Ma et al. (2025) PWVFnet: A Short-Time Troposphere PWV Forecast Model Combined Empirical Models and Spatiotemporal ConvLSTM Network

Identification

• Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• Year: 2025
• Date: 2025-12-25
• Authors: Xiongwei Ma, Yunzheng Huang, Qi Zhang, Bao Zhang, Xing Gao, Qingzhi Zhao, Xiaohu Lin, Chaoqian Xu, Yibin Yao
• DOI: 10.1109/jstars.2025.3648114

Research Groups

Information not available in the provided text.

Short Summary

This paper introduces PWVFnet, a novel model for short-time forecasting of tropospheric precipitable water vapor (PWV), which integrates empirical models with a spatiotemporal ConvLSTM network. The main findings are not detailed in the provided text.

Objective

• To develop and evaluate PWVFnet, a short-time forecast model for tropospheric precipitable water vapor (PWV) by combining empirical models and a spatiotemporal ConvLSTM network.

Study Configuration

• Spatial Scale: Troposphere (specific geographical extent or resolution not provided).
• Temporal Scale: Short-time forecast (specific duration not provided).

Methodology and Data

• Models used: PWVFnet, which combines empirical models and a spatiotemporal ConvLSTM network.
• Data sources: Information not available in the provided text.

Main Results

Information not available in the provided text.

Contributions

The primary contribution is the introduction of PWVFnet, a new model architecture for short-time tropospheric PWV forecasting that leverages the synergy between empirical models and spatiotemporal ConvLSTM networks. Specific advancements or performance improvements are not detailed in the provided text.

Funding

Information not available in the provided text.

Citation

@article{Ma2025PWVFnet,
  author = {Ma, Xiongwei and Huang, Yunzheng and Zhang, Qi and Zhang, Bao and Gao, Xing and Zhao, Qingzhi and Lin, Xiaohu and Xu, Chaoqian and Yao, Yibin},
  title = {PWVFnet: A Short-Time Troposphere PWV Forecast Model Combined Empirical Models and Spatiotemporal ConvLSTM Network},
  journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year = {2025},
  doi = {10.1109/jstars.2025.3648114},
  url = {https://doi.org/10.1109/jstars.2025.3648114}
}