Enhancing Weather Forecast Accuracy Through the Integration of WRF and BP Neural Networks: A Novel Approach
Abstract In the past century, scholars from both domestic and international communities have delved into the study of numerical weather prediction models to promptly understand meteorological factors and mitigate the impacts of extreme weather events on humanity. Effective and precise prediction mod...
Saved in:
| Main Authors: | Zeyang Liu, Jing Zhang, Yadong Yang, Yaping Wang, Wangjun Luo, Xiancun Zhou |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Geophysical Union (AGU)
2024-10-01
|
| Series: | Earth and Space Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2024EA003613 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Deep Learning for Atmospheric Modeling: A Proof of Concept Using a Fourier Neural Operator on WRF Data to Accelerate Transient Wind Forecasting at Multiple Altitudes
by: Paulo Alexandre Costa Rocha, et al.
Published: (2025-03-01) -
Impact of WRF Model Parameterization Settings on the Quality of Short-Term Weather Forecasts over Poland
by: Sebastian Kendzierski
Published: (2024-11-01) -
Assessment of the WRF model configuration optimization in predicting the heavy rainfall over urban city Bhubaneswar, India
by: Alugula Boyaj, et al.
Published: (2025-05-01) -
Assessing the Reliability of Seasonal Data in Representing Synoptic Weather Types: A Mediterranean Case Study
by: Alexandros Papadopoulos Zachos, et al.
Published: (2025-06-01) -
Advancements in Regional Weather Modeling for South Asia Through the High Impact Weather Assessment Toolkit (HIWAT) Archive
by: Timothy Mayer, et al.
Published: (2025-07-01)