Introduction
Project Introduction:
Weather AI utilizes various methods to acquire weather data and employs machine learning for weather prediction. Currently, the project includes:
- Ground Observation Data: Based on the uneven distribution of precipitation in Taiwan, the project analyzes the time trends and relationships among meteorological factors such as atmospheric pressure, temperature, and precipitation. It aims to propose efficient and accurate models for predicting future precipitation.
- Radar Echo Maps: Radar echo maps effectively detect rainfall within a certain range. By utilizing past radar echo map datasets and integrating them with machine learning models, the project predicts and generates future echo maps to provide more precise rainfall information for weather forecasting.
- Satellite Cloud Images: Since radar detection has limited coverage, the project combines satellite cloud images with radar echo maps. By transforming satellite cloud images into radar echo maps, it expands the radar's detection range, offering more comprehensive weather information.
Project Features:
- The project covers a wide range of extendable topics, providing numerous research opportunities.
- Participants can learn various weather-related information through this project.
- It offers an effective learning experience on utilizing machine learning for weather prediction.