Wavelet/Fourier-Domain Losses for Weather Prediction
Frequency-guided learning for spatially sharper precipitation prediction.
This project explores frequency-domain guidance for precipitation prediction.
The core idea is to encourage weather prediction models to better preserve spatial details by combining global Fourier-domain information with local wavelet-domain structure.
Methods studied include Fourier-domain losses and Dual Tree Complex Wavelet Transform guidance.
Related manuscript:
- Toward Spatially Sharper Precipitation Prediction via Global-Local Frequency Guidance.
- Under revision at npj Climate and Atmospheric Science.