STATISTICAL DOWNSCALING USING REGRESSION NONPARAMETRIC OF FOURIER SERIES-POLYNOMIAL LOCAL OF CLIMATE CHANGE
Indonesia is a tropical country that is vulnerable to the impacts of climate change. Climate change causes an effect on the level of comfort (heat stress) that can affect the level of human immunity, one of the indices to calculate the level of human comfort (heat stress) is the Thermal Humidity Ind...
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Universitas Pattimura
2023-09-01
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| Series: | Barekeng |
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8139 |
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| author | Tiani Wahyu Utami Fatkhurokhman Fauzi Eko Yuliyanto |
| author_facet | Tiani Wahyu Utami Fatkhurokhman Fauzi Eko Yuliyanto |
| author_sort | Tiani Wahyu Utami |
| collection | DOAJ |
| description | Indonesia is a tropical country that is vulnerable to the impacts of climate change. Climate change causes an effect on the level of comfort (heat stress) that can affect the level of human immunity, one of the indices to calculate the level of human comfort (heat stress) is the Thermal Humidity Index (THI). Climate change scenarios modeled in Earth System Models (ESMs). ESM has a coarse resolution and is subject to considerable bias. This research is using secondary data. The data source used in this study comes from the Coupled Model Intercomparison Project (CMIP5). This research will focus on projected heat stress which is calculated based on THI with the temperature and humidity variables. Therefore, in this research to reduce the bias correction method used Statistical Downscaling (SD) and nonparametric regression. The results of the bias correction using the Statistical Downscaling (SD) method and Nonparametric Regression Fourier-Polynomial Local Series in this study the R-square value for Relative Humidity yields 95% and for Temperature yields 94%. The projection of climate change based on the value of the Temperature Humidity Index (THI) in Indonesia in the category of 50% of the population of Indonesians feeling comfortable conditions occurred in 2006-2059. Then the population of citizens in Indonesia felt uncomfortable conditions occurred in 2060 to 2100 with a THI value of 27.0730°C - 27.7800°C. |
| format | Article |
| id | doaj-art-d50e03263e8445b78167bca661f71ca0 |
| institution | DOAJ |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2023-09-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-d50e03263e8445b78167bca661f71ca02025-08-20T03:02:45ZengUniversitas PattimuraBarekeng1978-72272615-30172023-09-011731411141810.30598/barekengvol17iss3pp1411-14188139STATISTICAL DOWNSCALING USING REGRESSION NONPARAMETRIC OF FOURIER SERIES-POLYNOMIAL LOCAL OF CLIMATE CHANGETiani Wahyu Utami0Fatkhurokhman Fauzi1Eko Yuliyanto2Statistics Study Program, Universitas Muhammadiyah Semarang, IndonesiaStatistics Study Program, Universitas Muhammadiyah Semarang, IndonesiaChemistry Education Study Program, Universitas Muhammadiyah Semarang, IndonesiaIndonesia is a tropical country that is vulnerable to the impacts of climate change. Climate change causes an effect on the level of comfort (heat stress) that can affect the level of human immunity, one of the indices to calculate the level of human comfort (heat stress) is the Thermal Humidity Index (THI). Climate change scenarios modeled in Earth System Models (ESMs). ESM has a coarse resolution and is subject to considerable bias. This research is using secondary data. The data source used in this study comes from the Coupled Model Intercomparison Project (CMIP5). This research will focus on projected heat stress which is calculated based on THI with the temperature and humidity variables. Therefore, in this research to reduce the bias correction method used Statistical Downscaling (SD) and nonparametric regression. The results of the bias correction using the Statistical Downscaling (SD) method and Nonparametric Regression Fourier-Polynomial Local Series in this study the R-square value for Relative Humidity yields 95% and for Temperature yields 94%. The projection of climate change based on the value of the Temperature Humidity Index (THI) in Indonesia in the category of 50% of the population of Indonesians feeling comfortable conditions occurred in 2006-2059. Then the population of citizens in Indonesia felt uncomfortable conditions occurred in 2060 to 2100 with a THI value of 27.0730°C - 27.7800°C.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8139climate changefourier seriesnonparametric regressionpolynomial localstatistical downscalingthermal humidity index (thi) |
| spellingShingle | Tiani Wahyu Utami Fatkhurokhman Fauzi Eko Yuliyanto STATISTICAL DOWNSCALING USING REGRESSION NONPARAMETRIC OF FOURIER SERIES-POLYNOMIAL LOCAL OF CLIMATE CHANGE Barekeng climate change fourier series nonparametric regression polynomial local statistical downscaling thermal humidity index (thi) |
| title | STATISTICAL DOWNSCALING USING REGRESSION NONPARAMETRIC OF FOURIER SERIES-POLYNOMIAL LOCAL OF CLIMATE CHANGE |
| title_full | STATISTICAL DOWNSCALING USING REGRESSION NONPARAMETRIC OF FOURIER SERIES-POLYNOMIAL LOCAL OF CLIMATE CHANGE |
| title_fullStr | STATISTICAL DOWNSCALING USING REGRESSION NONPARAMETRIC OF FOURIER SERIES-POLYNOMIAL LOCAL OF CLIMATE CHANGE |
| title_full_unstemmed | STATISTICAL DOWNSCALING USING REGRESSION NONPARAMETRIC OF FOURIER SERIES-POLYNOMIAL LOCAL OF CLIMATE CHANGE |
| title_short | STATISTICAL DOWNSCALING USING REGRESSION NONPARAMETRIC OF FOURIER SERIES-POLYNOMIAL LOCAL OF CLIMATE CHANGE |
| title_sort | statistical downscaling using regression nonparametric of fourier series polynomial local of climate change |
| topic | climate change fourier series nonparametric regression polynomial local statistical downscaling thermal humidity index (thi) |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/8139 |
| work_keys_str_mv | AT tianiwahyuutami statisticaldownscalingusingregressionnonparametricoffourierseriespolynomiallocalofclimatechange AT fatkhurokhmanfauzi statisticaldownscalingusingregressionnonparametricoffourierseriespolynomiallocalofclimatechange AT ekoyuliyanto statisticaldownscalingusingregressionnonparametricoffourierseriespolynomiallocalofclimatechange |