Standardized precipitation index based on pearson type III distribution
Autor(a) principal: | |
---|---|
Data de Publicação: | 2011 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Brasileira de Meteorologia (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862011000200001 |
Resumo: | The initial step in calculating the Standardized Precipitation Index (SPI) is to determine a probability density function (pdf) that describes the precipitation series under analysis. Once this pdf is determined, the cumulative probability of an observed precipitation amount is computed. The inverse normal function is then applied to the cumulative probability. The result is the SPI. This article assessed the changes in SPI final values, when computed based on Gamma 2-parameters (Gam) and Pearson Type III (PE3) distributions (SPIGam and SPIPE3, respectively). Monthly rainfall series, available from five weather stations of the State of São Paulo, were chosen for this study. Considering quantitative and qualitative assessments of goodness-of-fit (evaluated at 1-, 3-, and 6-months precipitation totals), the PE3 distribution seems to be a better choice than the Gam distribution, in describing the long-term rainfall series of the State of São Paulo. In addition, it was observed that the number of SPI time series that could be seen as normally distributed was higher when this drought index was computed from the PE3 distribution. Thus, the use of the Pearson type III distribution within the calculation algorithm of the SPI is recommended in the State of São Paulo. |
id |
SBMET-1_2bcec36c173868d24356ec76bf3ba694 |
---|---|
oai_identifier_str |
oai:scielo:S0102-77862011000200001 |
network_acronym_str |
SBMET-1 |
network_name_str |
Revista Brasileira de Meteorologia (Online) |
repository_id_str |
|
spelling |
Standardized precipitation index based on pearson type III distributiondroughtGamma distributionSPIThe initial step in calculating the Standardized Precipitation Index (SPI) is to determine a probability density function (pdf) that describes the precipitation series under analysis. Once this pdf is determined, the cumulative probability of an observed precipitation amount is computed. The inverse normal function is then applied to the cumulative probability. The result is the SPI. This article assessed the changes in SPI final values, when computed based on Gamma 2-parameters (Gam) and Pearson Type III (PE3) distributions (SPIGam and SPIPE3, respectively). Monthly rainfall series, available from five weather stations of the State of São Paulo, were chosen for this study. Considering quantitative and qualitative assessments of goodness-of-fit (evaluated at 1-, 3-, and 6-months precipitation totals), the PE3 distribution seems to be a better choice than the Gam distribution, in describing the long-term rainfall series of the State of São Paulo. In addition, it was observed that the number of SPI time series that could be seen as normally distributed was higher when this drought index was computed from the PE3 distribution. Thus, the use of the Pearson type III distribution within the calculation algorithm of the SPI is recommended in the State of São Paulo.Sociedade Brasileira de Meteorologia2011-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862011000200001Revista Brasileira de Meteorologia v.26 n.2 2011reponame:Revista Brasileira de Meteorologia (Online)instname:Sociedade Brasileira de Meteorologia (SBMET)instacron:SBMET10.1590/S0102-77862011000200001info:eu-repo/semantics/openAccessBlain,Gabriel Constantinoeng2011-08-04T00:00:00Zoai:scielo:S0102-77862011000200001Revistahttp://www.rbmet.org.br/port/index.phpONGhttps://old.scielo.br/oai/scielo-oai.php||rbmet@rbmet.org.br1982-43510102-7786opendoar:2011-08-04T00:00Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET)false |
dc.title.none.fl_str_mv |
Standardized precipitation index based on pearson type III distribution |
title |
Standardized precipitation index based on pearson type III distribution |
spellingShingle |
Standardized precipitation index based on pearson type III distribution Blain,Gabriel Constantino drought Gamma distribution SPI |
title_short |
Standardized precipitation index based on pearson type III distribution |
title_full |
Standardized precipitation index based on pearson type III distribution |
title_fullStr |
Standardized precipitation index based on pearson type III distribution |
title_full_unstemmed |
Standardized precipitation index based on pearson type III distribution |
title_sort |
Standardized precipitation index based on pearson type III distribution |
author |
Blain,Gabriel Constantino |
author_facet |
Blain,Gabriel Constantino |
author_role |
author |
dc.contributor.author.fl_str_mv |
Blain,Gabriel Constantino |
dc.subject.por.fl_str_mv |
drought Gamma distribution SPI |
topic |
drought Gamma distribution SPI |
description |
The initial step in calculating the Standardized Precipitation Index (SPI) is to determine a probability density function (pdf) that describes the precipitation series under analysis. Once this pdf is determined, the cumulative probability of an observed precipitation amount is computed. The inverse normal function is then applied to the cumulative probability. The result is the SPI. This article assessed the changes in SPI final values, when computed based on Gamma 2-parameters (Gam) and Pearson Type III (PE3) distributions (SPIGam and SPIPE3, respectively). Monthly rainfall series, available from five weather stations of the State of São Paulo, were chosen for this study. Considering quantitative and qualitative assessments of goodness-of-fit (evaluated at 1-, 3-, and 6-months precipitation totals), the PE3 distribution seems to be a better choice than the Gam distribution, in describing the long-term rainfall series of the State of São Paulo. In addition, it was observed that the number of SPI time series that could be seen as normally distributed was higher when this drought index was computed from the PE3 distribution. Thus, the use of the Pearson type III distribution within the calculation algorithm of the SPI is recommended in the State of São Paulo. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862011000200001 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862011000200001 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0102-77862011000200001 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Meteorologia |
publisher.none.fl_str_mv |
Sociedade Brasileira de Meteorologia |
dc.source.none.fl_str_mv |
Revista Brasileira de Meteorologia v.26 n.2 2011 reponame:Revista Brasileira de Meteorologia (Online) instname:Sociedade Brasileira de Meteorologia (SBMET) instacron:SBMET |
instname_str |
Sociedade Brasileira de Meteorologia (SBMET) |
instacron_str |
SBMET |
institution |
SBMET |
reponame_str |
Revista Brasileira de Meteorologia (Online) |
collection |
Revista Brasileira de Meteorologia (Online) |
repository.name.fl_str_mv |
Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET) |
repository.mail.fl_str_mv |
||rbmet@rbmet.org.br |
_version_ |
1752122084025171968 |