Exploring the typhoon intensity forecasting through integrating AI weather forecasting with regional numerical weather model
China Meteorological Administration · Chinese Academy of Meteorological Sciences · +1 more institution
Abstract
Recent advancements in artificial intelligence (AI) have notably enhanced global weather forecasting, yet accurately predicting typhoon intensity remains challenging. This is largely due to constraints inherent in regression algorithm properties including deep neural networks and inability of coarse resolution to capture the finer-scale weather processes. To address these insufficiencies in typhoon intensity forecasting, we propose an attractive approach by initiating regional Weather Research and Forecasting (WRF) model with Pangu-weather, a state-of-the-art AI weather forecasting system (AI-Driven WRF), whose forecasting power can be further augmented by the implementation of dynamic vortex initialization.…
Citation impact
- FWCI
- 46.21
- Percentile
- 100%
- References
- 33
Authors
5- HXHongxiong Xu
China Meteorological Administration, Chinese Academy of Meteorological Sciences
- YZYang ZhaoCorresponding
Ocean University of China
- DZDajun Zhao
China Meteorological Administration, Chinese Academy of Meteorological Sciences
- YDYihong Duan
China Meteorological Administration, Chinese Academy of Meteorological Sciences
- XXXiangde Xu
China Meteorological Administration, Chinese Academy of Meteorological Sciences
Topics & keywords
- Typhoon
- Tropical cyclone forecast model
- Meteorology
- Weather Research and Forecasting Model
- Numerical weather prediction
- Weather forecasting
- Climatology
- North American Mesoscale Model
- Climate action