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Rainfall trends in the African Sahel: Characteristics, processes, and causes
Open accessAbstract
Sahel rainfall is dynamically linked to the global Hadley cell and to the regional monsoon circulation. It is therefore susceptible to forcings from remote oceans and regional land alike. Warming of the oceans enhances the stability of the tropical atmosphere and weakens deep ascent in the Hadley circulation. Warming of the Sahara and of the nearby oceans changes the structure and position of the regional shallow circulation and allows more of the intense convective systems that determine seasonal rain accumulation. These processes can explain the observed interannual to multidecadal variability. Sea surface temperature anomalies were the dominant forcing of the drought of the 1970s and 1980s. In most recent decades, seasonal rainfall amounts have partially recovered, but rainy season characteristics have changed: rainfall is more intense and intermittent and wetting is concentrated in the late rainy season and away from the west coast. Similar subseasonal and subregional differences in rainfall trends characterize the simulated response to increased greenhouse gases, suggesting an anthropogenic influence. While uncertainty in future projections remains, confidence in them is encouraged by the recognition that seasonal mean rainfall depends on large‐scale drivers of atmospheric circulations that are well resolved by current climate models. Nevertheless, observational and modeling efforts are needed to provide more refined projections of rainfall changes, expanding beyond total accumulation to metrics of intraseasonal characteristics and risk of extreme events, and coordination between climate scientists and stakeholders is needed to generate relevant information that is useful even under deep uncertainty. This article is categorized under: Paleoclimates and Current Trends > Modern Climate Change
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Agreeing on Robust Decisions: New Processes for Decision Making under Deep Uncertainty
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Variability of moisture recycling using a precipitationshed framework
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Metrics for the Diurnal Cycle of Precipitation: Toward Routine Benchmarks for Climate Models
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Rainfall Types in the West African Sudanian Zone during the Summer Monsoon 2002
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Mechanisms of Climate Change in the Semiarid African Sahel: The Local View
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Evaluating Climate Models with an African Lens
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Assessing recovery and change in West Africa's rainfall regime from a 161‐year record
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The Role of the Sahara Low in Summertime Sahel Rainfall Variability and Change in the CMIP3 Models
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Self-citationAssessing climate adaptation options and uncertainties for cereal systems in West Africa
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Self-citationUsing and Designing GCM–RCM Ensemble Regional Climate Projections
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Crop quality under rising atmospheric CO2
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Remote Vegetation Feedbacks and the Mid-Holocene Green Sahara
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A further assessment of vegetation feedback on decadal Sahel rainfall variability
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Dealing with uncertainty: integrating local and scientific knowledge of the climate and weather
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Recent trends in selected extreme precipitation indices in Senegal – A changepoint approach
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A multi‐scale analysis of the extreme rain event of Ouagadougou in 2009
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Scales for rating heavy rainfall events in the West African Sahel
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Recent assessment of West African summer monsoon daily rainfall trends
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Self-citation
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Metadata
- Authors
- Biasutti, M.
- Venue
- WIREs Climate Change
- Publisher
- Wiley
- Published
- 2019-06-04
- Volume
- 10
- Issue
- 4
- Pages
- e591-e591
- ISSN
- 1757-7780 (ISSN-L)
- 1757-7799
- OpenAlex
- W2948284713
- Cited by
- 336
- References
- 158
- FWCI
- 14.07
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.