Comparison and Analysis of Rainfall Spatial Patterns IMERG (Integrated Multi-Satellite Retrievals for GPM) Data and Observation Data on Bali Province
Limitations of observational data such as insufficient data length, incomplete, and uneven station distribution make it difficult to analyze and predict rain, so it requires supporting instruments such as satellites to provide a better and broader picture of rainfall distribution. However, it is nec...
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| Format: | Article |
| Language: | English |
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Universitas Udayana
2020-11-01
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| Series: | Buletin Fisika |
| Online Access: | https://ojs.unud.ac.id/index.php/buletinfisika/article/view/65117 |
| _version_ | 1818885515991056384 |
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| author | Desy Yunita samosir I Made Yuliara Rakhmat Prasetia |
| author_facet | Desy Yunita samosir I Made Yuliara Rakhmat Prasetia |
| author_sort | Desy Yunita samosir |
| collection | DOAJ |
| description | Limitations of observational data such as insufficient data length, incomplete, and uneven station distribution make it difficult to analyze and predict rain, so it requires supporting instruments such as satellites to provide a better and broader picture of rainfall distribution. However, it is necessary to test the accuracy of satellite data because the resolution and conditions of each region are different. This research aims to validate IMERG rain data against observation data in the 2015 El Nino period using observation rainfall data from BMKG Negara and IMERG data from GPM satellite at 12 rain points in Bali Province. The analytical method used is quantitative statistics, the calculation of errors and correlations and the comparison of the spatial pattern of the two data. The results of the analysis of the spatial pattern of the IMERG data show that, there was a decrease in rainfall from May to July, but the rainfall increased into August, and again experienced a decline entering the months of September to December where the same pattern was also shown from the results of the spatial pattern analysis on the Observation data. The decrease in rainfall in the May-December 2015 period was a strong El Nino effect as evidenced by the results of the correlation analysis of the SOI index on rainfall which showed a fairly strong correlation value, namely 0.55.The validation of IMERG data on monthly observation data showed that the average correlation was sufficient strong is 0.42 and analysis per rain post shows a weak correlation namely 0.31, which means that data IMERG is not yet accurate as an alternative to the observation rainfall data in Bali Province. |
| first_indexed | 2024-12-19T16:06:41Z |
| format | Article |
| id | doaj.art-1c837a2e9d6a4e2e9db0240cd69e3f59 |
| institution | Directory Open Access Journal |
| issn | 1411-4690 2580-9733 |
| language | English |
| last_indexed | 2024-12-19T16:06:41Z |
| publishDate | 2020-11-01 |
| publisher | Universitas Udayana |
| record_format | Article |
| series | Buletin Fisika |
| spelling | doaj.art-1c837a2e9d6a4e2e9db0240cd69e3f592022-12-21T20:14:50ZengUniversitas UdayanaBuletin Fisika1411-46902580-97332020-11-01222677610.24843/BF.2021.v22.i02.p1065117Comparison and Analysis of Rainfall Spatial Patterns IMERG (Integrated Multi-Satellite Retrievals for GPM) Data and Observation Data on Bali ProvinceDesy Yunita samosir0I Made Yuliara1Rakhmat Prasetia2FisikaUdayana UniversityUdayana UniversityLimitations of observational data such as insufficient data length, incomplete, and uneven station distribution make it difficult to analyze and predict rain, so it requires supporting instruments such as satellites to provide a better and broader picture of rainfall distribution. However, it is necessary to test the accuracy of satellite data because the resolution and conditions of each region are different. This research aims to validate IMERG rain data against observation data in the 2015 El Nino period using observation rainfall data from BMKG Negara and IMERG data from GPM satellite at 12 rain points in Bali Province. The analytical method used is quantitative statistics, the calculation of errors and correlations and the comparison of the spatial pattern of the two data. The results of the analysis of the spatial pattern of the IMERG data show that, there was a decrease in rainfall from May to July, but the rainfall increased into August, and again experienced a decline entering the months of September to December where the same pattern was also shown from the results of the spatial pattern analysis on the Observation data. The decrease in rainfall in the May-December 2015 period was a strong El Nino effect as evidenced by the results of the correlation analysis of the SOI index on rainfall which showed a fairly strong correlation value, namely 0.55.The validation of IMERG data on monthly observation data showed that the average correlation was sufficient strong is 0.42 and analysis per rain post shows a weak correlation namely 0.31, which means that data IMERG is not yet accurate as an alternative to the observation rainfall data in Bali Province.https://ojs.unud.ac.id/index.php/buletinfisika/article/view/65117 |
| spellingShingle | Desy Yunita samosir I Made Yuliara Rakhmat Prasetia Comparison and Analysis of Rainfall Spatial Patterns IMERG (Integrated Multi-Satellite Retrievals for GPM) Data and Observation Data on Bali Province Buletin Fisika |
| title | Comparison and Analysis of Rainfall Spatial Patterns IMERG (Integrated Multi-Satellite Retrievals for GPM) Data and Observation Data on Bali Province |
| title_full | Comparison and Analysis of Rainfall Spatial Patterns IMERG (Integrated Multi-Satellite Retrievals for GPM) Data and Observation Data on Bali Province |
| title_fullStr | Comparison and Analysis of Rainfall Spatial Patterns IMERG (Integrated Multi-Satellite Retrievals for GPM) Data and Observation Data on Bali Province |
| title_full_unstemmed | Comparison and Analysis of Rainfall Spatial Patterns IMERG (Integrated Multi-Satellite Retrievals for GPM) Data and Observation Data on Bali Province |
| title_short | Comparison and Analysis of Rainfall Spatial Patterns IMERG (Integrated Multi-Satellite Retrievals for GPM) Data and Observation Data on Bali Province |
| title_sort | comparison and analysis of rainfall spatial patterns imerg integrated multi satellite retrievals for gpm data and observation data on bali province |
| url | https://ojs.unud.ac.id/index.php/buletinfisika/article/view/65117 |
| work_keys_str_mv | AT desyyunitasamosir comparisonandanalysisofrainfallspatialpatternsimergintegratedmultisatelliteretrievalsforgpmdataandobservationdataonbaliprovince AT imadeyuliara comparisonandanalysisofrainfallspatialpatternsimergintegratedmultisatelliteretrievalsforgpmdataandobservationdataonbaliprovince AT rakhmatprasetia comparisonandanalysisofrainfallspatialpatternsimergintegratedmultisatelliteretrievalsforgpmdataandobservationdataonbaliprovince |