每年專案
摘要
Increasing the accuracy of rainfall forecasts is crucial as an effort to prevent hydrometeorological disasters. Weather changes that can occur suddenly and in a local scope make fast and precise weather forecasts increasingly difficult to inform. Additionally, the results of the numerical weather model used by the Indonesia Agency for Meteorology, Climatology, and Geophysics are only able to predict the rainfall with a temporal resolution of 1–3 h and cannot yet address the need for rainfall information with high spatial and temporal resolution. Therefore, this study aims to provide the rainfall forecast in high spatiotemporal resolution using Himawari-8 and GPM IMERG (Global Precipitation Measurement: The Integrated Multi-satellite Retrievals) data. The multivariate LSTM (long short-term memory) forecasting is employed to predict the cloud brightness temperature by using the selected Himawari-8 bands as the input and training data. For the rain rate regression, we used the random forest technique to identify the rainfall and non-rainfall pixels from GPM IMERG data as the input in advance. The results of the rainfall forecast showed low values of mean error and root mean square error of 0.71 and 1.54 mm/3 h, respectively, compared to the observation data, indicating that the proposed study may help meteorological stations provide the weather information for aviation purposes.
原文 | ???core.languages.en_GB??? |
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文章編號 | 5950 |
期刊 | Remote Sensing |
卷 | 14 |
發行號 | 23 |
DOIs | |
出版狀態 | 已出版 - 12月 2022 |
指紋
深入研究「Rainfall Forecast Using Machine Learning with High Spatiotemporal Satellite Imagery Every 10 Minutes」主題。共同形成了獨特的指紋。專案
- 2 已完成
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亞洲大氣污染物之整合監測與其對環境及氣候之衝擊研究-國際參與(II)-整合衛星與地面觀測氣膠參數在空氣品質預報三維初始場之建構與應用(總計畫及子計畫六)
Lin, T.-H. (PI)
1/08/22 → 31/07/23
研究計畫: Research
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整合福衛衛星資料在台灣環境健康暴露度加值產品之建構-整合福衛衛星資料在台灣環境健康暴露度加值產品之建構(1/3)
Lin, T.-H. (PI)
1/05/22 → 30/04/23
研究計畫: Research