A Deep Learning Method for Real-time Bias Correction of Wind Field Forecasts in the Western North Pacific

no code implementations • 29 Dec 2022 • Wei zhang, Yueyue Jiang, Junyu Dong, Xiaojiang Song, Renbo Pang, Boyu Guoan, Hui Yu

In this study, we developed the Multi-Task-Double Encoder Trajectory Gated Recurrent Unit (MT-DETrajGRU) model, which uses an improved double-encoder forecaster architecture to model the spatiotemporal sequence of the U and V components of the wind field; we designed a multi-task learning loss function to correct wind speed and wind direction simultaneously using only one model.

Multi-Task Learning