Seasonal forecasts in the Sahel region: the use of rainfall-based predictive variables
In the Sahel region, seasonal predictions are crucial to alleviate the impacts of climate variability on populations' livelihoods. Agricultural planning (e.g., decisions about sowing date, fertilizer application date, and choice of crop or cultivar) is based on empirical predictive indices whos...
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| Veröffentlicht in: | Theoretical and applied climatology 2014-08, Vol.117 (3-4), p.485-494 |
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| creator | Lodoun, Tiganadaba Sanon, Moussa Giannini, Alessandra Traoré, Pierre Sibiry Somé, Léopold Rasolodimby, Jeanne Millogo |
| description | In the Sahel region, seasonal predictions are crucial to alleviate the impacts of climate variability on populations' livelihoods. Agricultural planning (e.g., decisions about sowing date, fertilizer application date, and choice of crop or cultivar) is based on empirical predictive indices whose accuracy to date has not been scientifically proven. This paper attempts to statistically test whether the pattern of rainfall distribution over the May–July period contributes to predicting the real onset date and the nature (wet or dry) of the rainy season, as farmers believe. To that end, we considered historical records of daily rainfall from 51 stations spanning the period 1920–2008 and the different agro-climatic zones in Burkina Faso. We performed (1) principal component analysis to identify climatic zones, based on the patterns of intra-seasonal rainfall, (2) and linear discriminant analysis to find the best rainfall-based variables to distinguish between real and false onset dates of the rainy season, and between wet and dry seasons in each climatic zone. A total of nine climatic zones were identified in each of which, based on rainfall records from May to July, we derived linear discriminant functions to correctly predict the nature of a potential onset date of the rainy season (real or false) and that of the rainy season (dry or wet) in at least three cases out of five. These functions should contribute to alleviating the negative impacts of climate variability in the different climatic zones of Burkina Faso. |
| doi_str_mv | 10.1007/s00704-013-1002-1 |
| format | Article |
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Agricultural planning (e.g., decisions about sowing date, fertilizer application date, and choice of crop or cultivar) is based on empirical predictive indices whose accuracy to date has not been scientifically proven. This paper attempts to statistically test whether the pattern of rainfall distribution over the May–July period contributes to predicting the real onset date and the nature (wet or dry) of the rainy season, as farmers believe. To that end, we considered historical records of daily rainfall from 51 stations spanning the period 1920–2008 and the different agro-climatic zones in Burkina Faso. We performed (1) principal component analysis to identify climatic zones, based on the patterns of intra-seasonal rainfall, (2) and linear discriminant analysis to find the best rainfall-based variables to distinguish between real and false onset dates of the rainy season, and between wet and dry seasons in each climatic zone. A total of nine climatic zones were identified in each of which, based on rainfall records from May to July, we derived linear discriminant functions to correctly predict the nature of a potential onset date of the rainy season (real or false) and that of the rainy season (dry or wet) in at least three cases out of five. These functions should contribute to alleviating the negative impacts of climate variability in the different climatic zones of Burkina Faso.</description><identifier>ISSN: 0177-798X</identifier><identifier>EISSN: 1434-4483</identifier><identifier>DOI: 10.1007/s00704-013-1002-1</identifier><language>eng</language><publisher>Vienna: Springer-Verlag</publisher><subject>Agricultural and forest climatology and meteorology. Irrigation. Drainage ; Agronomy. 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Drainage ; livelihood ; Meteorology ; Original Paper ; planning ; prediction ; principal component analysis ; Principal components analysis ; rain ; Rain and rainfall ; Rainfall distribution ; Rainfall measurement ; Rainy season ; Sahel ; Seasons ; sowing date ; Waste Water Technology ; Water Management ; Water Pollution Control ; Weather forecasting ; wet season</subject><ispartof>Theoretical and applied climatology, 2014-08, Vol.117 (3-4), p.485-494</ispartof><rights>Springer-Verlag Wien 2013</rights><rights>2015 INIST-CNRS</rights><rights>COPYRIGHT 2014 Springer</rights><rights>Springer-Verlag Wien 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c476t-6c4d7a5060db609233c0ef588112b8a876252406b55c6989df809cf1d966d13a3</citedby><cites>FETCH-LOGICAL-c476t-6c4d7a5060db609233c0ef588112b8a876252406b55c6989df809cf1d966d13a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00704-013-1002-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00704-013-1002-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28665151$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Lodoun, Tiganadaba</creatorcontrib><creatorcontrib>Sanon, Moussa</creatorcontrib><creatorcontrib>Giannini, Alessandra</creatorcontrib><creatorcontrib>Traoré, Pierre Sibiry</creatorcontrib><creatorcontrib>Somé, Léopold</creatorcontrib><creatorcontrib>Rasolodimby, Jeanne Millogo</creatorcontrib><title>Seasonal forecasts in the Sahel region: the use of rainfall-based predictive variables</title><title>Theoretical and applied climatology</title><addtitle>Theor Appl Climatol</addtitle><description>In the Sahel region, seasonal predictions are crucial to alleviate the impacts of climate variability on populations' livelihoods. Agricultural planning (e.g., decisions about sowing date, fertilizer application date, and choice of crop or cultivar) is based on empirical predictive indices whose accuracy to date has not been scientifically proven. This paper attempts to statistically test whether the pattern of rainfall distribution over the May–July period contributes to predicting the real onset date and the nature (wet or dry) of the rainy season, as farmers believe. To that end, we considered historical records of daily rainfall from 51 stations spanning the period 1920–2008 and the different agro-climatic zones in Burkina Faso. We performed (1) principal component analysis to identify climatic zones, based on the patterns of intra-seasonal rainfall, (2) and linear discriminant analysis to find the best rainfall-based variables to distinguish between real and false onset dates of the rainy season, and between wet and dry seasons in each climatic zone. A total of nine climatic zones were identified in each of which, based on rainfall records from May to July, we derived linear discriminant functions to correctly predict the nature of a potential onset date of the rainy season (real or false) and that of the rainy season (dry or wet) in at least three cases out of five. These functions should contribute to alleviating the negative impacts of climate variability in the different climatic zones of Burkina Faso.</description><subject>Agricultural and forest climatology and meteorology. Irrigation. Drainage</subject><subject>Agronomy. Soil science and plant productions</subject><subject>Analysis</subject><subject>application timing</subject><subject>Aquatic Pollution</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Atmospheric Sciences</subject><subject>Biological and medical sciences</subject><subject>Climate change</subject><subject>Climate variability</subject><subject>Climatic zones</subject><subject>Climatology</subject><subject>Climatology. Bioclimatology. Climate change</subject><subject>Cultivars</subject><subject>discriminant analysis</subject><subject>Dry season</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Earth, ocean, space</subject><subject>Exact sciences and technology</subject><subject>External geophysics</subject><subject>farmers</subject><subject>Fertilizer application</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General agronomy. 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Agricultural planning (e.g., decisions about sowing date, fertilizer application date, and choice of crop or cultivar) is based on empirical predictive indices whose accuracy to date has not been scientifically proven. This paper attempts to statistically test whether the pattern of rainfall distribution over the May–July period contributes to predicting the real onset date and the nature (wet or dry) of the rainy season, as farmers believe. To that end, we considered historical records of daily rainfall from 51 stations spanning the period 1920–2008 and the different agro-climatic zones in Burkina Faso. We performed (1) principal component analysis to identify climatic zones, based on the patterns of intra-seasonal rainfall, (2) and linear discriminant analysis to find the best rainfall-based variables to distinguish between real and false onset dates of the rainy season, and between wet and dry seasons in each climatic zone. 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| identifier | ISSN: 0177-798X |
| ispartof | Theoretical and applied climatology, 2014-08, Vol.117 (3-4), p.485-494 |
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| language | eng |
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| subjects | Agricultural and forest climatology and meteorology. Irrigation. Drainage Agronomy. Soil science and plant productions Analysis application timing Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution Atmospheric Sciences Biological and medical sciences Climate change Climate variability Climatic zones Climatology Climatology. Bioclimatology. Climate change Cultivars discriminant analysis Dry season Earth and Environmental Science Earth Sciences Earth, ocean, space Exact sciences and technology External geophysics farmers Fertilizer application Fundamental and applied biological sciences. Psychology General agronomy. Plant production Irrigation. Drainage livelihood Meteorology Original Paper planning prediction principal component analysis Principal components analysis rain Rain and rainfall Rainfall distribution Rainfall measurement Rainy season Sahel Seasons sowing date Waste Water Technology Water Management Water Pollution Control Weather forecasting wet season |
| title | Seasonal forecasts in the Sahel region: the use of rainfall-based predictive variables |
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