Two-Stage Spatiotemporal Context Refinement Network for Precipitation Nowcasting

• Published in: Remote sensing (Basel, Switzerland) Vol. 13; no. 21; p. 4285
• Main Authors: Niu, Dan, Huang, Junhao, Zang, Zengliang, Xu, Liujia, Che, Hongshu, Tang, Yuanqing
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2021
• Subjects: Accuracy; Algorithms; China; Coders; Context; data collection; Datasets; Deep learning; Feature extraction; image analysis; Image quality; Lead time; Learning algorithms; Machine learning; Methods; Neural networks; Nowcasting; Precipitation; precipitation nowcasting; prediction; Predictions; Radar; Radar echoes; Radar imaging; Rain; Rainfall; refinement network; Remote sensing; RNN; spatiotemporal prediction; Weather forecasting; China

Precipitation nowcasting by radar echo extrapolation using machine learning algorithms is a field worthy of further study, since rainfall prediction is essential in work and life. Current methods of predicting the radar echo images need further improvement in prediction accuracy as well as in presen...