Inas, Rosyida (2019) Proyeksi Iklim di Nusa Tenggara Timur Menggunakan Quantile Matching Bootstrap. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Berubahnya kondisi fisik atmosfer bumi antara lain suhu dan distribusi curah hujan membawa dampak luas terhadap berbagai sektor kehidupan manusia. Menurut Indonesia Food Security Monitoring Bulletin (2015), sepuluh kabupaten di Provinsi NTT menjadi prioritas pertama dalam klasifikasi kabupaten yang mengalami dampak kekeringan dari perubahan iklim yang terjadi di Indonesia. Oleh karena itu, proyeksi iklim diperlukan untuk mengetahui kondisi iklim di masa yang akan datang berdasarkan skenario iklim yang ditetapkan. Data untuk proyeksi iklim pada penelitian ini menggunakan data observasi BMKG berupa curah hujan dan suhu maksimum dan juga data General Circulation Model (GCM) dengan variabel mean daily temperature, tekanan permukaan laut, kelembaban spesifik, komponen angin, mixing ratio, dan ketinggian geopotensial. Metode untuk proyeksi iklim yang digunakan adalah metode Quantile Matching Bootstrap (QMB) yaitu dengan proyeksi kuantil dan simulasi bootstrap. Kuantil yang digunakan adalah 0,1; 0,5; dan 0,9. Hasil analisis yang dilakukan memberikan hasil bahwa persentase data observasi yang masuk ke 95% bootstrap prediction interval sudah mencapai sekitar 75% ke atas. Proyeksi curah hujan maupun suhu maksimum di NTT memberikan persentase cukup tinggi untuk bulan-bulan di musim hujan dan bulan transisi dari musim kemarau ke musim hujan. Pengecualian untuk hasil proyeksi suhu maksimum di Stasiun Meteorologi Fransiskus Xaverius Seda yang memiliki hasil paling rendah dibandingkan dengan stasiun lainnya. Dalam evaluasi hasil kebaikan metode QMB untuk proyeksi iklim di NTT diketahui bahwa metode QMB merupakan metode yang baik dikarenakan dapat melakukan proyeksi iklim untuk data harian. Metode QMB dalam hal proyeksi kuantil bulanan memiliki nilai standard error yang kecil dalam proyeksi curah hujan kuantil 0,1 dan curah hujan kuantil 0,9, serta suhu maksimum kuantil 0,1.
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Changing physical conditions of the Earth's atmosphere include temperature and distribution of rainfall, which has a wide impact on various sectors of human life. According to the Indonesia Food Security Monitoring Bulletin (2015), ten regencies in NTT Province were the first priority in the classification of districts experiencing drought impacts from climate change that occurred in Indonesia. Therefore, climate projection is needed to determine future climate conditions based on the climate scenario that is determined. Data for climate projection in this study uses BMKG observation data in the form of rainfall and maximum temperature and also General Circulation Model (GCM) data with variables: mean daily temperature, sea level pressure, wind components, specific humidity, mixing ratio, and geopotential heights. The quantiles used are 0,1; 0,5; and 0,9. The method for climate projection used is the Quantile Matching Bootstrap (QMB) method, which is the quantile projection and bootstrap simulation. The results of the analysis conducted showed that the percentage of observation data that entered the 95% bootstrap prediction interval had reached around 75% and above. The rainfall and maximum temperature projection in NTT provides a high enough percentage for the months of the rainy season and the transition month from the dry season to the rainy season. Exceptions to the results of the maximum temperature projection at Fransiskus Xaverius Seda Meteorological Station which have the lowest results compared to other stations. In evaluating the results of the fitness value of the QMB method for climate projections in NTT, it is known that the QMB method is a good method because it can do climate projections for daily data. The QMB method in terms of monthly quantile projections has a small standard error value in the 0,1 quantile rainfall and 0,9 quantile rainfall, and the 0,1 quantile maximum temperature projection.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | RTSt 519.536 Ina p-1 2019 |
| Uncontrolled Keywords: | Curah Hujan, GCM, Proyeksi Iklim, Quantile Matching Bootstrap, Suhu Maksimum |
| Subjects: | Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression Q Science > QA Mathematics > QA278.5 Principal components analysis. Factor analysis. Correspondence analysis (Statistics) |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Statistics > 49101-(S2) Master Thesis |
| Depositing User: | Rosyida Inas |
| Date Deposited: | 15 Jan 2024 02:22 |
| Last Modified: | 15 Jan 2024 02:22 |
| URI: | http://repository.its.ac.id/id/eprint/64520 |
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