Statistical modelling of 5-day average rainfall in Australia during 1950-2013
Many regions across Australia have high rainfall variability, which has various effects on water and food availability. This study examines rainfall patterns over consecutive 5-day periods during 1950-2013 using data from 92 observational stations in Australia. The first model used factor analysis...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Prince of Songkla University
2019-08-01
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| Series: | Songklanakarin Journal of Science and Technology (SJST) |
| Subjects: | |
| Online Access: | https://rdo.psu.ac.th/sjstweb/journal/41-4/21.pdf |
| _version_ | 1819079856060628992 |
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| author | Bright Emmanuel Owusu Nittaya McNeil Mayuening Eso |
| author_facet | Bright Emmanuel Owusu Nittaya McNeil Mayuening Eso |
| author_sort | Bright Emmanuel Owusu |
| collection | DOAJ |
| description | Many regions across Australia have high rainfall variability, which has various effects on water and food availability.
This study examines rainfall patterns over consecutive 5-day periods during 1950-2013 using data from 92 observational stations
in Australia. The first model used factor analysis to classify the stations into distinct geographical regions. Gamma generalised
linear model (GLM) was then fitted to describe the rainfall amount in each category with season and year factors as the
predictors.
Factor analysis revealed eight factors, which represent eight geographical regions of Australia. Analysis of the
similarities in the seasonal evolutions between regions revealed three seasonal rainfall groupings. The GLM models fitted the
data quite well in all the areas and showed that 5-daily rainfall is significantly affected by the period of the year and its annual
average in most of the regions. The models could be used to simulate rainfall data for the areas with inadequate rainfall records. |
| first_indexed | 2024-12-21T19:35:38Z |
| format | Article |
| id | doaj.art-9b4c9bf847c24ad2a0446b0f2fe1c288 |
| institution | Directory Open Access Journal |
| issn | 0125-3395 |
| language | English |
| last_indexed | 2024-12-21T19:35:38Z |
| publishDate | 2019-08-01 |
| publisher | Prince of Songkla University |
| record_format | Article |
| series | Songklanakarin Journal of Science and Technology (SJST) |
| spelling | doaj.art-9b4c9bf847c24ad2a0446b0f2fe1c2882022-12-21T18:52:37ZengPrince of Songkla UniversitySongklanakarin Journal of Science and Technology (SJST)0125-33952019-08-0141487087810.14456/sjst-psu.2019.111Statistical modelling of 5-day average rainfall in Australia during 1950-2013Bright Emmanuel Owusu0Nittaya McNeil1Mayuening Eso2Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Mueang, Pattani, 94000 ThailandDepartment of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Mueang, Pattani, 94000 ThailandDepartment of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Mueang, Pattani, 94000 ThailandMany regions across Australia have high rainfall variability, which has various effects on water and food availability. This study examines rainfall patterns over consecutive 5-day periods during 1950-2013 using data from 92 observational stations in Australia. The first model used factor analysis to classify the stations into distinct geographical regions. Gamma generalised linear model (GLM) was then fitted to describe the rainfall amount in each category with season and year factors as the predictors. Factor analysis revealed eight factors, which represent eight geographical regions of Australia. Analysis of the similarities in the seasonal evolutions between regions revealed three seasonal rainfall groupings. The GLM models fitted the data quite well in all the areas and showed that 5-daily rainfall is significantly affected by the period of the year and its annual average in most of the regions. The models could be used to simulate rainfall data for the areas with inadequate rainfall records.https://rdo.psu.ac.th/sjstweb/journal/41-4/21.pdfrainfall variabilityclassificationgeneralised linear modelsfactor analysis |
| spellingShingle | Bright Emmanuel Owusu Nittaya McNeil Mayuening Eso Statistical modelling of 5-day average rainfall in Australia during 1950-2013 Songklanakarin Journal of Science and Technology (SJST) rainfall variability classification generalised linear models factor analysis |
| title | Statistical modelling of 5-day average rainfall in Australia during 1950-2013 |
| title_full | Statistical modelling of 5-day average rainfall in Australia during 1950-2013 |
| title_fullStr | Statistical modelling of 5-day average rainfall in Australia during 1950-2013 |
| title_full_unstemmed | Statistical modelling of 5-day average rainfall in Australia during 1950-2013 |
| title_short | Statistical modelling of 5-day average rainfall in Australia during 1950-2013 |
| title_sort | statistical modelling of 5 day average rainfall in australia during 1950 2013 |
| topic | rainfall variability classification generalised linear models factor analysis |
| url | https://rdo.psu.ac.th/sjstweb/journal/41-4/21.pdf |
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