1. Introduction
2. Background and Related Works
2.1. Preliminaries of Time Series Precipitation Forecasting
2.2. Related Surveys
3. Datasets for Precipitation Nowcasting
3.1. Weather Radar
3.2. Weather Satellite
3.3. Sensor Fusion
3.4. Available Datasets
4. Preprocessing
4.1. Clipping
4.2. Scaling
4.3. Sampling
4.4. Sliding Window
5. Objective Functions
5.1. Weighted Loss
5.2. Pooling Loss
5.3. Motion Loss
5.4. Nowcasting Loss
5.5. Plotting Position Loss
6. Evaluation Metrics
6.1. Global-Level Accuracy
6.2. Binary Accuracy
6.3. Downscale Accuracy
6.4. Sharpness Accuracy
7. Recursive Strategy
7.1. Non-Adversarial-Based Methods
7.2. Adversarial-Based Methods
8. Multiple Strategy
8.1. UNet-Based Methods
8.2. Diffusion-Based Methods
8.3. Transformer-Based Methods
9. Methodology Comparison and Evaluation
9.1. Methodology Comparison
9.2. Performance Evaluation
10. Future Challenges and Opportunities
10.1. Long Lead Time
10.2. Multi-Sensor Data Fusion
10.3. Data Augmentation
10.4. Standard Evaluation Protocols
11. Conclusion