Search Results for author:
Found 5 papers, 1 papers with code
Climate Trends of Tropical Cyclone Intensity and Energy Extremes Revealed by Deep Learning
By training with uniquely labeled data integrating best tracks and numerical model analysis of 2004 to 2018 TCs, our model converts multichannel satellite imagery to a 0-750-km wind profile of axisymmetric surface winds.
Accurate and Clear Precipitation Nowcasting with Consecutive Attention and Rain-map Discrimination
We propose a new deep learning model for precipitation nowcasting that includes both the discrimination and attention techniques.
CNN Profiler on Polar Coordinate Images for Tropical Cyclone Structure Analysis
This study applies CNN on satellite images to create the entire TC structure profiles, covering all the structural parameters.
Real-time Tropical Cyclone Intensity Estimation by Handling Temporally Heterogeneous Satellite Data
Analyzing big geophysical observational data collected by multiple advanced sensors on various satellite platforms promotes our understanding of the geophysical system.
Benchmarking Tropical Cyclone Rapid Intensification with Satellite Images and Attention-based Deep Models
In addition, the human-driven nature of such an approach makes it difficult to reproduce and benchmark prediction models.
