The Utilization of Model Output Statistic (MOS) in Improving Weather Prediction Model Accuracy of Integrated Forecasting System (IFS)

Introduction/Main Objectives: Integrated Forecasting System (IFS) is one of the most accurate numerical weather prediction (NWP) model for Indonesia region. Background Problems: However, in fact, each model always has bias potential against observation which causes inaccuracy in weather prediction. Novelty: This research intends to overcome this problem by building a weather prediction model based on Model Output Statistic (MOS) to minimize bias and improve NWP accuracy. Research Methods: Provide an outline of the research method(s) and data used in this paper. Explain how did you go about doing this research. Again, avoid unnecessary content and do not make any speculation(s). Finding/Results: Analysis result states that compared to IFS, MOS fluctuation pattern is more relevant to observation. MOS has higher correlation to observation and lower error. However, the variance of observation value tends to be better represented by IFS. The test result of heavy rain cases prove that the application of MOS is able to provide fairly accurate prediction. This weather prediction will be able to be the basis for decision-making and preventive measure in dealing with extreme condition that may occur.

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Publication Details

Journal
Jurnal Aplikasi Statistika & Komputasi Statistik
Published
2024-12-24
DOI
https://doi.org/10.34123/jurnalasks.v16i2.732
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

The Utilization of Model Output Statistic (MOS) in Improving Weather Prediction Model Accuracy of Integrated Forecasting System (IFS)

Deni Septiadi, Isnaini Anjelina Ramadhan
Jurnal Aplikasi Statistika & Komputasi Statistik
Data Mining and Machine Learning Applications
article

The Utilization of Model Output Statistic (MOS) in Improving Weather Prediction Model Accuracy of Integrated Forecasting System (IFS)

Deni Septiadi, Isnaini Anjelina Ramadhan
article en

Abstract

Introduction/Main Objectives: Integrated Forecasting System (IFS) is one of the most accurate numerical weather prediction (NWP) model for Indonesia region. Background Problems: However, in fact, each model always has bias potential against observation which causes inaccuracy in weather prediction. Novelty: This research intends to overcome this problem by building a weather prediction model based on Model Output Statistic (MOS) to minimize bias and improve NWP accuracy. Research Methods: Provide an outline of the research method(s) and data used in this paper. Explain how did you go about doing this research. Again, avoid unnecessary content and do not make any speculation(s). Finding/Results: Analysis result states that compared to IFS, MOS fluctuation pattern is more relevant to observation. MOS has higher correlation to observation and lower error. However, the variance of observation value tends to be better represented by IFS. The test result of heavy rain cases prove that the application of MOS is able to provide fairly accurate prediction. This weather prediction will be able to be the basis for decision-making and preventive measure in dealing with extreme condition that may occur.

Jurnal Aplikasi Statistika & Komputasi StatistikVol. 16(2)
Meteorological, Climatological, And Geophysical Agency (ID)
Climate action
Openalex Percentile: Top 62%
Data Mining and Machine Learning Applications
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The Utilization of Model Output Statistic (MOS) in Improving Weather Prediction Model Accuracy of Integrated Forecasting System (IFS) — Deni Septiadi, Isnaini Anjelina Ramadhan · Jurnal Aplikasi Statistika & Komputasi Statistik (2024) | TGRS Research Map | TGRS