Bayesian Rainfall Variability Analysis in West Africa along Cross Sections in Space–Time Grid Boxes
This paper proposes an approach for analyzing rainfall variability over West Africa during the 1950–90 period. Three grid boxes, corresponding to three selected areas over West Africa, have been constructed. For each candidate area the set of annual grid maps are stored in 3D matrices, reflecting ti...
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description | This paper proposes an approach for analyzing rainfall variability over West Africa during the 1950–90 period. Three grid boxes, corresponding to three selected areas over West Africa, have been constructed. For each candidate area the set of annual grid maps are stored in 3D matrices, reflecting time and geographical position, called here space–time grid boxes. Each space–time grid box contains grid points corresponding to a given gauging year. The Bayesian procedure, based on a single-shifting model, is applied to grid points extracted from mean meridional and latitudinal cross sections of each space–time grid box. Two different problems are considered: the first is the detection of a change, while the second is the estimation of the changepoint and its amplitude under the assumption that a change has occurred. The Bayesian single-shift model is applied on grid points extracted from each cross section. A latitude–latitude and longitude–longitude analysis of the rainfall climatology changes is, thus, carried out. It is pointed out that the most significant rainfall climatological changes in the Sahel most probably occurred between 1965 and 1970 with the decrease of the mean level of annual rainfall. This deficit is very high over the coastal region of Senegal (25%) and over the central region of the Sahel (15%–20%). Under approximately 9°–10°N, over the humid West Africa region, a zone without any significant change extending from 6° to 10°N was highlighted. A similar zone with nonsignificant rainfall change was identified along the cross section at 1.5°E, which follow the border of Togo and Benin. However, over the zones in edge of the coast of Ivory Coast, a deficit about 17% is observed. |
doi_str_mv | 10.1175/1520-0442(2004)017<1069:BRVAIW>2.0.CO;2 |
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Three grid boxes, corresponding to three selected areas over West Africa, have been constructed. For each candidate area the set of annual grid maps are stored in 3D matrices, reflecting time and geographical position, called here space–time grid boxes. Each space–time grid box contains grid points corresponding to a given gauging year. The Bayesian procedure, based on a single-shifting model, is applied to grid points extracted from mean meridional and latitudinal cross sections of each space–time grid box. Two different problems are considered: the first is the detection of a change, while the second is the estimation of the changepoint and its amplitude under the assumption that a change has occurred. The Bayesian single-shift model is applied on grid points extracted from each cross section. A latitude–latitude and longitude–longitude analysis of the rainfall climatology changes is, thus, carried out. It is pointed out that the most significant rainfall climatological changes in the Sahel most probably occurred between 1965 and 1970 with the decrease of the mean level of annual rainfall. This deficit is very high over the coastal region of Senegal (25%) and over the central region of the Sahel (15%–20%). Under approximately 9°–10°N, over the humid West Africa region, a zone without any significant change extending from 6° to 10°N was highlighted. A similar zone with nonsignificant rainfall change was identified along the cross section at 1.5°E, which follow the border of Togo and Benin. However, over the zones in edge of the coast of Ivory Coast, a deficit about 17% is observed.</description><identifier>ISSN: 0894-8755</identifier><identifier>EISSN: 1520-0442</identifier><identifier>DOI: 10.1175/1520-0442(2004)017<1069:BRVAIW>2.0.CO;2</identifier><language>eng</language><publisher>Boston, MA: American Meteorological Society</publisher><subject>Bayesian analysis ; Climate change ; Climatology ; Climatology. Bioclimatology. 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Three grid boxes, corresponding to three selected areas over West Africa, have been constructed. For each candidate area the set of annual grid maps are stored in 3D matrices, reflecting time and geographical position, called here space–time grid boxes. Each space–time grid box contains grid points corresponding to a given gauging year. The Bayesian procedure, based on a single-shifting model, is applied to grid points extracted from mean meridional and latitudinal cross sections of each space–time grid box. Two different problems are considered: the first is the detection of a change, while the second is the estimation of the changepoint and its amplitude under the assumption that a change has occurred. The Bayesian single-shift model is applied on grid points extracted from each cross section. A latitude–latitude and longitude–longitude analysis of the rainfall climatology changes is, thus, carried out. It is pointed out that the most significant rainfall climatological changes in the Sahel most probably occurred between 1965 and 1970 with the decrease of the mean level of annual rainfall. This deficit is very high over the coastal region of Senegal (25%) and over the central region of the Sahel (15%–20%). Under approximately 9°–10°N, over the humid West Africa region, a zone without any significant change extending from 6° to 10°N was highlighted. A similar zone with nonsignificant rainfall change was identified along the cross section at 1.5°E, which follow the border of Togo and Benin. However, over the zones in edge of the coast of Ivory Coast, a deficit about 17% is observed.</description><subject>Bayesian analysis</subject><subject>Climate change</subject><subject>Climatology</subject><subject>Climatology. Bioclimatology. Climate change</subject><subject>Coastal zone</subject><subject>Earth, ocean, space</subject><subject>Exact sciences and technology</subject><subject>External geophysics</subject><subject>Latitude</subject><subject>Longitude</subject><subject>Meteorology</subject><subject>Rain</subject><subject>Rainfall</subject><subject>Rainfall measurement</subject><issn>0894-8755</issn><issn>1520-0442</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNpFkN1KHEEQRpsQIRvNIwQaQYgXs1b39M-MCYHdQVdBWFCjl01Nb7f0Ms6s3SO4d3mHvGGeJDOumKuCqsNXVYeQEwZTxrQ8YZJDBkLwbxxAHAPTPxio8nR-fTe7vP_JpzCtlt_5BzJ5Jz-SCRSlyAot5SfyOaU1AOMKYELcHLcuBWzpNYbWY9PQO4wB69CEfktnLTbbFBINLb13qaczH4NFik3XPtAqdinRG2f70LWvzM0Grfv7-89teHR0EcOKzrsXlw7I3hCd3Je3uk9-nZ_dVhfZ1XJxWc2uMpsr1mei0Oik83UuV6LwHK0HqTXPC62tLkuPXlmppVjVWGjLFQ6NGmvpPTKXr_J9crjL3cTu6Xm416y75zj8kAznvAShuBigxQ6y4_nRebOJ4RHj1jAwo2IzijOjODMqNoNiMyo2O8WGGzDV0vAh6ehtHSaLjY_Y2pD-x0kpCyVh4L7uuHXqu_g-54pLpkqd_wOuK4qV</recordid><startdate>20040301</startdate><enddate>20040301</enddate><creator>Tapsoba, Dominique</creator><creator>Haché, Mario</creator><creator>Perreault, Luc</creator><creator>Bobée, Bernard</creator><general>American Meteorological Society</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QH</scope><scope>7TG</scope><scope>7UA</scope><scope>7X2</scope><scope>7XB</scope><scope>88F</scope><scope>88I</scope><scope>8AF</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>M0K</scope><scope>M1Q</scope><scope>M2O</scope><scope>M2P</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>S0X</scope></search><sort><creationdate>20040301</creationdate><title>Bayesian Rainfall Variability Analysis in West Africa along Cross Sections in Space–Time Grid Boxes</title><author>Tapsoba, Dominique ; Haché, Mario ; Perreault, Luc ; Bobée, Bernard</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c361t-487ae5efb35d48f2acf057723877c799faf6c5754dba87c26aaf6bab5ffa1e3d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Bayesian analysis</topic><topic>Climate change</topic><topic>Climatology</topic><topic>Climatology. Bioclimatology. Climate change</topic><topic>Coastal zone</topic><topic>Earth, ocean, space</topic><topic>Exact sciences and technology</topic><topic>External geophysics</topic><topic>Latitude</topic><topic>Longitude</topic><topic>Meteorology</topic><topic>Rain</topic><topic>Rainfall</topic><topic>Rainfall measurement</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tapsoba, Dominique</creatorcontrib><creatorcontrib>Haché, Mario</creatorcontrib><creatorcontrib>Perreault, Luc</creatorcontrib><creatorcontrib>Bobée, Bernard</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aqualine</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Military Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>eLibrary</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Agricultural Science Database</collection><collection>Military Database</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><jtitle>Journal of climate</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tapsoba, Dominique</au><au>Haché, Mario</au><au>Perreault, Luc</au><au>Bobée, Bernard</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bayesian Rainfall Variability Analysis in West Africa along Cross Sections in Space–Time Grid Boxes</atitle><jtitle>Journal of climate</jtitle><date>2004-03-01</date><risdate>2004</risdate><volume>17</volume><issue>5</issue><spage>1069</spage><epage>1082</epage><pages>1069-1082</pages><issn>0894-8755</issn><eissn>1520-0442</eissn><abstract>This paper proposes an approach for analyzing rainfall variability over West Africa during the 1950–90 period. Three grid boxes, corresponding to three selected areas over West Africa, have been constructed. For each candidate area the set of annual grid maps are stored in 3D matrices, reflecting time and geographical position, called here space–time grid boxes. Each space–time grid box contains grid points corresponding to a given gauging year. The Bayesian procedure, based on a single-shifting model, is applied to grid points extracted from mean meridional and latitudinal cross sections of each space–time grid box. Two different problems are considered: the first is the detection of a change, while the second is the estimation of the changepoint and its amplitude under the assumption that a change has occurred. The Bayesian single-shift model is applied on grid points extracted from each cross section. A latitude–latitude and longitude–longitude analysis of the rainfall climatology changes is, thus, carried out. It is pointed out that the most significant rainfall climatological changes in the Sahel most probably occurred between 1965 and 1970 with the decrease of the mean level of annual rainfall. This deficit is very high over the coastal region of Senegal (25%) and over the central region of the Sahel (15%–20%). Under approximately 9°–10°N, over the humid West Africa region, a zone without any significant change extending from 6° to 10°N was highlighted. A similar zone with nonsignificant rainfall change was identified along the cross section at 1.5°E, which follow the border of Togo and Benin. However, over the zones in edge of the coast of Ivory Coast, a deficit about 17% is observed.</abstract><cop>Boston, MA</cop><pub>American Meteorological Society</pub><doi>10.1175/1520-0442(2004)017<1069:BRVAIW>2.0.CO;2</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Bayesian analysis Climate change Climatology Climatology. Bioclimatology. Climate change Coastal zone Earth, ocean, space Exact sciences and technology External geophysics Latitude Longitude Meteorology Rain Rainfall Rainfall measurement |
title | Bayesian Rainfall Variability Analysis in West Africa along Cross Sections in Space–Time Grid Boxes |
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