as proposed by Yamagata et al (2004).…”
Section: Datamentioning
confidence: 99%
“…Faurismith station in the southern parts has the highest CV ranging from 50% to 69%. Other studies by Manatsa and Matarira (2009) in southern Africa (Zimbabwe) also showed high seasonal variability with an average of around 26%, which is lower than the figures obtained in this study. High variability of seasonal rainfall resulting to drought conditions affects mostly the resource-poor farmers in the rural areas, and thus local municipalities have to partner with researcher institutions, nongovernmental organizations, and private companies to implement measures to help the most vulnerable communities during seasons of low harvests (Moeletsi 2010).…”
Section: Wrsi For 120-day Maize Planted In Januarycontrasting
confidence: 85%
“…One explanation is the potential influence of other atmospheric circulation processes (e.g. low pressure systems and SSTs) (Nicholson and Selato, 2000;Usman and Reason, 2004;Hansingo and Reason, 2009;Manatsa and Matarira, 2009;Hoell et al, 2014). Specific to anomalous dry and wet spells, both annual and seasonally specific, there are various patterns that are highlighted across different parts of southern Africa.…”
Section: Introductionmentioning
confidence: 99%
“…Specific to anomalous dry and wet spells, both annual and seasonally specific, there are various patterns that are highlighted across different parts of southern Africa. For example, in Zimbabwe, Manatsa and Matarira (2009) highlight the influence of the IOD+ on unusually dry periods, and conclude that ENSO might have less to do with the country's rainfall variability. However, just north during the height of the Zambian rainy season (December-January-February), Hachigonta and Reason (2006), identify the strength of importance of ENSO phases on variable dry and wet spell frequencies with less influence shown in relation to associations to Indian Ocean SST anomalies.…”
Section: Introductionmentioning
confidence: 99%