Developing a Real-Time Rainfall Forecasting System Using Weather Satellite Imagery
Date Issued
2005
Date
2005
Author(s)
Hong, Wei-Chun
DOI
zh-TW
Abstract
In this study, a feasible system must be built to realize a numerical model that can predict cumulative rainfall of Central Taiwan, by using GMS-5 geostationary meteorological satellite images and hourly rainfall data of some auto-recording rain gauges in Central Taiwan. During the study, rainfall records were used to estimate from dotted data to grid data by Block Kriging Estimation that match the pixels in satellite images, and satellite images were processed to represent the cloud top temperature data (CTT). The kernel function, that means the spatial characteristic of Central Taiwan, was calculated by the grid rainfall data and processed cloud top temperature above using Spatial Convolution Integral. Let the kernel function seemed as the state variable in a time-variant system, Kalman Filtering Algorithm was proposed to forecast this system’s state variable of next time. Then the forecasting can be calculated by Spatial Convolution Integral Technique again to transform into predictions of rainfall. Besides the numerical model development, this study built a practical system that predict rainfall of Central Taiwan by the model. By using the Graphical User Interface (GUI), and updating data hourly, the system will give the predicted data directly.
After using two historical typhoon events as trials, the system can predict the trend during whole rainfall events and warn the dangerous districts; but there are still a problem of time-lag makes some error predictions.
Subjects
雨量預測
雨量推估
空間摺合積分
卡門濾波演算
Rainfall Prediction
Rainfall Estimation
Spatial Convolution Integral
Kalman Filtering Algorithm
Type
thesis