<b>Extreme value theory applied to the standardized precipitation index</b> - doi: 10.4025/actascitechnol.v36i1.17475
The Standardized Precipitation Index (SPI) is a mathematical algorithm developed for detecting and characterizing precipitation departures with regard to an expected regional climate condition. Thus, this study aimed to verify the possibility of using the time-independent general extreme value distr...
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| Format: | Article |
| Language: | English |
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Universidade Estadual de Maringá
2014-01-01
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| Series: | Acta Scientiarum: Technology |
| Subjects: | |
| Online Access: | http://186.233.154.254/ojs/index.php/ActaSciTechnol/article/view/17475 |
| _version_ | 1811284892127854592 |
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| author | Gabriel Constantino Blain |
| author_facet | Gabriel Constantino Blain |
| author_sort | Gabriel Constantino Blain |
| collection | DOAJ |
| description | The Standardized Precipitation Index (SPI) is a mathematical algorithm developed for detecting and characterizing precipitation departures with regard to an expected regional climate condition. Thus, this study aimed to verify the possibility of using the time-independent general extreme value distribution (GEV) for modeling the probability of occurrence of both SPI annual maxima (the maximum monthly SPI value; SPImax) and SPI annual minima (the minimum monthly SPI value; SPImim) obtained from the weather station of Campinas, State of São Paulo, Brazil (1891-2011) and to evaluate the presence of trends, temporal persistence and periodical components in these two datasets. The goodness-of-fit tests used in this study quantify the agreement between the empirical cumulative distribution and the GEV cumulative function. Our results have indicated that such parametric function can be used to assess the probability of occurrence of SPImin and SPImax values. No significant serial correlation and no trend were detected in both series. For the SPImim, the wavelet analysis has detected a dominant mode in the 4-8 year band. Future studies should focus on the development of a GEV model capable of accounting for such feature. No dominant mode was found for the annual monthly SPI maximums. |
| first_indexed | 2024-04-13T02:36:23Z |
| format | Article |
| id | doaj.art-0cab08718f504053bb7c936cda1ed4a6 |
| institution | Directory Open Access Journal |
| issn | 1806-2563 1807-8664 |
| language | English |
| last_indexed | 2024-04-13T02:36:23Z |
| publishDate | 2014-01-01 |
| publisher | Universidade Estadual de Maringá |
| record_format | Article |
| series | Acta Scientiarum: Technology |
| spelling | doaj.art-0cab08718f504053bb7c936cda1ed4a62022-12-22T03:06:22ZengUniversidade Estadual de MaringáActa Scientiarum: Technology1806-25631807-86642014-01-0136114715510.4025/actascitechnol.v36i1.1747510186<b>Extreme value theory applied to the standardized precipitation index</b> - doi: 10.4025/actascitechnol.v36i1.17475Gabriel Constantino Blain0Instituto Agronômico de CampinasThe Standardized Precipitation Index (SPI) is a mathematical algorithm developed for detecting and characterizing precipitation departures with regard to an expected regional climate condition. Thus, this study aimed to verify the possibility of using the time-independent general extreme value distribution (GEV) for modeling the probability of occurrence of both SPI annual maxima (the maximum monthly SPI value; SPImax) and SPI annual minima (the minimum monthly SPI value; SPImim) obtained from the weather station of Campinas, State of São Paulo, Brazil (1891-2011) and to evaluate the presence of trends, temporal persistence and periodical components in these two datasets. The goodness-of-fit tests used in this study quantify the agreement between the empirical cumulative distribution and the GEV cumulative function. Our results have indicated that such parametric function can be used to assess the probability of occurrence of SPImin and SPImax values. No significant serial correlation and no trend were detected in both series. For the SPImim, the wavelet analysis has detected a dominant mode in the 4-8 year band. Future studies should focus on the development of a GEV model capable of accounting for such feature. No dominant mode was found for the annual monthly SPI maximums.http://186.233.154.254/ojs/index.php/ActaSciTechnol/article/view/17475wavelet analysisMann-Kendall testSPI |
| spellingShingle | Gabriel Constantino Blain <b>Extreme value theory applied to the standardized precipitation index</b> - doi: 10.4025/actascitechnol.v36i1.17475 Acta Scientiarum: Technology wavelet analysis Mann-Kendall test SPI |
| title | <b>Extreme value theory applied to the standardized precipitation index</b> - doi: 10.4025/actascitechnol.v36i1.17475 |
| title_full | <b>Extreme value theory applied to the standardized precipitation index</b> - doi: 10.4025/actascitechnol.v36i1.17475 |
| title_fullStr | <b>Extreme value theory applied to the standardized precipitation index</b> - doi: 10.4025/actascitechnol.v36i1.17475 |
| title_full_unstemmed | <b>Extreme value theory applied to the standardized precipitation index</b> - doi: 10.4025/actascitechnol.v36i1.17475 |
| title_short | <b>Extreme value theory applied to the standardized precipitation index</b> - doi: 10.4025/actascitechnol.v36i1.17475 |
| title_sort | b extreme value theory applied to the standardized precipitation index b doi 10 4025 actascitechnol v36i1 17475 |
| topic | wavelet analysis Mann-Kendall test SPI |
| url | http://186.233.154.254/ojs/index.php/ActaSciTechnol/article/view/17475 |
| work_keys_str_mv | AT gabrielconstantinoblain bextremevaluetheoryappliedtothestandardizedprecipitationindexbdoi104025actascitechnolv36i117475 |