Manfaat Prediksi Cuaca Jangka Pendek Berdasarkan Data Radiosonde Dan Numerical Weather Prediction (NWP) Untuk Pertanian Daerah
Prosiding Seminas
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Title |
Manfaat Prediksi Cuaca Jangka Pendek Berdasarkan Data Radiosonde Dan Numerical Weather Prediction (NWP) Untuk Pertanian Daerah
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Creator |
wardani, indra kusuma
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Description |
ABSTRAK Indonesia sebagai negara maritime-continent mempunyai karakteristik cuaca yang beragam di berbagai daerah. Informasi tentang prakiraan cuaca yang cepat dan tepat menjadi suatu hal yang penting sehingga diperlukan metode yang efektif dalam prakiraan cuaca. Penelitian ini didasarkan pada data radiosonde dan Numerical Weather Prediction (NWP)Â menggunakan data observasi pada 00 Universal Time Coordinate (UTC) dan 12 UTC. Analisis data radiosonde dilakukan terhadap variabel permukaan dan indeks K yang digunakan untuk kajian stabilitas atmosfer dan potensi thunderstorm. Hasil analisis data radiosonde menunjukkan fluktuasi variabel permukaan selama observasi dan indeks K tertinggi pada musim penghujan. Metode NWP menggunakan 4 variabel prediktan dan 9 variabel prediktor. Analisis dilakukan dengan mereduksi dimensi variabel prediktor terhadap dimensi horisontal (grid) dan dimensi ketinggian (level) menggunakan Principal Component Analysis (PCA) dan analisis regresi multivariate. Prediksi cuaca menunjukkan hasil yang cukup relevan antara data observasi dan data dugaan yang ditunjukkan dengan nilai korelasi sebesar 67%. Kata kunci: radiosonde, numerical weather prediction, variabel permukaan, indeks K, principal component analysis. Â Â ABSTRACT Indonesia as a continent- maritime has a climate characteristics in different regions. Information on fast and accurate weather forecasts to be one important needed an effective method of forecasting the weather. The study was based on radiosonde data and Numerical Weather Prediction (NWP) using observational data at 00 Universal Time Coordinates (UTC) and 12 UTC. Radiosonde data analysis performed on the surface variables and K-index that are used to study the stability of the atmosphere and the potential of a thunderstorm. The results of the analysis of radiosonde data showed fluctuations in the surface variables during the observation and the highest K-index in the rainy season. NWP method using 4 variables predictant and 9 predictor variables. The analysis was done by reducing the dimensions of a predictor variable on the horizontal dimension (grid) and higher dimensions (levels) by using the Principal Component Analysis (PCA) and multivariate regression analysis. Weather prediction shows a fairly relevant results between observational data and the data shown by the allegations that the correlation value by 67%. Keywords: radiosonde, numerical weather prediction, variable surface, K indices, principal component analysis.
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Publisher |
Unipdu Jombang
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Contributor |
—
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Date |
2012-04-01
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Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion Artikel Peer-review |
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Format |
application/pdf
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Identifier |
https://journal.unipdu.ac.id/index.php/seminas/article/view/42
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Source |
Prosiding Seminas Competitive Advantage; Vol 1, No 1 (2011): Seminas Competitive Advantage I
Prosiding Seminas; Vol 1, No 1 (2011): Seminas Competitive Advantage I |
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Language |
eng
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Relation |
https://journal.unipdu.ac.id/index.php/seminas/article/view/42/42
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