2021
DOI: 10.3390/atmos12060742
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Multi-Decadal Variability and Future Changes in Precipitation over Southern Africa

Abstract: The future planning and management of water resources ought to be based on climate change projections at relevant temporal and spatial scales. This work uses the new regional demarcation for Southern Africa (SA) to investigate the spatio-temporal precipitation variability and trends of centennial-scale observation and modeled data, based on datasets from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The study employs several statistical methods to rank the models according to their prec… Show more

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Cited by 39 publications
(22 citation statements)
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References 79 publications
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“…The findings for the seasonal cycle for the historical period were unimodal and close to the cycle south of the equator. This result is consistent with the CMIP6 P seasonality found in Southern Africa by [73]. However, the future climate presented an opposite seasonal cycle for all the SSP-RCPs (Figure 3).…”
Section: Discussionsupporting
confidence: 89%
See 1 more Smart Citation
“…The findings for the seasonal cycle for the historical period were unimodal and close to the cycle south of the equator. This result is consistent with the CMIP6 P seasonality found in Southern Africa by [73]. However, the future climate presented an opposite seasonal cycle for all the SSP-RCPs (Figure 3).…”
Section: Discussionsupporting
confidence: 89%
“…The humid-tropical zones (along with the Guinean coast) and the interior of the Cameroonian, Kenyan, and Ethiopian Highlands provided a comparatively similar mean ET. The ET pattern recorded is consistent with CMIP6 P patterns found in East Africa [77], North Africa [78] and Southern Africa [73].…”
Section: Discussionsupporting
confidence: 85%
“…The two main projections utilized are drawn from Tier 1 ScenarioMIP: SSP2-4.5 and SSP5-8.5. Following the recommendations of previous studies (e.g., [57,[81][82][83][84][85]), this employs MME of CMIP6 for projection of extreme events over the study area. Many studies have remarked on the robustness of MME as compared to individual models due to cancellation of intermodel biases [59].…”
Section: Discussionmentioning
confidence: 99%
“…Simultaneously, the OND season shows likely intensification of PRCPTOT, R95 p, and CWD over Uganda and most parts of Kenya, while reduction is observed over the Tanzania region (Figures 5 and 6). Presence of complex topography has considerable influence on the variation of extreme events and impacted regions [66,83]. For instance, the presence of large inland water bodies-i.e., Lake Victoria, which is the largest freshwater lake in Africa and second in the world, covering about 68,000 km 2 and bordering three countries, Uganda (45%), Tanzania (49%), and Kenya (6%)-have a significant influence on the incidences of extreme events [84].…”
Section: Discussionmentioning
confidence: 99%
“…More recently, CMIP6 simulations have been investigated in terms of mean precipitation change at continental scale (Almazroui et al 2020) and for southern Africa (Sian 2021), and by extreme events over East Africa (Ayugi et al 2021a). In addition, Moon and Ha (2020) and Ukkola et al (2020) investigated future characteristics of (global) monsoon precipitation and meteorological droughts, respectively.…”
Section: Introductionmentioning
confidence: 99%