Zhang et al. (2026) How Effective Are Time-Series Models for Precipitation Nowcasting? A Comprehensive Benchmark for GNSS-Based Precipitation Nowcasting

Identification

• Journal: IEEE Transactions on Geoscience and Remote Sensing
• Year: 2026
• Date: 2026-01-01
• Authors: Yifang Zhang, Shengwu Xiong, Henan Wang, Wenjie Yin, Jie Peng, Yuqiang Zhang, Chen Zhou, Hao Chen, Qin Zhao, Pengfei Duan
• DOI: 10.1109/tgrs.2026.3671768

Research Groups

[Information not available in the provided text]

Short Summary

[Information not available in the provided text]

Objective

• To evaluate the effectiveness of time-series models for precipitation nowcasting, specifically using GNSS-based methods, and to provide a comprehensive benchmark for these models.

Study Configuration

• Spatial Scale: [Information not available in the provided text]
• Temporal Scale: [Information not available in the provided text]

Methodology and Data

• Models used: Time-series models (specific models not detailed in the provided text)
• Data sources: GNSS-based precipitation data (specific sources not detailed in the provided text)

Main Results

• [Information not available in the provided text]

Contributions

• [Information not available in the provided text]

Funding

• [Information not available in the provided text]

Citation

@article{Zhang2026How,
  author = {Zhang, Yifang and Xiong, Shengwu and Wang, Henan and Yin, Wenjie and Peng, Jie and Zhang, Yuqiang and Zhou, Chen and Chen, Hao and Zhao, Qin and Duan, Pengfei},
  title = {How Effective Are Time-Series Models for Precipitation Nowcasting? A Comprehensive Benchmark for GNSS-Based Precipitation Nowcasting},
  journal = {IEEE Transactions on Geoscience and Remote Sensing},
  year = {2026},
  doi = {10.1109/tgrs.2026.3671768},
  url = {https://doi.org/10.1109/tgrs.2026.3671768}
}