Enhancing Nowcasting With Multi‐Resolution Inputs Using Deep Learning: Exploring Model Decision Mechanisms
Abstract Nowcasting methods based on deep learning typically rely solely on radar data. However, effectively leveraging multi‐source data with diverse spatio‐temporal resolutions remains a significant challenge in the field. To address this challenge, we propose and validate a novel deep learning mo...
Saved in:
| Main Authors: | Yuan Cao, Lei Chen, Junjing Wu, Jie Feng |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-02-01
|
| Series: | Geophysical Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2024GL113699 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Climate nowcasting
by: Andrew Gettelman, et al.
Published: (2025-01-01) -
Deep Learning Model for Precipitation Nowcasting Based on Residual and Attention Mechanisms
by: Zhan Zhang, et al.
Published: (2025-03-01) -
CPrecNet: Enhanced Nowcast of High‐Resolution Short‐Term Precipitation Using Deep Learning
by: Jun Park, et al.
Published: (2025-07-01) -
SwinNowcast: A Swin Transformer-Based Model for Radar-Based Precipitation Nowcasting
by: Zhuang Li, et al.
Published: (2025-04-01) -
RainHCNet: Hybrid High-Low Frequency and Cross-Scale Network for Precipitation Nowcasting
by: Lei Wang, et al.
Published: (2025-01-01)