M. Agbazo, J. Adéchinan, G. K. N'Gobi, Joseph Bessou
{"title":"西非贝宁共和国天气站观测的干旱期长度分析及可预测性","authors":"M. Agbazo, J. Adéchinan, G. K. N'Gobi, Joseph Bessou","doi":"10.4236/ajcc.2021.104030","DOIUrl":null,"url":null,"abstract":"The complex behavior and predictability of the Dry Spell Lengths (DSL) series obtained in Benin synoptic stations, from 1951 to 2010 are analyzed in this paper using a fractal approach. The synoptic stations are located in Cotonou, Bohicon, Save (subequatorial climate), and Parakou, Natitingou, Kandi (Sudanian climate). The DSLs are computed by considering four thresholds level, R0 = {1.0, 1.5, 2.0 and 5.0} mm/day. The fractal trace is estimated for dry spell density by the mean of the “Dry Spell Spell” (DSS) n-index. The rescaled range method is used to determine the predictability of DSL. By ana-lyzing the DSS, results show that low DSS n-index values (n-index < 0.4) are more favored in the northern part of Benin than in the southern region,","PeriodicalId":69702,"journal":{"name":"美国气候变化期刊(英文)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Analysis and Predictability of Dry Spell Lengths Observed in Synoptic Stations of Benin Republic (West Africa)\",\"authors\":\"M. Agbazo, J. Adéchinan, G. K. N'Gobi, Joseph Bessou\",\"doi\":\"10.4236/ajcc.2021.104030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The complex behavior and predictability of the Dry Spell Lengths (DSL) series obtained in Benin synoptic stations, from 1951 to 2010 are analyzed in this paper using a fractal approach. The synoptic stations are located in Cotonou, Bohicon, Save (subequatorial climate), and Parakou, Natitingou, Kandi (Sudanian climate). The DSLs are computed by considering four thresholds level, R0 = {1.0, 1.5, 2.0 and 5.0} mm/day. The fractal trace is estimated for dry spell density by the mean of the “Dry Spell Spell” (DSS) n-index. The rescaled range method is used to determine the predictability of DSL. By ana-lyzing the DSS, results show that low DSS n-index values (n-index < 0.4) are more favored in the northern part of Benin than in the southern region,\",\"PeriodicalId\":69702,\"journal\":{\"name\":\"美国气候变化期刊(英文)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"美国气候变化期刊(英文)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4236/ajcc.2021.104030\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"美国气候变化期刊(英文)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4236/ajcc.2021.104030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis and Predictability of Dry Spell Lengths Observed in Synoptic Stations of Benin Republic (West Africa)
The complex behavior and predictability of the Dry Spell Lengths (DSL) series obtained in Benin synoptic stations, from 1951 to 2010 are analyzed in this paper using a fractal approach. The synoptic stations are located in Cotonou, Bohicon, Save (subequatorial climate), and Parakou, Natitingou, Kandi (Sudanian climate). The DSLs are computed by considering four thresholds level, R0 = {1.0, 1.5, 2.0 and 5.0} mm/day. The fractal trace is estimated for dry spell density by the mean of the “Dry Spell Spell” (DSS) n-index. The rescaled range method is used to determine the predictability of DSL. By ana-lyzing the DSS, results show that low DSS n-index values (n-index < 0.4) are more favored in the northern part of Benin than in the southern region,